an illustrated atlas of pat signals in sleep...

An Illustrated Atlas of

PAT Signals in Sleep Medicine

Amir Bar M.D. B’nai Zion Medical Center, Haifa

Giora Pillar M.D. D.Sc. Rambam Medical Center, Haifa

Robert P Schnall D.Sc. Itamar Medical, Caesarea

Jacob Sheffy PhD. Itamar Medical, Caesarea

Copyright 2009 by Itamar Medical Ltd.

“An Illustrated Atlas of PAT™ Signals in Sleep Medicine” Copyright 2009 Authors in alphabetical order: Amir Bar M.D. B’nai Zion Medical Center, Haifa Giora Pillar M.D. D.Sc. Rambam Medical Center, Haifa Robert P Schnall D.Sc. Itamar Medical, Caesarea Jacob Sheffy PhD. Itamar Medical, Caesarea PAT is a registered trademark of Itamar Medical Ltd. Part number: IP2100101 Itamar Medical Ltd. Tel: +972-4-617 7000 Fax: +972-4 627 5598 Email: [email protected] Web: www.itamar-medical.com

Table of Contents PART A: PERIPHERAL ARTERIAL TONE (PAT) SIGNAL OVERVIEW IN SLEEP MEDICINE. ........... 1

A.1. Conceptual Basis For The Clinical Application ............................................................. 1 A.1.1. Clinical Applications .............................................................................................. 1 A.1.2. Rationale of PAT signal as a non-invasive physiological marker .......................... 1 A.1.3. Essential overview of the PAT signal..................................................................... 2 A.1.4. The finger tip as a measurement site....................................................................... 3

A.2. PAT Application In Sleep Medicine............................................................................... 5 A.2.1. Detection of sleep-disordered breathing ................................................................. 5 A.2.2. Detection of REM sleep.......................................................................................... 6 A.2.3. Detection of Cheyne-Stokes breathing in Congestive Heart Failure patients......... 7

PART B: ILLUSTRATED SCREENS OF WATCHPAT SIGNALS ....................................................... 9 B.1. Recordings of normal individuals................................................................................. 10

B.1.1. Wakefulness (3-minute screen)............................................................................. 11 B.1.2. Non-REM sleep (30-second screen) ..................................................................... 13 B.1.3. Non-REM sleep (1 minute screen) ....................................................................... 15 B.1.4. Non-REM sleep (2-minute screen) ....................................................................... 17 B.1.5. Non-REM sleep (3-minute screen) ....................................................................... 19 B.1.6. Non-REM sleep (5-minute screen) ....................................................................... 21 B.1.7. Detection of REM sleep........................................................................................ 23 B.1.8. REM sleep (3-minute screen) ............................................................................... 24 B.1.9. REM sleep (10 minute screen).............................................................................. 26 B.1.10. REM sleep (50-minute screen illustrating REM onset and offset) ....................... 27 B.1.11. REM sleep (2-hour screen) ................................................................................... 29

B.2. Breathing disorders during sleep .................................................................................. 30 B.2.1. OSA, WatchPAT + PSG, hypopneas.................................................................... 31 B.2.2. OSA, WatchPAT + PSG, hypopneas and UARS ................................................. 34 B.2.3. OSA, WatchPAT + PSG, hypopneas and UARS ................................................. 35 B.2.4. Upper Airway Resistance Syndrome (UARS)...................................................... 36 B.2.5. Central Sleep Apnea (CSA) .................................................................................. 40 B.2.6. CSA, WatchPAT + PSG ....................................................................................... 40 B.2.7. CSR, WatchPAT + PSG ....................................................................................... 42

B.3. Other forms of Sleep fragmentation ............................................................................. 44 B.3.1. PLMD without arousals, WatchPAT + PSG ........................................................ 45 B.3.2. PLMD with borderline arousals, WatchPAT + PSG ............................................ 46 B.3.3. PLMD with arousals, WatchPAT + PSG.............................................................. 47 B.3.4. PLMD and SDB, WatchPAT + PSG .................................................................... 48 B.3.5. PLMD and SDB, WatchPAT + PSG .................................................................... 49 B.3.6. PLMD and UARS, WatchPAT + PSG ................................................................. 50

B.4. Detecting Arrhythmias.................................................................................................. 52 B.4.1. Premature beats, WatchPAT + PSG ..................................................................... 53 B.4.2. Bigeminy............................................................................................................... 56 B.4.3. Quadrigeminy ....................................................................................................... 57

B.4.4. Skipping beats....................................................................................................... 59 B.4.5. Paroxysmal Atrial Fibrillation (5 min) ................................................................. 60 B.4.6. Paroxysmal Atrial Fibrillation (1 minute)............................................................. 61 B.4.7. Paroxysmal Atrial Fibrillation (20 seconds) ......................................................... 62

PART C: PAT MEASUREMENT TECHNOLOGY: KEY PHYSIOLOGICAL, BIOPHYSICAL AND PROBE

DESIGN CONSIDERATIONS.............................................................................................................. 63 C.1.1. PAT probe Design Features .................................................................................. 63 C.1.2. PAT technology in comparison to conventional plethysmographic methods; ..... 68 C.1.3. Resolving the disadvantages of VOP and segmental plethysmography............... 68 C.1.4. The PAT technology solution to traditional plethysmographs’ drawbacks.......... 70

C.1.4.1. Full-length, uniform pressure anti venous pooling region............................ 70 C.1.4.2. Extended pressure field buffer region........................................................... 70 C.1.4.3. Ability to unload arterial wall tension without causing venous pooling. ..... 70

C.1.5. Overview of the self-contained pneumo-optical PAT system.............................. 71 C.1.6. Technical features of the self-contained PAT probe and support system............. 71 C.1.7. Isobaric, volume displacement PAT probe design ............................................... 71 C.1.8. Technical features of the wrist mounted supporting device ................................. 73

PART D: List of References ..................................................................................................... 74

List of Figures Figure 1: Dose response curves of finger/forearm:-(α and β adrenergic agonists)......................... 4 Figure 2: Three-minute trace of PAT signal during repeated apneic episodes............................... 6 Figure 3: Marked sustained attenuation of the PAT signal during REM ....................................... 7 Figure 4: PAT oscillatory pattern in-phase with breathing/non-breathing respiration pattern....... 8 Figure 5: Wakefulness (3-minute screen) ..................................................................................... 11 Figure 6: Wakefulness (3-minute screen) ..................................................................................... 12 Figure 7: Non-REM sleep (30-second screen).............................................................................. 13 Figure 8: Non-REM sleep (30-second screen).............................................................................. 14 Figure 9: non-REM sleep (1 minute screen)................................................................................. 15 Figure 10: non-REM sleep (1 minute screen)............................................................................... 16 Figure 11: Non-REM sleep (2-minute screen).............................................................................. 17 Figure 12: Non-REM sleep (2-minute screen).............................................................................. 18 Figure 13: Non-REM sleep (3-minute screen).............................................................................. 19 Figure 14: Non-REM sleep (3-minute screen).............................................................................. 20 Figure 15: Non-REM sleep (3-minute screen).............................................................................. 20 Figure 16: Non-REM sleep (5-minute screen).............................................................................. 21 Figure 17: non-REM sleep (5-minute screen) .............................................................................. 22 Figure 18: REM sleep (3-minute screen)...................................................................................... 24 Figure 19: REM sleep (3-minute screen)...................................................................................... 25 Figure 20: REM sleep (10 minute screen) .................................................................................... 26 Figure 21: REM sleep (50-minute screen illustrating REM onset and offset) .............................27 Figure 22: REM sleep (50-minute screen illustrating REM onset and offset) .............................28 Figure 23: REM sleep (2 hours screen) ........................................................................................ 29 Figure 24: OSA, WatchPAT + PSG, hypopneas .......................................................................... 32 Figure 25: OSA, WatchPAT + PSG, hypopneas .......................................................................... 32 Figure 26: OSA, WatchPAT + PSG, hypopneas .......................................................................... 33 Figure 27: OSA, WatchPAT + PSG, hypopneas .......................................................................... 33 Figure 28: OSA, WatchPAT + PSG, hypopneas and UARS........................................................ 34 Figure 29: OSA, WatchPAT + PSG, hypopneas and UARS........................................................ 35 Figure 30: UARS, WatchPAT + PSG........................................................................................... 37 Figure 31: UARS, WatchPAT + PSG........................................................................................... 37 Figure 32: UARS, WatchPAT only .............................................................................................. 38 Figure 33: UARS, WatchPAT only .............................................................................................. 39 Figure 34: CSA, WatchPAT + PSG.............................................................................................. 40 Figure 35: CSA, WatchPAT + PSG.............................................................................................. 41 Figure 36: CSR, WatchPAT + PSG.............................................................................................. 42 Figure 37: CSR, WatchPAT + PSG.............................................................................................. 43 Figure 38: PLMD without arousals, WatchPAT + PSG............................................................... 45 Figure 39: PLMD with borderline arousals, WatchPAT + PSG................................................... 46 Figure 40: PLMD with arousals, WatchPAT + PSG.................................................................... 47 Figure 41: PLMD and SDB, WatchPAT + PSG........................................................................... 48 Figure 42: PLMD and SDB, WatchPAT + PSG........................................................................... 49 Figure 43: PLMD and UARS, WatchPAT + PSG........................................................................ 50

Figure 44: PLMD and UARS, WatchPAT + PSG........................................................................ 51 Figure 45: premature beats, WatchPAT + PSG............................................................................ 53 Figure 46: premature beats, WatchPAT + PSG............................................................................ 54 Figure 47: premature beats, WatchPAT + PSG............................................................................ 54 Figure 48: premature beats, WatchPAT + PSG............................................................................ 55 Figure 49: Bigeminy ..................................................................................................................... 56 Figure 50: Quadrigeminy.............................................................................................................. 57 Figure 51: Quadrigeminy.............................................................................................................. 58 Figure 52: Skipping beats ............................................................................................................. 59 Figure 53: Paroxysmal Atrial Fibrillation (5-minute)................................................................... 60 Figure 54: Paroxysmal Atrial Fibrillation (1 minute) ................................................................... 61 Figure 55: Paroxysmal Atrial Fibrillation (20 seconds) ............................................................... 62 Figure 56: Cross-sectional view through the pneumo-optical PAT finger probe......................... 64 Figure 57: Arterial compliance curve ........................................................................................... 65 Figure 58: Arterial Pressure vs. Volume compliance Curve ........................................................ 66 Figure 59: Acute effect of venous blood pooling on arterial pulse amplitude.............................. 67 Figure 60: Opposing effects of vascular unloading and venous pooling...................................... 69 Figure 61: Functional attributes of the self-contained PAT probe. .............................................. 71 Figure 62: Functional similarity of optical and volumetric signals .............................................. 72

An Illustrated Atlas of PAT Signals - 1 - ©Itamar-Medical Inc.

PART A: PERIPHERAL ARTERIAL TONE (PAT) SIGNAL OVERVIEW IN SLEEP MEDICINE .

A.1. CONCEPTUAL BASIS FOR THE CLINICAL APPLICATION The basic concept underlying the various clinical applications of the PAT technology lies in its ability to quantitatively detect and identify a broad spectrum of variations in the vasomotor expression of autonomic activity. The activity of the autonomic nervous system is an integral and essential part of the body’s ability to preserve the basic homeostatic balance necessary for health and basic existence. In general, PAT technology has been used in assessing various clinical conditions related to either spontaneous, endogenously generated sympathetic activation, or the presence of patterns of PAT changes characteristic of sympathetic activation in the face of specific challenges. PAT technology is a measurement method that consists of recording the pulsatile volume changes of the arteries of peripheral vascular beds, principally those of the distal phalanx of the finger which are major sites of sympathetic nervous system mediated vasoconstrictor activity. The PAT signal correlates with and is a surrogate of the activity of the sympathetic branch of the autonomic nervous system. Peripheral arterial tone measurements can be used to track changes in the autonomic nervous system non-invasively, continuously, and accurately.

A.1.1. Clinical Applications The PAT method has been investigated in a number of clinical situations in which autonomic nervous system function plays a major role. In sleep medicine, it is used for detecting sleep-disordered breathing conditions including obstructive sleep apnea and hypopnea, spontaneous arousals and for the detection of REM stage sleep. It is also an effective detector of Cheyene-Stokes breathing which occurs in Congestive Heart Failure (CHF) where it is associated with a poor prognosis.

A.1.2. Rationale of PAT signal as a non-invasive ph ysiological marker PAT measurement takes advantage of the fact that the finger is an extremely convenient site for non-invasive physiological measurement, and that the vascular network of the distal phalanges of the fingers provides a physiologically unique measurement site. The purpose of this discussion is to provide a brief overview of the:

• physiological rationale underlying PAT technology, • physiological significance of the finger as a measurement site, and • manner in which PAT technology has been applied in the diagnosis of certain specific

sleep related physiological and patho-physiological states.


A.1.3. Essential overview of the PAT signal PAT technology is a novel method of plethysmographic measurement (the measurement of volume changes of an organ or some body part) that was specifically tailored to measure the PAT signal by eliminating deficiencies of traditional plethysmographic methods. The essential objective of PAT technology is to measure the ongoing time-course of pulsatile arterial volume. As will be shown, the time-course of finger pulsatile arterial volume directly reflects the peripheral arterial vasomotor state of the finger and is a consequence of the activity of the sympathetic branch of the autonomic nervous system. Vascular smooth muscle contraction is an active process, and in the finger reduced arterial pulsatile amplitude represents increased sympathetic activity. Autonomically mediated vascular tone regulation is an integral and essential part of the body’s ability to preserve the basic homeostatic balance necessary for health and basic existence. Specific patterns of acute, phasic changes in finger arterial vasomotor tone, as well as longer term tonic changes, have been found to accurately mark certain physiological and patho-physiological states. These patterns will be considered at considerable length in the accompanying ATLAS. Brief discussions of some exemplary cases are presented in this introduction to illustrate some of the essential concepts. The vascular network is comprised of basically two separate systems; a high pressure arterial system and a thin walled low pressure venous system. The venous system is characterized by an extremely high compliance relative to the arterial system. That is, the walls of the veins are much more easily stretched so that at a given pressure of the blood within them, the veins are capable of accommodating over ten times the volume of blood than the arteries. In practice, this means that attempts to measure arterial volume changes can be overwhelmingly obscured by massive volume changes in the venous system, unless steps are taken to avoid this occurrence. As mentioned, the venous system is an innately low pressure system, however due to the effect of gravity, when some part of the body is situated below heart level a hydrostatic pressure gradient is automatically generated. Even slight hydrostatic gradients in the venous system can lead to massive venous distention also known as venous blood pooling. In a highly controlled laboratory situation, this can be avoided by ensuring that the specific measurement site is kept above heart level to avoid passive hydrostatic pooling. Under normal circumstances, venous distention due to hydrostatic influences is inevitable. Apart from obscuring arterial volume changes due to the sheer bulk of the venous distention, venous pooling also invokes a reflex constrictory response in the arteries supplying the veins, thus imposing an additional physiological change that can obscure the desired arterial vasomotor response under investigation. The PAT measurement system was developed with the express purpose of creating a measurement environment devoid of the confounding influences of venous blood pooling effects, and devoid of secondarily induced reflex mediated arterial vascular changes. A detailed explanation of the manner in which this is achieved is provided in part C. Having created an appropriate measurement environment for the measurement of arterial volume changes, the pulsatile arterial amplitude measurements are achieved using optical density


measurement of the part of the finger being studied. This signal provides functionally similar information to direct volumetric measurements as will be shown in part C.

A.1.4. The finger tip as a measurement site The vascular bed of the distal end of the finger is an ideal measurement site primarily because of its high vascularity and dense innervation by essentially pure alpha-adrenergic fibers. Although local factors can affect finger blood flow, the finger vasculature is greatly influenced by systemic autonomic activity, and because of the specificity of its innervation, it can serve as a marker of generalized sympathetic activation. The peripheral vascular beds located at the distal parts of the limbs are major sites of sympathetic vasoconstrictor activity, and hence play an important role in circulatory regulation (1-3). This is particularly true of the soles of the feet, the planar surfaces of the toes, and the planar surfaces of the hands and fingers, where there is a high density of arteriovenous anastomoses, and a correspondingly high level of alpha adrenergic sympathetic innervation to the smooth muscles of the arterial bed (4). The wide range of sympathetic nervous activity governing finger vascular beds can be appreciated when one considers that a one-hundred-fold range of steady-state finger blood flow rates (FBFR), is considered to be within physiological limits. FBFR values ranging from 1 ccm/100 ccm tissue/min to 100 ccm/100 ccm tissue /min. have been reported (1). Since a low blood flow rate of 1 ccm/100 ccm tissue/min is still compatible with tissue viability, and blood flow increases with ambient temperature, the enormous potential excess steady-state flow has generally been believed to be associated with a heat-dissipating role in body thermoregulation (5,6). Several factors have been shown to affect tonic levels of finger blood flow. These include local finger temperature changes, heating or cooling of the torso or other large body masses, hypovolemia, protracted mental stress and phasic vasoconstriction in response to being startled (1-6). An interesting cause of transiently reduced finger blood flow is the so called “inspiratory gasp reflex” which involves the taking of a maximal inspiratory breath followed by rapid expiration, which results in a substantial and rapid decline in blood flow that may persist long after normal breathing has resumed (7). The inspiratory gasp reflex is elicited by an unusual forced breathing maneuver which usually needs to be deliberately performed. The mechanism of the peripheral vascular response to such a deep breath has not been elucidated; however, it is thought that pleural stretch receptors may provide the afferent input (7). An important aspect of the innervation of the finger and palmar vascular beds is that their innervation is essentially mediated purely by α-adrenergic receptors. This was clearly demonstrated by Grote et al (8), who demonstrated a dose related response curves of finger arterial pulse amplitude (PAT signal), in response to the α-adrenergic agonist norepinephrine, (Figure 1A), but a near total lack of response to the β -adrenergic agonist isoproterenol, (Figure 1B). In contrast, in the forearm vascular bed which is known to be innervated by both α and β adrenergic receptors, blood flow was appropriately affected by both agents. These dose response curves are shown in Figure 1.


Figure 1: Dose response curves of finger/forearm:-(α and β adrenergic agonists)

Dose response curves of finger arterial pulse amplitude (PAT signal), - (closed squares) and forearm blood flow (open circles) for the α-adrenergic agonist norepinephrine (A), and the β -adrenergic agonist is oproterenol (B). Both vascular beds exhibit α-adrenergic mediated vasoconstriction, but only the fore-arm exhibits β –adrenergic mediated vasodilation. This shows that autonomic vasomotor control of the finger vascular bed is mediated purely by α-adrenergic receptors. (Courtesy of DR L. Grote and Prof J Hedner et al (8)).


A.2. PAT APPLICATION IN SLEEP MEDICINE Clinical Applications of Measuring Peripheral Arterial Tone Using PAT Technology - Some essential studies using PAT have generated a considerable body of data regarding the autonomic expression of physiological and patho-physiological states during sleep. The following provides a brief description of several key aspects of PAT application in sleep medicine.

A.2.1. Detection of sleep-disordered breathing Measuring the PAT signal has been shown to be a highly effective way to detect breathing disorders during sleep based on the circulatory responses associated with such disordered breathing. It is known that apneas terminate in brief arousals, which are associated with tachycardia and elevated blood pressure indicative of sympathetic activation (9, 10). Morgan, et al., showed that auditorally induced arousal from non-rapid-eye-movement (NREM) sleep resulted in bursts of sympathetic nervous system activity associated with increased systolic and diastolic blood pressure, increased heart rate and decreased cardiac output. Auditory stimuli that failed to induce EEG frequency changes or to alter muscle-nerve sympathetic activity were nevertheless associated with hemodynamic changes consistent with increased peripheral resistance and transient tachycardia (9). Pitson and Stradling evaluated the relationships between indices of sleep fragmentation (EEG arousals, apnea/hypopnea index (AHI), and SaO2 drops) and autonomic markers of arousal (heart rate change and the pulse transition time, an analogue of blood pressure). They found that the indirect blood pressure index correlated better to the rate of apneic events during sleep (AHI-which is an index calculated by the total number of disordered breathing events divided by hours of sleep) (r=0.65), than did heart rate changes (r= 0.51) (10). Although estimates of the prevalence of sleep-related breathing disorders such as obstructive sleep apnea syndrome (OSAS) vary considerably, it is clear that they are very widespread (11,12). OSAS is well recognized as a major cause of morbidity and excess mortality. The negative health effects of OSAS include daytime sleepiness, depression, sexual dysfunction, and a general lack of mental acuity. The disorder is strongly associated with hypertension and cardiovascular morbidity and reduced longevity, and is acknowledged to be a contributing factor in automotive and industrial accidents (13-15). OSAS is also strongly associated with arrhythmias (16) and endothelial dysfunction (17). In addition to OSAS, which involves frank cessations in breathing in sleep, milder variants such as hypopnea and upper airway resistance syndrome (UARS) have been more recently described (18). Apneas and hypopneas do not occur frequently in UARS, which is much more difficult to diagnose than OSAS, due to the condition’s more subtle symptomatology (18). However, the condition results in frequent arousals and sleep fragmentation and also could be responsible for cardiac sequelae similar to those associated with OSAS, perhaps due to high levels of airways resistance (18). Upper airway (UAW) patency during inspiration depends largely on the interaction between the UAW’s anatomical and mechanical factors on the one hand, and the forces exerted by the dilating muscles that support its walls on the other (19-21). The presence and severity of OSAS has traditionally been determined using a combination of standard polysomnographic measurements and measurements of the respiratory aspects of the disorder, which include non-


invasively monitoring the airflow at nose and mouth and the respiratory movements of the thorax and abdomen. Apart from the disadvantage of being limited to the sleep laboratory, this approach is likely to underestimate hypopneas – and particularly UARS – where respiratory parameters are not sufficiently sensitive (22). The evaluation of OSAS by monitoring blood oxygen saturation using pulse oximetry is likely to have low sensitivity, since minor variations in SaO2 accompanying hypopneas and UARS may be missed (23). In several clinical studies, algorithmically based automatic evaluations of PAT technology in combination with pulse rate (24, 40, 41, 48), and with pulse-rate, oxygen saturation and actigraphic sleep/wake determination, (25-28, 38, 39, 42-46, 49, 50, 52), were shown to provide very high levels of agreement when validated against conventional laboratory based polysomnography which is considered the “gold standard” for quantifying sleep disordered breathing. The essential features of PAT amplitude and pulse-rate time-course during a typical apneic episode is shown in Figure 2.

Figure 2: Three-minute trace of PAT signal during repeated apneic episodes

Note heart rate (second trace) increases accompanying each depression of the PAT signal. Respiration (trace 6) shows periods of absence of breathing followed by increased ventilation (24).

A.2.2. Detection of REM sleep Sleep staging, in particular the determination of REM (Rapid Eye Movement) stage sleep, is a vital tool for diagnosing sleep disorders and numerous other conditions. During REM sleep, altered control of breathing occurs with greatly reduced chemo-sensitivity resulting in highly irregular breathing patterns and the greatest declines in blood oxygen saturation.


Changes in REM latency have been reported in a plethora of effective illnesses including endogenous depression, schizophrenia, anxiety disorders, obsessive-compulsive disorders, eating disorders as well as in narcolepsy, alcoholism, Alzheimer's disease and impotence. REM latency is important not only in the diagnosis of these conditions but also in therapy and follow up since it is a sensitive indicator of the patient's condition. A robust association between REM stage sleep and a pattern of protracted attenuation of the PAT signal of a substantial magnitude compared to the prior non REM period has been found (29). It is believed that the visible PAT amplitude attenuation is not triggered by the REM sleep itself, but rather appears to be related to an ongoing cycle that is synchronized with the sleep stages cycle in such a way that the nadirs of this cycle coincide with REM sleep (29). Further improvement in the accuracy of REM detection has been achieved by incorporating aspects of PAT amplitude variability and pulse-rate variability into the detection algorithm, resulting in a highly sensitive and specific measure as discussed later in this book (47, 51). The essential feature of sustained PAT amplitude attenuation is shown in Figure 3. The upper trace of Figure 3 shows a marked and sustained attenuation beginning before the period of rapid eye movement (center trace), and with the end of the rapid eye movement phase reverts to former levels (29).

Figure 3: Marked sustained attenuation of the PAT signal during REM

A.2.3. Detection of Cheyne-Stokes breathing in Cong estive Heart Failure patients

An unusual pattern of disordered breathing known as “Cheyne-Stokes” breathing typically occurs in patients with congestive heart failure (CHF). In this breathing pattern, which occurs during sleep, the depth of breathing follows a sinusoidal pattern with periods of very little or even no breathing followed by progressively increasing breathing volumes. This has the shape of an ongoing crescendo - decrescendo pattern. Cheyne Stokes breathing in CHF patients has a known prognostic value (30). During polysomnographic studies which included breathing recordings the PAT signal reliably traced the cyclic breathing pattern (31). The PAT device therefore has the potential to be a useful tool for ambulatory follow up and treatment assessment in CHF patients. The typical time course of PAT modulation during Cheyne-Stokes breathing is shown in Figure 4.

Motion artifact


Figure 4: PAT oscillatory pattern in-phase with breathing/non-breathing respiration pattern


PART B: ILLUSTRATED SCREENS OF WATCH PAT SIGNALS General The purpose of this section is to help the clinician better understand the WatchPAT (signal patterns in a broad spectrum of clinical conditions, and to provide the reader a basic understanding of the automatic algorithm’s rationale. In addition to the automatic results given by the WatchPAT software (zzzPAT), there is a large amount of information that can be derived from direct inspection of the raw data. This section provides the reader with tools to help understand the raw data in the various clinical conditions. In each section there is a brief theoretical background followed by selected examples of the WatchPAT screens. Generally, the usual montage of the WatchPAT includes 6 channels (PAT – actual pulse wave, PAT amplitude envelope, pulse rate, oxygen saturation, actigraphy, and WatchPAT based sleep stages. In some of the following examples, additional channels from simultaneous synchronized polysomnographic (PSG) recordings are presented in order to let the reader compare the novel WatchPAT channels aligned with the standard PSG channels. While the WatchPAT software allows the clinician to review the raw channels in different time bases, the WatchPAT is usually best read at 2-5min screens (these resolutions emphasize respiratory abnormalities).

Glossary of Channel Names: WP Channels: PAT Raw PAT Signals

PAT Amplitude Envelope of PAT Signals

Pulse Rate Rate derived from PAT Signals

SaO2 Arterial Blood Oxygen Saturation

Actigraph Actigraphy (Movement Detection)

WatchPAT Stages Sleep States (Wake, REM, NREM)

PSG Channels: Stages Sleep Stages

O1A2, O2A1 EEG Channels

ROC/LOC Right/Left Electro Occulography

NAF Nasal Air Flow (Pressure Cannula)

FLOW Nasal Air Flow (Thermistor)

ABD Abdominal Respiratory Effort

THO Thoracic Respiratory Effort

RESP Respiratory Effort

HEART RATE Heart Rate

LLEG Left Leg Movement


B.1. RECORDINGS OF NORMAL INDIVIDUALS In normal individuals, nocturnal sleep is characterized by cycles of around 1.5 hours each (ultradian rhythm). During these cycles every individual spends some time in Rapid-Eye-Movement (REM) sleep (dream stage) and in non-REM sleep stages. The WatchPAT device identifies the sleep/wake state based on a unique algorithm of the actigraphic data, and distinguishes between REM and non-REM states based on the different autonomic function in these stages. Actigraphy monitors accelerations (movements) of the wrist, and utilizing specific software, it can accurately detect sleep/wake phases. Several algorithms have been developed for this purpose, most of which focused on normal individuals and insomniac patients. The algorithm actually used in the WatchPAT device (a part of zzzPAT software) has been specially developed for patients with breathing disorders in sleep, and has been shown to be accurate in populations of normal individuals, insomniacs and in sleep apnea patients. As for the sleep pattern determination, the WatchPAT algorithm is primarily based on the different autonomic profiles in REM and non-REM sleep stages. Generally, there is slight decrement in sympathetic activity with the transition from wakefulness to sleep. This may be further diminished with the transition to tonic REM sleep, but may be substantially increased during phasic REM sleep. In contrast, it seems that the parasympathetic activity increases with the transition from wake to sleep, and further increases or persists unchanged during REM sleep. These changes of the autonomic activity during sleep result in a more stable digital pulse volume during normal non-REM sleep stages, but irregular and low (vasoconstricted) pulse wave during REM sleep (see later). In addition, usually the falling asleep process is associated with a slowing of the heart rate, which becomes somewhat faster and irregular during REM sleep. The following are some examples of these normal sleep states as recorded by the WatchPAT.


B.1.1. Wakefulness ( 3-minute screen) These are examples of 3 minute recordings during wakefulness. Generally, recording during wakefulness vary from very stable signals during quiet rest to very inconsistent signals during “active” wakefulness. Both PAT amplitude and pulse rate are substantially affected by the respiratory pattern, and maneuvers such as the Valsalva and the Muller maneuvers as well as sighing, yawning, prolonged breath holding and movements may result in an erratic signal. In Figure 5, the second quarter of the screen demonstrates relatively restful wakefulness with no actigraphic movements and relatively stable pulse wave amplitude (PWA) and pulse rate. Then the subject moves (as can be seen in the actigraphic channel), which results in changes in the PWA and pulse rate. In the 6th channel (shown at the bottom), it can be seen that these epochs are scored as “wake” by the zzzPAT automatic algorithm.

Figure 5: Wakefulness (3-minute screen)

Figure 6 also shows 3 minutes of wakefulness, simultaneously recorded by the WatchPAT (upper 6 channels) and standard PSG (lower 4 channels: EEG=electroencephalography, EOG=electrooculography, NAF=nasal airflow, LEG=leg movements). This subject is active, moves intensively, and the PAT amplitude and pulse rate are unstable.


Figure 6: Wakefulness (3-minute screen)


B.1.2. Non-REM sleep (30-second screen) Figure 7 is a 30-second trace demonstrating stable non-REM sleep of a normal healthy subject. The pulse wave signal is regular. The upward deflection of the signal represents the systolic upstroke and the angle change in the upper third of the downward deflection (dicrotic notch or incisura) represents the closure of the aortic valve. Both the amplitude and the pulse rate are stable, and there are no oxygen saturation changes or movements.

Figure 7: Non-REM sleep (30-second screen)


This is further exemplified in Figure 8 that shows a similar record (30 seconds screen) with simultaneous PSG recordings. The EEG channel indicates that this is a stage 2 sleep epoch, and again, the pulse wave is regular and stable. The automatic WatchPAT scoring system has indeed scored this epoch as sleep, as can be seen in the WatchPAT Stages channel.

Figure 8: Non-REM sleep (30-second screen)


B.1.3. Non-REM sleep (1 minute screen) Figure 9 is another example of normal healthy subject recording, this time a one minute page during stable non-REM sleep. As can be seen, the records are all stable with some minimal variations which may relate to Meyer waves (see below).

Figure 9: non-REM sleep (1 minute screen)


In Figure 10, which shows again stable stage 2 sleep in a one-minute page with simultaneous PSG recordings, the vasomotor variations are slightly more prominent. Note the stable and rhythmic respiration, and the lack of leg movements.

Figure 10: non-REM sleep (1 minute screen)


B.1.4. Non-REM sleep (2-minute screen) Figure 11 shows 2 minutes of stable sleep, with no abnormal events. The pulse wave amplitude, the pulse rate and the oxygen saturation are all stable. There are no movements in the actigraphic channel.

Figure 11: Non-REM sleep (2-minute screen)

Figure 12 shows a similar record with simultaneous PSG channels. Note some minor rhythmic changes of the pulse wave amplitude, which represent the rhythmic blood pressure and vasomotor variations known as Traube-Hering or Mayer waves. These waves represent normal mild vasoconstrictions usually at a rate of around 4-6 per minute. They differ substantially from respiratory disturbances or arousals by their rhythmic nature, the lack of oxygen desaturations and the stable pulse rate (although it may show some mild changes too). The amplitude span during these vasomotor variations is usually mild to moderate. These waves are not always seen, but when they do appear one should recognize them and not confuse them with abnormal events during sleep. Note that the vasomotor changes are not associated with substantial increase in pulse rate, and the PSG channels show no abnormal respiratory or movement events.


B.1.5. Non-REM sleep (3-minute screen) The following 3 figures represent normal and stable sleep. The PAT signal and oxygen saturation are stable and there are no movements. Similar characteristics in a record with simultaneous PSG recordings are shown in Figure 14. When spontaneous vasomotor changes exist, they may be best seen using screens of 1-3 minute, as demonstrated in this example. Again, note that these variations in pulse wave amplitude are not associated with substantial increases in heart rate. These changes may in some cases be very prominent as demonstrated in Figure 15. However, again, the lack of associated increase in heart rate, movement and oxygen desaturation distinguishes between these waves and respiratory events or arousals. In the example shown there are no respiratory cessations, leg movements, or arousals from sleep.



B.1.6. Non-REM sleep (5-minute screen) Figure 16 and Figure 17 are 5-minute screens of a normal subject’s non-REM sleep. In this condensed screen it is hard to see the 4-6/min rhythmic variations. However, it shows that these spontaneous variations may vary in their magnitude, being prominent on some occasions. The stable pulse rate and the lack of movements or oxygen saturation changes indicate that these are not pathological events, as confirmed in Figure 17 with simultaneous PSG channels. There are no arousals, sleep disordered breathing or leg movements.



Figure 17: non-REM sleep (5-minute screen)


B.1.7. Detection of REM sleep In contrast to the non REM sleep stages that are characterized by parasympathetic dominance, REM sleep is associated with intense sympathetic activation. This is manifested by an increase in heart rate and respiratory rate, as well as in their variability. In addition, peripheral vasoconstriction and increased systemic blood pressure occur. Sleep disordered breathing is frequently worse during this stage of sleep, probably secondary to the decreased sensitivity of the respiratory control mechanisms to hypercapnia and hypoxia. Thus, detecting REM sleep has an important clinical role. During in-lab PSG, REM sleep is detected by low amplitude mixed frequency fast EEG activity, rapid eye movements, and the absence of tonic EMG activity. REM sleep can be detected by the WatchPAT, based primarily on the steady prolonged sympathetic activation and the unique autonomic instability, manifested by PAT amplitude and pulse rate fluctuations. While the transition from wake to non-REM sleep is characterized by decreased sympathetic activation and increased parasympathetic activation, the changes in REM sleep are more complex. During REM sleep two different states can be recognized: tonic REM and phasic REM. During tonic REM sleep, generally, parasympathic activation increases, while during phasic REM the sympathetic activation is dominant. Moreover, the autonomic control is different amongst the various organs. The net effect in the digital arteries is increased alpha sympathetic activation. This partially explains why the most characteristic cardiovascular feature of REM sleep is the high pulse rate variability, and peripheral vasoconstriction. The following figures exemplify these points.


B.1.8. REM sleep (3-minute screen) Figure 18 exemplifies normal REM sleep. Both the pulse wave amplitude (PWA) and the pulse rate are highly variable, but not synchronously so. The actigraphic channel shows no movements, and there are no oxygen desaturations. The example shown is derived from the last REM episode toward the morning, as can be seen in the first (upper) channel which depicts the whole-night PAT signal. The gray zone indicates the location of this screen on the scale of the whole-night recording. The PWA and pulse rate channels demonstrate changes from relatively stable signal (tonic REM) to a highly variable one (phasic REM), and the oxygen saturation and movement (actigraphic) channels show no desaturations or movements.

Figure 18: REM sleep (3-minute screen)


The REM-related digital vasoconstriction, with variable pulse rate is also shown with simultaneous PSG recordings in Figure 19, which shows that respiration is also unstable. These features are further exemplified in the following slides.

Figure 19: REM sleep (3-minute screen)


B.1.9. REM sleep (10 minute screen) Figure 20 is an example of 10 minutes of REM sleep. The low baseline amplitude with high pulse rate and PAT amplitude variability together with absence of movements as indicated by the actigraph, is characteristic of REM sleep. There are very mild oxygen saturation changes. In this example, scoring of REM onset was delayed by 2 minutes in the PSG scoring compared to the WatchPAT.

Figure 20: REM sleep (10 minute screen)


B.1.10. REM sleep (50-minute screen illustrating RE M onset and offset) Figure 21 is a 50-minute screen showing the transition from NREM to REM sleep and back to NREM sleep. The REM period is characterized by a lower and unstable PAT signal. The REM onset is often accompanied by some movements that are seen on the actigraphic channel, probably representing changes in body position that commonly occur in sleep stage changes. These characteristics are further demonstrated in Figure 22, with simultaneous WatchPAT and PSG recordings.

Figure 21: REM sleep (50-minute screen illustrating REM onset and offset)


Figure 22: REM sleep (50-minute screen illustrating REM onset and offset)


B.1.11. REM sleep (2-hour screen) Figure 23 is a similar example of a larger time scale (2 hours). There is a prominent decrement of the PAT amplitude during REM sleep (between the 2 non-REM sleep segments), with substantial increases in the variability in the PAT amplitude and pulse rate. Note that there is a short awakening during the REM sleep period.

Figure 23: REM sleep (2 hours screen)


B.2. BREATHING DISORDERS DURING SLEEP It is common to group sleep disorders into one of three general categories: excessive daytime sleepiness (Hypersomnia), inability to initiate or maintain sleep (Insomnia), and undesired events during sleep (Parasomnia). Of the hypersomnolence group, the most common disorder is the sleep apnea syndrome (prevalence of 2-4%). It is defined as frequent cessations of breathing during sleep, which can be partial (decreased tidal volume, hypopnea) or complete (apnea). Three types of apneas can be defined based on the pathophysiology: obstruction of the upper airway (obstructive apnea), loss of ventilatory effort (central apnea), or a combination of the two (mixed apnea). In all three types, whether the apnea is complete or partial, the termination of the event is associated with autonomic arousal from sleep and sympathetic activation, which results in digital vasoconstriction and increase in heart rate. These features are easily detected by the WatchPAT. There are several reports indicating that the WatchPAT is accurate in detecting sleep disordered breathing. Studies on several hundred patients, monitored simultaneously by standard polysomnography (PSG) and WatchPAT demonstrated high accuracy in the diagnosis of OSA. The sensitivity and specificity ranged between 75-95% and the area under the ROC curve between 0.80-0.85. The correlation between the RDI measured by PSG and the automatically calculated PRDI (PAT RDI) of the WatchPAT was approximately 0.9 in most studies. The following figures are examples of the raw WatchPAT recordings of sleep apnea patients.


B.2.1. OSA, WatchPAT + PSG, hypopneas Figure 24 is a classic example of WatchPAT recording in a patient with obstructive sleep apnea. A four minute screen is shown, with the 6 upper channels constituting the standard WatchPAT montage (PAT, PAT amplitude, pulse rate, Oxygen saturation, actigraphy and WatchPAT automatic staging), and the rest are channels derived from the simultaneously recorded PSG (O2-A1 EEG, NAF=nasal airflow assessed by pressure cannula, ABD=respiratory effort measured by an abdominal belt, LLEG=left anterior tibialis EMG). The markers of the arousal and respiratory event are automatically generated by the zzzPAT software. With the termination of each hypopnea (at the re-breathing phase) there is a sharp attenuation of the PAT signal accompanied by an increase in pulse rate and sometimes a movement detected by the actigraph. The EEG demonstrates at these times arousals (although difficult to see at the resolution presented). The oxygen saturation recoveries are delayed by several seconds, probably due to the time-lag between the mechanical re-breathing and the true level of oxygen saturation in the blood detected at the digits. In this example termination of hypopneas is associated with leg movements. Figure 25 the patient demonstrates complete obstructive apneas rather than hypopneas, and there are no leg movements at the termination of sleep disordered breathing events. Note that by looking only at the oxymetry channel some of the events may be missed (arrows). The oxygen saturation may or may not decrease during a sleep disordered breathing event (depending on the nature and length of the event, as well as on other patient factors), as further demonstrated in Figure 27. In the second half of this 5-minute screen the sleep disordered breathing events are associated with substantially less oxygen desaturations. In Figure 26 only the WatchPAT channels are shown (a 5-minute screen). Note the dramatic mirror-like reciprocal pattern of the PAT amplitude and pulse rate channels. Classical sleep disordered breathing events with associated autonomic arousals result in simultaneous sharp attenuation of the PWA and increase in pulse rate. In the second half of this 5-minute screen, the sleep disordered breathing events are associated with substantially less oxygen desaturations.


Figure 24: OSA, WatchPAT + PSG, hypopneas



B.2.2. OSA, WatchPAT + PSG, hypopneas and UARS Figure 28 emphasizes the high sensitivity of the PAT signal in detecting hypopneas (and upper airway resistance syndrome, see below), even if the only PSG evidence for sleep disordered breathing is in the nasal pressure channel. Note that if looking solely at the thoracic movement channel, respiratory abnormalities can hardly be suspected. However, in the more sensitive NAF channel hypopneas can clearly be noted. These events are accurately detected by the PAT channel and the automatic scoring algorithm.

Figure 28: OSA, WatchPAT + PSG, hypopneas and UARS


B.2.3. OSA, WatchPAT + PSG, hypopneas and UARS Figure 29 exhibits a combined case of hypopneas and increased upper airway resistance syndrome. This is a 5-minute screen demonstrating some hypopneas in the beginning and at the end of the screen, with flattening (and clipping) of the nasal pressure signal in the middle (characteristic of UARS). As stated, regardless of the origin of the sleep disordered breathing event, the hyperpneic phase at the termination of the event is marked as a respiratory event by the automatic zzzPAT algorithm.

Figure 29: OSA, WatchPAT + PSG, hypopneas and UARS


B.2.4. Upper Airway Resistance Syndrome (UARS) In some cases frank apneas or hypopneas are not noted, yet the patient complains of snoring and daytime somnolence. This combination is suggestive of the increased upper airway resistance syndrome. In previous studies performed with esophageal balloons, it has been shown in this syndrome that although clear respiratory disturbances could not be observed with standard PSG, there was evidence for partial upper airway collapse and increased resistance, manifested by gradually increased respiratory effort (negative esophageal pressure), which was ultimately terminated by an arousal. Later studies demonstrated that this syndrome may be suspected based on nasal pressure recordings, since even in the absence of frank apneas or hypopneas in this syndrome, the increased resistance may be seen as flow limitation (flattening of the nasal pressure signal). Some examples of the raw PAT data in patients with the increased upper airway resistance syndrome are shown in the following figures. UARS, WatchPAT + PSG: Figures 30 through 33 are classic examples of UARS (4 min). Apneas or hypopneas are absent, but there is a clear flattening of the nasal pressure signal, terminated by an arousal from sleep accompanied by some breaths with a very large tidal volume. When arousal with high tidal volume breaths occurs, the WatchPAT detects a respiratory event due to decrease in PAT amplitude with simultaneous increased pulse rate. Note that during the flow limitation phase there are several PAT attenuations with a somewhat unstable PAT signal, however these are not marked as respiratory events due to the absence of simultaneous tachycardia. In Figure 32 the actigraphic channel demonstrates increase in movement intensity during flow limitation, which probably represents the increase in respiratory effort against increased resistance, and ultimately results in arousal. This phenomenon is commonly seen in WatchPAT recordings of patients with UARS. Also, in the two examples shown there is no oxygen desaturation during the flow limitation period, but with the arousal and hyperpnea phase, the oxygen saturation rises above the previous base line level. This is quite characteristic, as also demonstrated in Figure 32 and Figure 33.


Figure 30: UARS, WatchPAT + PSG

Figure 31: UARS, WatchPAT + PSG


Figure 32 exhibits only the WatchPAT channels. This is a record from a patient with mild UARS, for whom the signal is stable until an arousal occurs. When the signal is very stable with a gradual increase in movement intensity (actigraphic channel) followed by a clear respiratory event (PAT attenuation and increase in pulse rate) and an increase in oxygen saturation, UARS should be suspected.

Figure 32: UARS, WatchPAT only


Figure 33 presents a 5-minute screen of a WatchPAT recording (without simultaneous PSG). It demonstrates that in some cases it may be hard to distinguish between frank apneas/hypopneas and UARS, although it is arguable whether making such a distinction is of clinical importance. The very stable signal and oxygen saturation between events and substantial increase above baseline values following the events, does however suggest that this is a case of UARS.

Figure 33: UARS, WatchPAT only


B.2.5. Central Sleep Apnea (CSA) While obstructive sleep apnea is the most prevalent form of sleep apnea syndrome (over 90% of apnea cases), in some individuals central apneas are predominant, and if more than 80% of the events are central, central sleep apnea (CSA) is diagnosed. There are 3 major types of CSA: idiopathic, central alveolar hypoventilation syndrome (CAHS), and Cheyne-Stokes respiration (CSR). Briefly, in the idiopathic type usually complete cessations of breathing are seen with no respiratory effort, in CAHS hypopneas predominate (with awake hypoxemia and hypercapnia that are worsened during sleep), and in CSR there is a unique breathing pattern characterized by crescendo-decrescendo pattern of the tidal volume, frequently followed by complete central apneas. Although at present the body of PAT recordings in these types of patients is limited, there are some data suggesting that WatchPAT may be able to detect these events. The following figures demonstrate such examples.

B.2.6. CSA, WatchPAT + PSG Figure 34 and Figure 35 are classic examples of the raw data showing detection of central apneas by the WatchPAT. As can be seen in these examples, the absence of flow is not associated with respiratory effort or rib-cage volume changes, indicating apneas of the central type. Yet, there are marked attenuations of the PAT and increases in pulse rate with the re-breathing (hyperpnea) phase, and these events are detected as respiratory events. Note that the oxygen desaturations are relatively mild which is characteristic of CSA. Also, the screens demonstrate that the PAT amplitude attenuation and increased pulse rate occur with the onset of re-breathing (termination of apnea) which is also typical in this type of central apnea as opposed to CSR as shown later in this section.

Figure 34: CSA, WatchPAT + PSG


Figure 35: CSA, WatchPAT + PSG


B.2.7. CSR, WatchPAT + PSG These following two examples are derived from WatchPAT recordings of patients with congestive heart failure and CSR. Note that the respiratory pattern consists of a crescendo-decrescendo phases of the tidal volume, followed by complete central apneas in Figure 36, or without clear complete cessation of breathing in Figure 37. Both cases should be diagnosed as CSR. In both cases the arousal (associated with attenuation of the PAT amplitude and increase in pulse rate) occurs at the peak of the hyperpnea phase, rather than at the termination of apnea. Note that there is a substantial delay between the breathing phase and the oxygen saturation incline, which is typical of congestive heart failure (due to prolonged circulation time). In fact, looking at the signals it appears that at the time of peak hyperpnea the oxygen saturation reaches its nadir (though in general such lags may simply represent the physiological delay due to equilibration of blood oxygen partial pressure following the augmented breathing period).

Figure 36: CSR, WatchPAT + PSG


Figure 37: CSR, WatchPAT + PSG


B.3. OTHER FORMS OF SLEEP FRAGMENTATION Sleep fragmentation in the form of frequent “brief arousals” is a very important factor resulting in poor sleep quality. It has been implicated in daytime impairment of cognitive and psychomotor performance, particularly (but not exclusively) in sleep related breathing disorders. Thus, the number of arousals is a useful marker of sleep quality, which is independent of traditional sleep quality markers such as sleep efficiency and sleep latency. Arousals from sleep are associated with increased sympathetic activation, and are therefore associated with peripheral vasoconstriction. Using a special automatic analysis algorithm, digital vasoconstrictions as measured by PAT, combined with an increase in pulse rate, have been shown to accurately reflect arousals from sleep, and can provide an arousal index (ARI). Since the standard criteria for detecting arousals from sleep are not always clear-cut and are commonly difficult to determine, large inter scorer variability in scoring arousals from sleep has been reported. The ARI therefore provides a reliable and reproducible measure of sleep fragmentation. Moreover, the currently used EEG criteria for defining arousals and sleep fragmentation has failed to predict either subjective or objective sleepiness.

Periodic Limb Movement Disorder of Sleep (PLMD) One of the most common forms of sleep fragmentation is the periodic limb movement disorder of sleep (PLMD). This condition, also known as nocturnal myoclonus or periodic movements in sleep, occurs exclusively during sleep. It usually affects the legs, but occasionally the arms. The movements are periodic, highly stereotypic, and may or may not be associated with arousals from sleep. As frequently it causes sleep fragmentation, the clinical outcome is often hypersomnia or insomnia. In those occasions when these movements do not cause arousals, it should probably be categorized as a parasomnia. The following are some examples of PLMD as recorded by the WatchPAT.


B.3.1. PLMD without arousals, WatchPAT + PSG Figure 38 is an example of periodic limb movements (PLMs) without associated arousals. Note the periodic nature of the four leg movement events in this 2 minute screen, and the lack of signs of arousal in the EEG. These movements are captured by the WatchPAT actigraph, but are not marked as arousals (by the automatic zzzPAT) since the pulse wave amplitude and pulse rate are very stable.

Figure 38: PLMD without arousals, WatchPAT + PSG


B.3.2. PLMD with borderline arousals, WatchPAT + PS G In Figure 39, showing a 3-minute screen of simultaneous WatchPAT and PSG recordings, there are PLMs with no clear signs of cortical arousal in the EEG channel, but the movements are associated with some degree of PAT amplitude attenuation and tachycardia. However, these are sub-threshold changes for defining arousal by the WatchPAT algorithm that has been tuned against standard cortical arousals. Nevertheless, if such a patient does complain of sleep fragmentation and daytime somnolence the clinician may consider these borderline events as arousals.

Figure 39: PLMD with borderline arousals, WatchPAT + PSG


B.3.3. PLMD with arousals, WatchPAT + PSG In Figure 40, the PLMs are associated with arousals from sleep, which are also detected by the WatchPAT. These arousals are not accompanied by respiratory events! Respiration and oxygen saturation are stable, yet there are clear PAT attenuations associated with increased pulse rate indicating arousals from sleep.

Figure 40: PLMD with arousals, WatchPAT + PSG


B.3.4. PLMD and SDB, WatchPAT + PSG Figure 41 demonstrates that in some cases leg movements are seen together with sleep disordered breathing (SDB). In this example, there are 6 leg movement events within the 3-minute screen shown, but only 3 episodes of respiratory disturbances (hypopneas), seen in the airflow (NAF) channel. While the leg movements in this case do not result in arousals, the sleep disordered breathing events do cause arousals which are marked by the zzzPAT algorithm.

Figure 41: PLMD and SDB, WatchPAT + PSG


B.3.5. PLMD and SDB, WatchPAT + PSG Figure 42 is another example of a patient with a combined respiratory and movement disorder. Five movements are noted in this 3-minute screen, but there are only 3 hypopneas, all of which are associated with arousal from sleep (noted both in the EEG channel and marked by the zzzPAT). The first leg movement in the series, shown at 23:52:00, is associated with mild PAT attenuation and marginal increase in pulse rate, which may represent a sub threshold sign of arousal.

Figure 42: PLMD and SDB, WatchPAT + PSG


B.3.6. PLMD and UARS, WatchPAT + PSG These are examples of patients with both PLMD and increased upper airway resistance syndrome. Note that in Figure 43, the leg movements are not associated with arousals while in Figure 44 the leg movements are associated with arousals. In both cases the flow-limited breaths ultimately result in arousals from sleep.

Figure 43: PLMD and UARS, WatchPAT + PSG


Figure 44: PLMD and UARS, WatchPAT + PSG


B.4. DETECTING ARRHYTHMIAS Irregular heart rate has an important role in sleep studies. Patients with sleep-disordered breathing often demonstrate arrhythmias such as VPBs, brady-tachy arrhythmias, and in severe and rare cases, also ventricular tachycardia. No doubt that the gold standard technique for detecting arrhythmias is the standard ECG, which cannot be replaced by pulse wave detection at the level of the digital arteries. The pulse signal does however provide an indication of the mechanical hemodynamic consequences of an arrhythmia, which is not the case for ECG, and PAT might thus be considered to provide complementary information to the ECG. The following screens demonstrate some examples of heart rate abnormalities, which can be detected by the WatchPAT and should be an indication for performing standard ECG evaluation. These findings have practical importance when dealing with apnea patients since such findings usually require both cardiologic consultation and more aggressive treatment of the sleep apnea. In addition, the interpreter of the WatchPAT should be aware that in periods with arrhythmias there may be a discrepancy between the pulse rate and heart rate.


B.4.1. Premature beats, WatchPAT + PSG Figure 45 is an example of a patient with frequent premature contractions. Note that with every premature beat (ECG channel) there is a secondary peak in the PAT channel. Similar examples can be seen in Figure 46, Figure 47 and Figure 48. Following the compensatory period, substantially larger pulse wave amplitude is seen, and this represents a greater stroke volume.

Figure 45: premature beats, WatchPAT + PSG


B.4.2. Bigeminy Figure 49 is an example the PVCs (Premature Ventricular Contraction) are in an “every other” order, a pattern known as bigeminy. In the PAT channel this is expressed as a series of large amplitude and delayed pulses, which should always raise the suspicion of such an arrhythmia.

Figure 49: Bigeminy


B.4.3. Quadrigeminy In other arrhythmic premature beat patterns such as trigeminy or quadrigeminy as seen in this figure, the mechanical outcome shown in the PAT channel is usually a pulse rate of n-1 beats per cluster of arrhythmic beats as recorded by the ECG. Thus, bigeminy is seen as a continuous series of large beats Figure 50 while quadrigeminy (as shown in this example in the ECG) is seen as trigeminy in the PAT channel with secondary peaks. When looking at a larger time scale, this may be more pronounced, as can be seen in Figure 51.

Figure 50: Quadrigeminy


Figure 51: Quadrigeminy


B.4.4. Skipping beats Figure 52 is an example of a patient with missing (skipping) beats, which similarly to PVCs, may result in decreased pulse rate, but unlike PVCs is not associated with increased PWA.

Figure 52: Skipping beats


B.4.5. Paroxysmal Atrial Fibrillation (5 min) The following figures demonstrate a Paroxysmal Atrial Fibrillation (AF) case, where the focus is on the transition point from AF period to Normal Sinus Rhythm (NSR) evident in the right half of the screen. Please note the following: (a) excluded areas (marked by the automatic algorithm) during the AF period and the detected arousal and respiratory events during the NSR period. (b) The differences between the left and the right halves of the screen: irregularity on the ECG channel and PAT raw signal.

Figure 53: Paroxysmal Atrial Fibrillation (5-minute)


B.4.6. Paroxysmal Atrial Fibrillation (1 minute) Figure 54 demonstrates the transition from an AF period to a NSR period. Please note the irregularity on the ECG and the pulse wave.

Figure 54: Paroxysmal Atrial Fibrillation (1 minute )


B.4.7. Paroxysmal Atrial Fibrillation (20 seconds) Figure 55 again demonstrates the transition from an AF period to a NSR period providing a better view of the individual pulses. Note on the right half of the screen the clear P waves on the ECG together with the dicrotic notches on the PAT signal, compared to the irregularities evident on the left side of the screen.

Figure 55: Paroxysmal Atrial Fibrillation (20 seconds)


PART C: PAT MEASUREMENT TECHNOLOGY : KEY PHYSIOLOGICAL , BIOPHYSICAL AND PROBE DESIGN CONSIDERATIONS

PAT technology is a novel digital plethysmographic measurement method that was developed with the express purpose of creating an optimal measurement environment for the recording of pulsatile arterial volume signals in the finger. There are a number of prerequisites for the accurate measurement of such arterial pulse waves. The most important of these are; a), that the signal be devoid of the confounding influences of venous blood volume influence, since the sheer bulk of the venous distention can obscure arterial volume changes, and, b), that the occurrence of measurement induced, reflex mediated arterial vascular changes be avoided. Later in this section, it will be shown why conventional plethysmographic methods are unable to realize these dual objectives, and how the PAT probe was designed to resolve the problem.

C.1.1. PAT probe Design Features Essentially, the PAT probe is an elongated, longitudinally split thimble, completely lined within by a highly compliant elastic membrane surrounded by an outer rigid casing. The internal membrane is functionally tethered to the mid line of the outer shell as illustrated in figure 5. When the space between the membrane and the rigid outer case is pressurized to the desired level the internal membranes converge. Due to its split thimble structure, when pressurized, the PAT probe imparts a two-point clamping effect, which actively clamps itself to the entire surface of the finger, and because the membrane is restrained from outward displacement, no tendency to expel the finger can occur. An important feature of the PAT technology is that the clamping effect increases as the pressure is raised in the PAT probe, in contrast, open ended cuffs applied over the finger tip increasingly tend to expel the finger as pressure is raised. The special significance of this difference will be discussed in relation to alternate plethysmographic methods. The PAT probe is also characterized by having a contiguous pressure compartment which proximally extends the effective length of the applied pressure field and buffers the distal measure site from retrograde vascular pressure waves. The PAT signal can be recorded as an actual change either in pulsatile volume or in the optical density which is related to the relative volume of blood in the finger at any time. In either case, the pressure fields and measurement environments within the probes are the same in all functional respects. Recording optical density changes, however, makes it possible to include a self-contained pressure source as an integral part of the probe itself, substantially simplifying the supporting system and greatly facilitating the ambulatory nature of the device. Self-contained PAT probes have therefore been adopted for measurements in sleep studies.


The major design features of the PAT probe used in sleep studies are illustrated in Figure 56.

Figure 56: Cross-sectional view through the pneumo-optical PAT finger probe.

Note split thimble construction of the entire probe. An optical (photo-plethysmographic) sensor monitors changes in optical density. The applied pressure field proximal to the sensor acts as a buffer region. The probe is distinguished by its ability to generate a self-contained, finger volume independent pressure field, by virtue of the external membrane. In measurement with the PAT and in plethysmographic measurement in general, there is a practical advantage to applying a relatively high degree of pressure within the cuff, (up to diastolic blood pressure level), since this increases the range of motion of the arterial walls. This is due to the curvilinear nature of the arterial compliance curve as illustrated in Figure 57. As shown in panel C of this figure, the greatest amount of arterial wall motion occurs when cuff pressure is close to diastolic blood pressure since this allows arterial transmural pressure at diastole to be near zero (see lower tracing panel B Figure 57).


Figure 57: Arterial compliance curve

A. Time course of pulse wave signal and applied pressure. Note cutting off of the signal at high pressure levels, increasing amplitude of the signal at middle pressure range, and increasing elevation of the signals above the zero baseline as applied pressure falls . B. Systolic (upper) and diastolic (lower) envelopes define the ranges of pulse volume as functions of applied pressure. Note the origin of the diastolic curve at an applied counter pressure of about 95 mmHg. As counter pressure continues to fall, both diastolic and systolic curves continue to rise and the difference between them falls. C. Pulsatile amplitude (systolic-diastolic difference) versus applied pressure. Note that maximal signal amplitude occurs when applied pressure equals diastolic pressure (i.e. diastolic transmural pressure = 0 mmHg). As diastolic transmural pressure increases, the systolic-diastolic volume changes progressively decrease. Figure 58 illustrates how the application of external counter-pressure increases the volume change associated with pulse waves of a given pulse pressure in the process known as vascular wall unloading. When applying pressure in the plethysmograph to increase arterial motion, if there are any tissues distal to the plethysmograph, (as is the case for plethysmographic devices other than PAT), then the externally applied pressure will lead to venous pooling in those tissues. Within


such distal tissues the degree of venous distention will be determined by the applied pressure. Hendriksen et al showed in a series of papers that subjecting the veins to such distending pressure levels is likely to result in reflex arteriolar constriction (32). As pressure is increased, venous pooling and distension will occur resulting in proportionately greater reflex veno-arteriolar vasoconstriction (32). During measurement, all of the tissues distal to the cuff will become engorged with blood at a pressure equal to the cuff pressure.

Figure 58: Arterial Pressure vs. Volume compliance Curve

Figure 58 demonstrates how reducing arterial transmural pressure (i.e. arterial pressure minus external pressure) by applying more external pressure increases the pulse signal (A low external pressure, B high external pressure). This occurs because of the curved pattern of the volume versus pressure curve of the arterial network. It should be noted that the PAT probe is specifically designed to cover the distal end of the finger so that no region of tissue experiences induced or passive venous distention. An example of the acute effect of induced venous pooling is shown in Figure 59. This figure shows the time-course of pulse wave amplitude in two adjacent fingers when a proximal cuff on the upper arm is alternately inflated to a pressure of 40 mmHg and then deflated back to 0 mmHg. The result of inflating the proximal cuff to 40 mmHg is to induce venous distention in the tissues distal to the cuff. The upper trace shows the pulse-wave amplitude recorded from a


finger over which minimal external counter pressure is applied while the lower trace shows the pulse-wave amplitude from a finger over which a pressure field of near diastolic pressure is applied over the entire surface of the two distal phalanges using a PAT probe. In the finger with minimal applied pressure, venous distention will occur; however, when the distal end of the finger is surrounded by the pressure field from the PAT probe (inflated to above 40 mmHg), no venous pooling can occur.

Figure 59: Acute effect of venous blood pooling on arterial pulse amplitude.

Time-course of pulse wave amplitude in adjacent fingers within different pressure fields when a proximal cuff on the upper arm is alternately inflated to a pressure of 40 mmHg and then deflated to 0 mmHg. Inflating the cuff to 40 mmHg induces venous distention in the tissues distal to the cuff. Upper trace – pulse signal from finger within minimal external counter pressure environment Lower trace – pulse signal from a finger within near diastolic pressure field is applied over the entire surface of the two distal phalanges (using a PAT probe). In the absence of the pressure field, periods of induced venous distention are associated with substantial attenuation of the pulse signal, in sharp contrast simultaneous recording from the finger within the pressure field is essentially unaffected by the induced venous distention. It is clear from Figure 59 that in the finger without the pressure field the periods of induced venous distention are associated with substantial attenuation of the pulse-wave amplitude compared to when there is no applied venous distention. In sharp contrast to this, the simultaneous recording from the finger within the PAT pressure field is essentially unaffected by the induced venous distention. The acute effect of this locally induced vasoconstriction is further complicated by a tendency for induced veno-arteriolar vasoconstriction to propagate centripetally over time as reported by Henriksen et al (32).


C.1.2. PAT technology in comparison to conventional plethysmographic methods;

The major advantages of PAT technology are best illustrated by considering certain problems associated with these methods. In the above described experiment, the combination of inflating a proximal cuff to induce venous distention in the tissues distal to that cuff, and measuring the resulting volume changes using a second cuff in which minimal external counter pressure is applied, is in fact functionally equivalent to Venous Occlusion Plethysmography, (VOP), an important conventional plethysmography technique. VOP is primarily used to measure arterial blood flow rather than pulsatile volume changes. The primary use of venous occlusion plethysmography is in obtaining accurate quantitative measures of blood flow mainly useful for research purposes. When the proximal cuff is pressurized to a level somewhere between venous pressure and diastolic blood pressure the blood passing beneath the high-pressure cuff will accumulate in the veins distal to that cuff, and the accumulating volume can be measured within the distal low-pressure element. Blood-flow rate is measured as a function of the rate of change in volume as blood builds up distal to the occlusion cuff. As described above and illustrated in Figure 59, the signal recorded from a site distal to the venous occluding cuff is strongly affected by the degree of venous distention being induced in the measurement region. Segmental plethysmography is another important conventional plethysmography technique in common use. In this method, volume changes are measured in the cuff itself. The method works by applying a pressurized cuff around an essentially cylindrical part of the body, such as a limb or digit, and recording changes in blood volume by recording variations in the pressure within the cuff. The primary clinical use of segmental plethysmography is in determining the degree of potency of large arteries at various sites for evaluating structural obstructive vascular disease. In addition to the direct strong affect on signal amplitude due to venous distention shown in Figure 59, Henriksen et al (32), reported that the acute effect of this locally induced vasoconstriction is further complicated by a tendency for induced veno-arteriolar vasoconstriction to propagate centripetally over time. Thus measurement within a segmental cuff is likely to be adversely affected by this phenomenon as well.

C.1.3. Resolving the disadvantages of VOP and segme ntal plethysmography From the foregoing, it is apparent that the application of external counter pressure to a segment of the finger (or other part of the body), can increase arterial wall motion, yet at the same time it can also induce venous pooling and related vasoconstriction distal to the site of the pressure application. These opposing vasomotor tendencies can therefore lead to a situation of indeterminate and possibly unstable signal amplitude over time. The effects of these conflicting interactions on the compliance characteristics of the measured vascular beds as well as the benefits of preventing distal venous pooling, are summarized in Figure 60.


The open-ended design of plethysmographic devices prior to PAT, means that they can only be applied in a mechanically stable manner if they fall short of the terminal end of the finger. If, for example, a length of a cuff were to be applied beyond the tip of the finger, the portion of the cuff not parallel to the finger would not be in direct contact with the finger. The finger region not in full contact with the cuff would not only be inadequately pressurized, but the cuff would also tend to expel the terminal end of the finger due a net vector force acting against the finger tip.

Figure 60: Opposing effects of vascular unloading and venous pooling

A - External counter pressure can increase arterial wall motion due to a leftward shift along the pressure volume curve. B - External counter pressure can also induce venous pooling related vasoconstriction distal to the site of the pressure application. (see arrows & solid curve), leading indeterminate and possibly unstable signal amplitude over time. C - The effect of preventing distal venous pooling whilst applying significant counter-pressure is to facilitate improved vascular compliance without inducing reflex vasoconstriction resulting in a stable signal with optimal dynamic range. The problem of induced distal venous pooling can be overcome if a uniform pressure field is applied to the entire surface of the distal part of the body part including the distal most tip to counter act the venous distention, as was shown in Figure 58. The combination of adequate counter pressure and the absence of distal venous pooling would facilitate measurement as illustrated in Figure 60C. Such a pressure field does however require a special mechanical design that is physically stable in light of the tendency of cuffs to generate a


net vector force acting against the tip. An illustration of how this is achieved by the split thimble design of the PAT probe is shown in Figure 56.

C.1.4. The PAT technology solution to traditional p lethysmographs’ drawbacks

The above-described induced artifacts associated with prior forms of plethysmography are likely to interfere with the accurate measurement of vasomotor changes actually being studied. The PAT probe's main functional advantages for resolving these problems can be summarized as follows:

C.1.4.1. Full-length, uniform pressure anti venous pooling region Unlike other plethysmographic devices, the PAT probe is capable of completely covering the surface of the distal end of the finger with a uniform pressure field that extends all the way to the terminal end of the finger. The external counter-pressure inhibits venous blood pooling and distension within the measurement site and prevents distal venous pooling from occurring. This prevents the induction of veno-arteriolar reflex vasoconstriction, which can otherwise lead to the development of an indeterminate degree of vasoconstriction. (32). The ability to apply pressure to the tip of the finger is critical for comfortably sustaining the measurement of peripheral arterial tone over lengthy periods. Prior to the development of PAT technology, the collecting cups of finger-mounted venous occlusion plethysmographs could not be inflated beyond the order of about 1 mmHg, without being pushed off the finger.

C.1.4.2. Extended pressure field buffer region A proximal (towards the heart), extension of the pressure field relative to the optical sensor creates an isobaric barrier between the measurement site within the probe and the blood vessels feeding the measurement site. Although the proximal portion of the extended pressure field is not actually used in measuring the pulse signal, it provides two important benefits: a) it extends the effective pressure boundary of the measurement site and, b) it buffers the measurement site from retrograde venous blood perturbations. The benefit of these effects is best demonstrated when measurements are made on a moving subject, where mechanical perturbations of the blood would tend to cause mechanical artifacts in the absence of a buffer region. An added benefit is that the extended pressure field further immobilizes the distal finger joint, helping to eliminate finger bending.

C.1.4.3. Ability to unload arterial wall tension without causing venous pooling. By applying substantial levels of external counter-pressure, the PAT probe is able to unload arterial wall tension, which means that when a pulse wave traverses the probe, the arterial walls may experience increased wall motion between the diastolic and systolic stages of the pulse wave. Increasing the amount of arterial wall motion will increase the size of the arterial volume change and thus increase the size of the PAT signal.

Due to the fact that the entire distal part of the finger is enveloped by the applied pressure field of the PAT probe, no venous pooling or distention occurs.


C.1.5. Overview of the self-contained pneumo-optica l PAT system The desire to facilitate ambulatory measurement using PAT technology led to the development of a self-contained probe and wrist mounted support system (33). This system, together with embedded actigraphy and advanced signal processing algorithms has been validated against conventional, laboratory based, polysomnography as a diagnostic means for evaluating sleep disordered breathing (25-28). It has also been used in a number of related research applications such as the detection of REM stage sleep (29), in the evaluation of the linkage between encephalographic frequency spectral analysis and autonomic responsiveness in relation to brief arousals during sleep (34) and to the effect of exogenously modified upper airway obstruction and arousal on peripheral vascular responsiveness (35).

C.1.6. Technical features of the self-contained PAT probe and support system A major advantage of this type of PAT probe lies in its ability to apply the uniform pressure field in a self-contained manner independently of any external pressure source, while being able to apply an exact level of pressure independent of finger size (33). The ability to apply a predetermined level of pressure which is unaffected by the size of the finger being tested is an inherent property of the probe which is derived from the use of an external elastic membrane which can be configured to generate a fixed level of pressure in accordance with the law of Laplace (33).

C.1.7. Isobaric, volume displacement PAT probe desi gn A unique feature of the self-contained PAT finger probe is its ability to generate its own pressure field at a fixed level of pressure irrespective of the size of the finger (33). The pressure field is created by the insertion of a finger into the probe as depicted in Figure 61A and Figure 61B.

Figure 61: Functional attributes of the self-contained PAT probe.


When the finger is inserted into the probe, air is shifted from the inner compartment of the probe to its outer compartment, causing the pre-tensioned outer membrane to be pushed off the wall of the inner shell and to thus apply pressure to the air within the probe. The elastic properties of the balloon like outer membrane are such that over a wide range of volumes it creates a constant pressure, as shown in the figure above. C. A transmission mode photo-electric plethysmograph situated at opposing lateral sides at about the middle of the distal phalanx is used to measure the optical density changes associated with pulsatile blood volume changes of the finger. The proximal two-thirds of the pressure field buffers the sensing region from extraneous and artifactual signals such as perturbations in the venous system. The optical sensing method provides data that is highly correlated with volumetric changes as can be seen in Figure 62. This demonstrates the suitability of the convenient optical density recording method as a surrogate of direct volumetric measurement.

Figure 62: Functional similarity of optical and volumetric signals

Figure 62A shows the time-course of optical and volumetric signals recorded simultaneously from the same finger. Three reflex mediated episodes of vasoconstriction are shown. Note gross similarity of response patterns.


Figure 62B. Scatter plot of optical versus volumetric signals shown in 11A. Note the very high concordance (R=.97), and high degree of linearity between signals. The WatchPAT probe contains an inner and an outer membrane on either sides of a rigid plastic thimble. Before insertion of the finger, approximately 10 ccm of air is situated between the inner membrane and the plastic thimble. Since the inner membrane is not stretched, the air is at atmospheric pressure. The outer membrane is fitted to the external wall of the plastic thimble, and is slightly stretched from its natural size. When the finger is inserted into the probe, a proportionate amount of air is shifted from the inner compartment of the probe to its outer compartment, causing the pre-tensioned outer membrane to be pushed off the wall of the inner shell and to thus apply pressure to the air within the probe. For simplicity, insertion tabs for aiding in the insertion of the finger, and an external probe cover are not shown in the figure. The pressure volume characteristics of the self contained PAT probe. Note that a fixed level of pressure is applied over a wide range of finger sizes.

C.1.8. Technical features of the wrist mounted supp orting device The above described sensing probe is used in combination with a battery powered wrist/forearm mounted consol unit placed just above the wrist, which in addition to the PAT probe, also integrates pulse oxymetry, (Nonin OEM 2 oximetry module, 8000J sensor, USA), and records oxymetry inputs. This unit provided the power supply, amplifiers, signal filtering, data acquisition and storage functions required for monitoring the PAT signals, pulse oxymetry and data from an actigraph embedded within the forearm unit itself. Pulse rate is derived from the PAT signal. All four signals were recorded at a sampling rate of 100Hz, and stored on to a removable flash disc throughout the sleep study.


PART D: List of References

1. Burton AC. The range and variability of the blood flow in the human fingers and the vasomotor regulation of body temperature. Am J Physiol 1939;127:437-453.

2. Thauer R. Circulatory adjustments to climatic requirements. In: W.F. Hamilton (Ed.) Handbook of Physiology, Circulation, American Physiological Society, Washington DC. pp. 1921-1966, 1963.

3. Doupe J, Newman HW, Wilkins RW. The effect of peripheral vasomotor activity on systolic arterial pressure in the extremities of man. J Physiology 1939; 95:244-257.

4. Molyneux GS. Neuronal control of cutaneous arteriovenous anastomoses. In:"Progress in Microcirculation Research", (Ed. Garlick D), University of New South Wales. pp. 296-315, 1981.

5. Hassan AAK, Rayman G, Tooke JE. Effects of indirect heating on the postural control of skin blood flow in the human foot. Clin Sci 1986;70: 577-580.

6. Russell A, Kappagoda T. Reactive Hyperemia in patients with Reynaud's Phenomenon. J Rheumatology 1988;15: 653-1657.

7. Sharpy-Shafer EP. Effects of respiratory acts on circulation. In WF Hamilton (Ed.) Handbook of Physiology, Circulation, American Physiological Society, Washington DC. Pp. 1875-1886, 1963.

8. Grote LB, Hedner J, Ding Z. Alteration of Digital Pulse Amplitude Reflects Alpha-adrenoceptor Mediated Constriction of the Digital Vascular Bed. SLEEP 2001, Vol. 24 (Suppl.), A79.

9. Morgan BJ, Crabtree DC, Puleo DS, Badr MS, Troiber F, Skatrud JB. Neurocirculatory consequences of abrupt change in sleep stage in humans J Appl Physiol 1996;80:1627-1636.

10. Pitson DJ, Stradling JR. Autonomic markers of arousal during sleep in patients undergoing investigation for obstructive sleep apnea, their relationship to EEG arousals, respiratory events and subjective sleepiness. J. Sleep Res. 1998; 7, 53-59.

11. Lavie P. Incidence of sleep apnea in a presumably healthy working population: a significant relationship with excessive daytime sleepness. Sleep 1983;6: 312-318.

12. Young T, Palta M, Dempsey J, Skatrud J, Weber S, Badr S. The occurrence of sleep disordered breathing among middle-aged adults. N Eng J Med 1993; 328:1230-1235.

13. Lavie P, Peled R, Berger I, Yoff N, Zomer J and Rubin AH. Mortality in sleep apnea patients: A multivariate analysis of risk factors. Sleep 18:149-157, 1995.

14. He J, Kryger MH, Zorick FJ, Conway W and Roth T. Mortality and apnea index in obstructive sleep apnea: Experience in 385 male patients. Chest 1988, 94:9-14.

15. Hoffstein V, Chan C, Slutstky AS. Sleep apnea and systemic hypertension: a causal association- review. Am. J. Med 1991;91:190-196.

16. Roche F, Xuong AN, Court-Fortune I, Costes F, Pichot V, Duverney D, Vergnon JM, Gaspoz JM, Barthelemy JC. Relationship among the severity of sleep apnea syndrome, cardiac arrhythmias, and autonomic imbalance. Pacing Clin Electrophysiol 2003 Mar;26(3):669-77.

17. Imadojemu VA, Gleeson K, Quraishi SA, Kunselman AR, Sinoway LI, Leuenberger UA. Impaired vasodilator responses in obstructive sleep apnea are improved with continuous positive airway pressure therapy. Am J Respir Crit Care Med 2002 Apr 1;165(7):950-3

18. Guilleminault C, Stoohs R, Clark A, Cetel M and Maistros P. A cause of excessive daytime sleepiness. The upper airway resistance syndrome. Chest 1993, 104:781-787.

19. Pack AI. Obstructive Sleep Apnea. – review. Advances in Internal Medicine 1994; 39:517-567. 20. Strohl KP. Upper airway muscles of respiration. Am. Rev. Resp. Dis. 117:39-51, 1981. 21. Remmers JE, Issa FG, Suratt PM. Sleep and respiration. J. Appl. Physiol. 68: 1287-9, 1990.


22. Norman RG, Adhmed MM, Walsleben JA, Rapoport DM. Detection of respiratory events during NPSG: Nasal cannula pressure sensor versus thermistor. Sleep 1997, 20:1175-1184.

23. Levy P, Pepin JL, Deschaux Blanc C, Paramelle B, Brambilla C. Accuracy of oximetry for detection of respiratory disturbances in sleep apnea syndrome. Chest 1996; 109:395-399.

24. Schnall RP, Shlitner A, Sheffy J, Kedar R, Lavie P. Periodic, Profound Peripheral Vasoconstriction – A New Marker of obstructive Sleep Apnea. Sleep 1999, Vol. 22 (7), 939-46.

25. Bar A, Pillar G, Dvir I, Sheffy J, Schnall RP, Lavie P. Evaluation of a portable device based on arterial peripheral tonometry (PAT) for unattended home sleep studies. Chest, 2003 March, 123(3):695-703.

26. Pillar G, Bar A, Bettito M, Schnall R, Dvir I, Sheffy J, Lavie P. An automatic ambulatory device for detection of AASM defined arousals from sleep: the WatchPAT. Sleep Medicine, 2003 4(3):207-212.

27. Pillar G, Bar A, Shlitner A, Schnall RP, Sheffy J, Lavie P. Autonomic Arousal Index (AAI): An Automated Detection based on Peripheral Arterial Tonometry. Sleep 2002, Vol. 25 (5), 541.

28. Penzel T, Brandenburg U, Fricke R, Peter JH. New methods for the non-invasive assessment of sympathetic activity during sleep. Somnologie 2002; 6:69-73.

29. Lavie P, Schnall RP, Sheffy J, Shlitner A. Peripheral Vasoconstriction during REM sleep detected by a novel plethysmographic method. Nature Medicine 2000, Vol. 6(6), 606.

30. Paola A. Lanfranchi, Alberto Brahiroli, Enzo Bosimini, Giorgio Mazzuero, Roberto Colombo, Claudio Donner, Pantaleo Giannuzzi: Prognostic Value of Nocturnal Cheyne-Stokes Respiration in Chronic Heart Failure. Circulation. 1999;99: 1435-40.

31. Freimark D, Adler Y, Sheffy J, Schechter D, Schwammenthal E, Motro M, Lavie P. Oscillations in peripheral arterial tone in CHF patients: A new marker for Cheyne-Stokes breathing. Cardiology 2002, 98, 21-4.

32. Henriksen O, Sejrsen P. Local reflex in microcirculation in human cutaneous tissue. Acta Physiol Scand 1976;98:227-231.

33. Schnall Robert P. United States Patent 6,461,305 Pressure applicator devices particularly useful for non-invasive detection of medical conditions; October 8, 2002 Foreign Application Priority Data Jun 07, 1998

34. Lavie P, Shlitner A, Sheffy J, Schnall RP. Peripheral Arterial Tonometry: A novel and sensitive non-invasive monitor of brief arousals during sleep. IMAJ 2000, Vol.2 (3), 246.

35. O’Donnell CP, Allan L, Atkinson P, Schwartz AR. The effect of upper airway obstruction and arousal on Peripheral Arterial Tonometry in Obstructive Sleep Apnea. Am J Respir Crit Care Med 2002, Vol.166, 965-71

36. Dvir I, Adler Y, Freimark D, Lavie P. Evidence for fractal correlation properties in the variations of peripheral arterial tone during REM sleep. American Journal of Physiology 2002; 283(1):H434-H439.

37. Pillar G, Bar A, Shlitner A, Schnall RP, Sheffy J, Lavie P. Autonomic Arousal Index (AAI): An Automated Detection based on Peripheral Arterial Tonometry. SLEEP 2002; 25(5):543-549.

38. Ayas N. TA, Pittman S, MacDonald M, White D. Assessment of a Wrist-worn Device in the Detection of Obstructive Sleep Apnea. Sleep Medicine 2003; 4(5):435-442.

39. Margel D, White D, Pillar G. long-Term intermittent exposure to high ambient CO2 causes respiratory disturbances during sleep in submariners. Chest 2003; 124(5):1716-1723.

40. Zou D, Grote L, Eder ND, Peker Y, Hedner J. Obstructive Apneic Events Induce Alpha-receptor Mediated Digital Vasoconstriction. SLEEP 2004; 27(3):485-489.

41. Tauman R, O’Brien ML, Mast TB, Holbrook CH, Gozal D. Peripheral Arterial Tonometry Events and EEG Arousals in Children. SLEEP 2004; 27(3):502-506.

42. Pittman DS, Ayas NT, MacDonald MM, Malhotra A, Fogel RB, White D. Using a Wrist-Worn Device Based on Peripheral Arterial Tonometry to Diagnose Obstructive Sleep Apnea: In-Laboratory and Ambulatory Validation. SLEEP 2004; 27(5):923-933.


43. Hedner J, Pillar G, Pittman DS, Zou D, Grote L, White D. A Novel adaptive wrist actigraphy algorithm for Sleep-Wake assessment in sleep apnea patients. SLEEP 2004; 27(8):1560-1566.

44. Penzel T, Kesper K, Pinnow I, Becker HF, Vogelmeier C. Peripheral arterial tonometry, oximetry and actigraphy for ambulatory recording of sleep apnea. Physiol Meas. 2004; 25(4):1025-1036.

45. Zou D, Grote L, Peker Y, Lindblad U, Hedner J. Validation of a Portable Monitoring Device for Sleep Apnea Diagnosis in a Population Base Cohort Using Synchronized Home Polysomnography. SLEEP 2006; 29(3):367-374.

46. Pittman S.D, Pillar G, Berry RB, Malhotra A, MacDonald MM, White DP. Follow-Up Assessment of CPAP Efficacy in Patients with Obstructive Sleep Apnea using an Ambulatory Device Based on Peripheral Arterial Tonometry. Sleep and Breathing 2006; 10(3):123-131.

47. Herscovici S, Peer A, Papyan S, Lavie p. Detecting REM sleep from the finger: automatic REM sleep algorithm based on Peripheral Arterial Tone (PAT) and actigraphy. Physiol Meas 2007; 28(2): 129-140.

48. O’Brien L. M., Gozal D. Potential Usefulness of Noninvasive Autonomic Monitoring in Recognition of Arousals in Normal Healthy Children. Journal of Clinical Sleep Medicine 2007; 3(1):41-47.

49. Kenny P. Pang, Christine G. Gourin and David J. Terris. A comparison of polysomnography and the WatchPAT in the diagnosis of obstructive sleep apnea. Otolaryngology - Head and Neck Surgery 2007; 137(4): 665-668

50. White DP. Monitoring peripheral arterial tone (PAT) to diagnose sleep apnea in the home. J Clin Sleep Med. 2008;4(1):73

51. Ma'ayan Bresler, Koby Sheffy, Giora Pillar, Meir Preiszler, Sarah Herscovici Differentiating between light and deep sleep stages using an Ambulatory Device Based on Peripheral Arterial Tonometry . Physiol Meas. 2008; 29(5): 571-584.

52. Richard B. Berry, Gilbert Hill, Linda Thompson, Valorea McLaurin, Malcom Randall. Portable Monitoring and Autotitration versus Polysomnography for the Diagnosis and Treatment of Sleep Apnea. SLEEP 2008; 31(10):1423-1431.

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