improving the selectivity of surface emg recordings of facial muscles: effects of electrode...

IMPROVING THE SELECTIVITY

OF SURFACE EMG RECORDINGS OF FACIAL MUSCLES:

EFFECTS OF ELECTRODE PARAMETERS

O. ROMIJN

Improving the selectivity of surface EMG recordings

2

Improving the Selectivity

of Surface EMG Recordings of Facial Muscles:

Effects of Electrode Parameters


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Table of contents Abstract 4 Introduction 5 What does facial behavior express? 5

Scoring facial behavior 5

Facial Action Coding System 6

Surface electromyography of facial muscles 6

The physiological basis of surface EMG 7

The composition of the surface EMG signal 9

Characteristics of surface EMG recordings: cross-talk 9

Reducing cross-talk: a practical approach 16

Aims of the present study 17

Methods 19 Subjects and experimental task 19

EMG recording 20

Electrodes 20

EMG analysis 22

Statistical analysis 25

Results 28 Amplitude 28

Selectivity 30 Discussion 45 Conclusions 48 References 49 Acknowledgments 54

Appendix 55


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Abstract

Facial behavior may provide a measure of the mental state of an individual. Surface EMG is

an objective method that is able to reveal non-visible changes in facial muscle tone. However,

cross-talk may hamper the interpretation of EMG records. The aim of this study is to reduce

cross-talk between facial muscles with a minimum number of concomitant drawbacks. Two

electrode parameters were examined: shape of the electrode contacts and bipolar spacing. The

EMG of twenty subjects was bilaterally recorded from 8 sites while they viewed 48 pictures,

which were presented in series. Although the parameters do affect the amplitude of the

myoelectric signal, no consistent results were found that point to an increase in selectivity of

the EMG signal as measured by the Selective Value (SV). However, it may be argued that the

SV by itself is not a reliable measure for selectivity.


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Introduction

What does facial behavior express?

In daily life, face-to-face discussions are characterized by a seemingly inexhaustible variety

of facial expressions. Presumably, facial expressions play an important role in interindividual

communication (e.g. Ekman, 1979). However, several studies (e.g. Ekman, 1972; Fridlund,

1991) indicate that social context is not a prerequisite for spontaneous facial expressions,

although it may be facilitating (e.g. Chapman, 1974).

As Darwin (1872) and James (1890) already noted, facial expressions might not merely serve

the goal of conveying information to the social environment. Darwin (1872) stated that

expressions might influence subjective feelings and other mental processes. Thus, facial

expressions may serve both as a read-out system of mental state in inter-individual interaction

(feed forward process) and as a sensory feedback system for the intra-individual experience

(e.g. Izard, 1977, 1981).

For this reason, facial behavior may provide a measure of the mental state of an individual.

(e.g. see Ekman & Friesen, 1978; Van Boxtel & Jessurun, 1993). However, in order to make

valid inferences about an individual’s mental state, one should at least be able to qualify and

quantify the exhibited facial behavior reliably.

Scoring facial behavior

Since facial behavior is brought about by facial muscle activity (e.g. Duchenne, 1862;

Hjorstjo, 1970; Lightoller, 1925) a scoring technique that encompasses the musculature of the

face ought to be preferred over techniques that merely focus on facial appearance (e.g.

Birdwhistell,1970; Blurton Jones, 1971; McGrew, 1972; Grant 1969; Brannigan &

Humphries, 1972). Ekman (1979) points out that some of these latter methods present

descriptions that are anatomically incorrect and therefore render error in classification.


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Facial Action Coding System

Ekman and Friesen (1978) presented a method that does take the anatomical constraints of the

facial musculature into account. They focused on determining the independent units of facial

action. The Facial Action Coding System (FACS; Ekman & Friesen, 1978) analyzes facial

behavior by observing its component elements: Action Units (AU). Any complex facial

behavior can be broken down into a set of single AU scores following the guidelines in the

corresponding manual. Although this method may be useful as a descriptive tool, it has at

least five considerable drawbacks that limit its usability:

1. the description of facial behavior is limited to visual movements;

2. the classification is somewhat subjective, for it requires an observer;

3. the quantification of intensity is restricted to a three point scale;

4. the process of describing facial behavior is time consuming;

5. the method is not a direct measure of facial muscle activity but instead looks at its

resultants, which are mediated by physiognomic factors such as wrinkles, bulges and

pouches.

Surface Electromyography of facial muscles

EMG recordings are less vulnerable to the aforementioned weaknesses, and may therefore be

a more desirable method of assessing facial behavior. However, this technique is far from

flawless (see the sections on cross-talk) and Ekman and Friesen (1978) question the general

usefulness of EMG: “…we think it is unlikely that surface electrodes could distinguish the

variety of visible movements which most other methods delineate”. Whether it is favorable to

describe the appearance of the face (FACS) or to measure the activity of the underlying

muscular tissue (EMG) remains a point of dispute. However, both the scientific demand of

objectivity and the utility in the case of covert facial movements put a heavy burden on the

Facial Action Coding System.

Before turning to the electromyographic signal, the physiological basis of surface EMG will

be briefly discussed.


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The physiological basis of surface EMG

The motor unit

Each striated muscle is innervated by a single motor nerve whose cell bodies are primarily

located in the ventral horn of the spinal cord or, in the case of the muscles of the head, in the

cranial nerves of the brain stem (Cacioppo et al., 1990). This motor nerve consists of

numerous individual motoneurons (Cacioppo et al., 1990), which divide into a number of

branches, termed axon fibrils, just before reaching the muscle. Each of these axon fibrils

forms a junction, termed a motor end plate, on an individual muscle fiber. As a result, a

motoneuron innervates a number of muscle fibers.

A motor unit (MU) consists of a cell body of the motoneuron, its axon, its axon fibrils and the

individual muscle fibers innervated by these axon fibrils. As Cacioppo et al. (1990) point out:

“An important functional consequence of this structure is that muscle fibers do not contract

individually but rather there is a concerted action by each set of muscle fibers innervated by a

single motoneuron”. The fibers of multiple motor units tend to be interspersed throughout the

muscle (e.g. Loeb & Gans, 1986).

The number of muscle fibers innervated by one motor neuron is termed the innervation ratio

and varies considerably between muscles. Low innervation ratios are found in muscles

involved in precisely controlled movements (e.g. Eccles & Sherington, 1930), whereas higher

– up to a factor 300 - innervation ratios can be found in the more slowly and grossly acting

postural muscles (Basmajian & DeLuca, 1985).

Although striated muscle fibers receive their stimulation via the motor end plates, which are

usually near the midpoint of each fiber (e.g. Loeb & Gans, 1986), the innervation is not

necessarily in the middle of the muscle (Roeleveld, 1997). The motor endplates may be

distributed along widely scattered zones (e.g. Masuda & DeLuca, 1991).

To increase the vigor of a muscle contraction, more MUs are activated (e.g. Henneman et al.,

1965) together with an increase in firing rate (e.g. Clamman, 1970).


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How muscles generate electricity

Loeb and Gans (1986) state that the muscle fiber can be thought of as a large-diameter,

unmyelinated nerve axon. The muscle fiber, like any neuron, actively maintains its

intracellular environment by means of a sodium-potassium pump. This mechanism collects

potassium ions and evicts sodium ions, thereby rendering a resting potential of about 80 mV

negative with respect to its surroundings (Loeb & Gans, 1986). The depolarization of a

motoneuron results in the release of acetylcholine at its motor end plates (DeLuca, 1989).

This excitation changes the fiber membrane’s permeability to both potassium and sodium

ions, causing the resting potential to drop temporarily (e.g. 1 ms; DeLuca, 1989).

Subsequently, voltage-sensitive channels, admitting sodium ions only, are opened (Gans &

Loeb, 1986). Soon afterwards, channels that let potassium ions pass are opened, enabling the

outward flow of potassium ions. As a resultant, the resting potential is restored. This whole

chain of events moves bi-directionally down the muscle fiber at about 2 to 5 m per second. As

the action potential travels along the muscle fiber, a small portion of this electrical activity

(see the section on bipolar electrode spacing) passes through the extracellular fluids to the

skin (DeLuca, 1989).

The series of bioelectrical events that give rise to a recorded voltage are as follows (Loeb &

Gans, 1986):

1. Changing conductivities in the membranes cause action currents to flow across the

membranes and in the extracellular fluids around active cells.

2. The extracellular currents cause potential gradients as they flow through the resistive

fluids.

3. The changing potential gradients give rise to electrical currents in the electrode leads

by capacitive conductance across the metal/electrolyte interface of the electrode

contacts. The currents actually flow through the high-impedance circuits of the

amplifier input stage.

4. The amplifier converts these weak currents into large output voltages.


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The composition of the surface EMG signal

The measured EMG is dependent on the total amount of activity in the pick-up range of the

surface electrodes. This amount of activity depends on the number of recruited MUs and their

firing rates.

Motor Unit Action Potentials

As pointed out in the previous section, surface electrodes can record the electrical activity that

passes through the extracellular fluids to the skin. However, the recorded voltage changes do

not emanate from a single Muscle-fiber Action Potential (MAP) but from aggregated Motor

Unit Action Potentials (MUAPs, e.g. DeLuca, 1989). A MUAP is the summation of action

potentials of all muscle fibers belonging to a specific Motor Unit (Roeleveld, 1997). Owing to

temporal and spatial differences between single MAPs, the MUAP is not simply the high-

amplitude version of a single MAP (e.g. Roeleveld, 1997). Since the recorded Compound

Motor Action Potentials (CMAPs) in surface EMG are the sum of MUAPs, which, in turn, are

the sum of single MAPs, “we can expect the waveform of the EMG signal to be highly

complex and random in its details” (Loeb & Gans, 1986, p.50).

Characteristics of surface EMG recordings: cross-talk

Surface electrodes are always at least some millimeters away from the closest active fibers

(e.g. Roeleveld, 1997). Therefore, MUAPs will be recorded with a relatively low spatial

resolution compared to invasive needle EMG (e.g. Nandedkar et al., 1985). The details of the

individual MUAPs and MAPs are lost, as well as their precise muscular origins (DeLuca,

1989).

The low degree of spatial resolution constitutes the major drawback of surface electrodes in

comparison to (indwelling) wire electrodes. Since surface electrodes have relatively large

pick-up areas, they are less selective (Barkhaus & Nandedkar, 1994). This means that signals

from muscles, other than the ones the electrodes are meant for, can also be registered

(O’Connell & Gardner, 1963). This phenomenon is termed cross-talk and has been described

by Denny-Brown as early as 1949. Note, that although this phenomenon prevails in surface

EMG, it may be apparent in (indwelling) wire EMG as well (e.g. Mangun et al., 1986;

Solomonow et al., 1994).


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Factors underlying cross-talk: physiological characteristics of the recording site

Mangun et al. (1986) point out that “Cross-talk can cause misinterpretations of muscle

function”. In one study, DeLuca (1988) estimated that as much as 16.6 % of the EMG of an

active muscle can be picked up at an electrode above a non-active neighboring muscle. Koh

and Grabiner (1992) reported comparable findings. Although Solomonow et al. (1994) point

out that the level of cross-talk is presumably over-estimated, he makes clear that “surface

electrodes are heavily contaminated with cross-talk if a subcutaneous layer of fat is located

under the electrodes”. Solomonow assumes that, in this case, as much as 37% of the mean

absolute value of the EMG may be due to cross-talk from adjacent muscles.

Several other factors besides volume conduction by adipose tissue affect the extent of cross-

talk in EMG recordings. The characteristics of both the recording site and the recording

device influence the spatial selectivity of the EMG recording.

Mangun et al. (1986) pointed out that cross-talk is more probable to occur in recordings from

small muscles or from those muscles which are relatively small as compared to neighboring

muscles with which they are in intimate contact. Clearly, the extent of intimate contact

depends for a great deal on the proximity of the neighboring muscle. In addition, since the

effect of the non-target muscle EMG signal depends on the amplitude of the target muscle

EMG signal, Mangun et al. (1986) noted that cross-talk is more probable when relatively

inactive muscles are recorded during a motor act that results in large activation of neighboring

muscles.

Barkhaus and Nandedkar (1994) noted that the amplitude of the MUAPs depends on the

distance between the electrode and the muscle fiber (see figure 3). When this distance

increases the amplitude decreases. They pointed out that this distance may be in a horizontal

plane as well as in a vertical plane (i.e. depth of the MUAP generator). Although a

neighboring muscle may be at considerable (horizontal) distance from the target muscle, its

relative effect on the surface EMG signal depends on the amplitude of the target-signal and

therefore on the depth of the target MUs. This depth is partly a result of both the skin and

adipose tissue thickness (Barkhaus & Nandedkar, 1994).

An experimenter is often not able to manipulate the conductive characteristics of the adipose

tissue, the skin thickness or the relative location of target as well as non-target muscles (see

also the section on reducing cross-talk). Furthermore, the experimenter is limited in his

capacity to exert influence on the activation of neighboring muscles through task


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manipulations. Nevertheless, there are a number of other factors that affect the extent of

cross-talk in the EMG signal, which can be manipulated more easily. These factors are related

to electrode parameters and to the employed method of analysis.

Factors underlying cross-talk: considering electrode parameters

Electrode placement

Cacioppo et al. (1990) note that electrodes should be arranged to span maximally the gradient

desired (e.g., in line with the underlying target-muscle) to maximize the recording of its

activity. Loeb and Gans (1986) point out that the bipolar electrode should be oriented parallel

to the voltage gradient to be measured. Therefore, electrodes should be aligned parallel to the

course of the muscle fibers. In addition, the electrodes should preferably be arranged distal

and perpendicular to gradients of extraneous signal sources (e.g. proximal non-target muscles)

to attenuate the recording of non-target activity. Figure 3 shows the effect of electrode

orientation.

A number of authors (e.g. Fridlund and Cacioppo, 1986; Tassinary et al., 1987; Tassinary et

al., 1989; Van Boxtel et al., 1984) have drawn up guidelines for an optimal electrode

montage. Note, however, that an optimal placement may require a compromise between the

two requirements mentioned above.

Dimensions of the electrode contacts

De Luca (1997) noted that the greater the number of fibers covered by the detection surface,

the greater the amplitude of the EMG signal turns out to be. Thus, both shape and size seem to

play a role. However, Jonas et al. (1999) report findings that indicate that this assumption

does not always hold. They argued that in a large muscle the size of the recording area indeed

determines the number of motor units actually collected, whereas in a small muscle this is not

the case. They found higher amplitudes with smaller recording areas and attributed this

difference to a decrease in phase cancellation with smaller electrodes.

Loeb and Gans (1986, p. 70) state that, in general, each recording contact should be as large

as feasible. They point out that “the notion that small electrode contacts provide greater

selectivity is basically wrong for bipolar electrodes”. According to Loeb and Gans (1986, p.


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70) the use of small registration contacts “adds only to noise and unduly biases the recordings

by concentrating on the signals from a few fibers”. Nonetheless, Winter et al. (1994) found

that decreasing the electrode’s recording area does reduce cross-talk. Apparently the optimal

electrode dimension depends partly on the underlying musculature and as Loeb and Gans

(1986) make clear, on the bipolar inter-electrode distance. As a rule of thumb they suggest

that the electrode’s contact dimensions should not be reduced below half the bipolar inter-

electrode distance.

Electrical characteristics of the two recording contacts

Since bipolar electrodes are used with a differential amplifier, which subtracts the two signals

prior to amplification, the two input signals should be as similar in size, electrical impedance

and physical environment as possible (Loeb & Gans, 1986). Loeb and Gans (1986) point out

that bipolar electrodes with dissimilar contacts are generally inferior in terms of common

mode rejection of remote electrical noise (e.g. cross-talk).

Bipolar electrode spacing

A large number of studies (e.g. Lynn et al., 1978; Reucher et al., 1987; Winter et al., 1994)

have shown that reduced bipolar spacing improves the selectivity of the EMG recording.

However, reduced bipolar spacing generally results in a decrease in amplitude of the recorded

EMG signal (e.g. Loeb & Gans, 1986; Jonas et al., 1999). In order to give insight into the

rationale behind determining the optimal bipolar spacing the flow of extracellular currents

that are picked up by surface electrodes will be described in more detail.

Loeb and Gans (1986) make clear that when the action potential starts to propagate from the

innervation point, the inward flow of positive sodium ions is temporarily restricted to this

region. This makes the region surrounding the innervation point look like a sink. From an

electrical point of view, “the circuit from outside to inside must be completed by a

complementary source of current”(Loeb & Gans, 1986, p.47), i.e. the source. This current

arises in the regions most adjacent to the sink, which are having their cations stripped from

the outer surface and their anions stripped from the inner surface of the membrane (see figure

1). “An instant later, these adjacent, passively depolarizing regions themselves become sinks

for sodium ions, with the passive source lying still further out to the ends of the muscle fiber.”


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The active current source (i.e. the outward flow of potassium ions) repolarizes the membrane

potential in the region that was first to depolarize (i.e. the innervation point).

Figure 1. Propagation of an action potential along a muscle fiber. Note the leading

edge at the top right of the figure. See text for details. Adapted from Loeb and

Gans (1986, p. 46).

An electrode in the extracellular fluid around such a discharging muscle fiber placed at some

distance from the innervation point would alternatively find itself near a current source

(cathode), then a current sink (anode) again followed by again a current source (see figure 1).

Suppose that the two recording contacts are positioned so that, at one instant, one lies right

over a current sink and the other over an active current sink. “At that instant a maximal

potential difference will be measured. The amplitude of this potential is the product of the

action current times the resistance of the local extracellular fluid through which the current

(mostly) flows.” The optimal bipolar spacing of the two recording contacts would be the

distance between the current source and sink (i.e. the dipole spacing). The process of

depolarization and repolarization back to resting level each takes about 0.5 ms (Loeb & Gans,

1986, p. 48) and thus about 1 ms in total (e.g. Cacioppo et al., 1990). If the disturbance is

known to be moving in tandem (i.e. sink followed by source) down the fiber at 5 m per


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second – the chain of events moves down the muscle fiber at about 2 to 5 m per second (Loeb

& Gans, 1986, p. 48-49)- then the length of the patch acting as a source or sink must be 0.5

times 5 mm per ms (=2.5 mm). Since the repolarizing action follows immediately on the heels

of the depolarizing action the dipole spacing will measure 2.5 mm as well. However, surface

electrodes cannot be placed right on top of a discharging muscle fiber. To describe the effect

of these more remote contact surfaces Loeb and Gans (1986) stated that only some of the

current can squeeze through the limited amount of resistive extracellular fluid right up next to

the fiber. The remaining current will have to take the long way around, thereby resembling

the magnetic flux lines surrounding a short bar magnet (see figure 2).

Figure 2. Current flow in the extracellular fluids around a muscle fiber generating an

action potential. See text for details. Adapted from Loeb and Gans (1986, p.

48).

Assuming that the detection surface runs parallel to the axis of the dipole, it becomes clear

that the distance from dipole axis to detection surface affects the bipolar spacing for

recordings of maximum amplitude. Hence, since the dipole spacing appears to be larger at the

detection surface due to the current taking the long way around, the two electrodes should

also be more widely spaced in order to record signals at maximum amplitude. Figure 3

shows the effects of the distance between the electrode and the source, electrode orientation

and bipolar spacing on the amplitude of the recorded EMG signal.


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Figure 3. Effects of bipolar spacing, electrode orientation and spacing between source

and electrode on the amplitude of the recorded EMG signal. The dipole

source is shown as a plus sign and a small circle. Adapted from Loeb and

Gans (1986, p. 63).

As a first approximation of the bipolar spacing, Loeb and Gans (1986) suggest that a

reasonable bipolar spacing can be calculated by taking the square of the perpendicular

distance from the electrodes to the fiber and adding it to the value of the dipole spacing for the

specific fiber.

The increase in selectivity due to a reduced bipolar spacing is based on the principle described

above. Since non-target fibers are presumably more remote from the dipole axis than target

fibers, their optimal bipolar spacing is larger than for the more adjacent target fibers.

Therefore, the amplitude of the EMG signal stemming from the more remote fibers will be

relatively low compared to the amplitude of the EMG stemming from the more adjacent

fibers. As a rule of thumb Loeb and Gans (1986) point out that, in order to record selectively,

the effective conductive path from dipole source to bipolar electrode (i.e. the path through the

extracellular volume-conductive tissues) should be equal to or less than the bipolar spacing.

Furthermore they note that, in order to reject selectively, the electrical path from dipole source

to bipolar electrode should be greater than four times the dipole spacing of the source.

Reducing the bipolar spacing works because “the amplitude of the potentials coming from

sources lying closer to the electrodes than the bipole separation only decreases linearly as the


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separation is made shorter than their dipole moments. For potentials that originate further than

four times the bipole separation from the electrode, the amplitude decreases as the square of

the distance” (Loeb & Gans, 1986, p. 70).

Reducing cross-talk: a practical approach

In order to reduce the extent of cross-talk, Loeb and Gans (1986) propose a procedure that

centers round the physiological basis of cross-talk: volume conduction of the myoelectrical

signal. They describe a method that isolates the target-muscle from non-target muscles by

placing a non-conductive barrier between the muscle-groups. Note that this procedure is

invasive. In general however, it is far more convenient to alter recording characteristics

(including electrode parameters) and methods of analysis than to manipulate the physiological

characteristics of the recording site.

As stated in the previous section, electrode placing, electrode orientation, electrode size,

bipolar spacing and the electrical properties of the electrode contacts may be altered to

increase spatial selectivity.

De Luca (1997) describes a method to reduce and possibly even eliminate cross-talk: the

double differential technique (see also Broman et al., 1985). This technique consists of using

a surface electrode that has (at least) three detection surfaces equally spaced apart. Initially,

two differential signals are obtained: one from detection surfaces 1 and 2 and another from

detection surfaces 2 and 3. Subsequently, a differential signal is obtained from these two. This

procedure decreases the pick-up volume of the electrode, thus filtering out more remote

signals from non-target muscles. The fact that additional equipment is required constitutes the

major drawback of this method.

The aforementioned methods focus on the acquisition of EMG signals rather than on the

analysis of EMG signals. However, there are several ways to reduce the extent of cross-talk

by means of data analysis.

Since cellular media act as a low pass filter (e.g. Mangun et al., 1986), signals stemming from

more remote muscles are characterized by a lower frequency spectrum (e.g. De Luca, 1997).

This characteristic can be used to rid cross-talk from the target signal by applying a high-pass

filter (90 or 100 Hz) to the data (e.g. Cacioppo et al., 1990). Bear in mind that subjecting the

data to an external high-pass filter results in the elimination of a significant portion of the


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EMG signal. Note that closely spaced bipolar electrodes have intrinsic high-pass filtering

characteristics. Thus, a reduced bipolar spacing results in an increase in both the bandwith and

in the peak frequency of the EMG spectrum (e.g. Loeb & Gans, 1986; McLeod et al., 1976).

Another approach to reducing cross-talk is to record all of the adjacent potential cross-talk

sites simultaneously (e.g. De Luca, 1997; Loeb & Gans, 1986) and somehow remove the

cross-correlated signal originating in non-target muscles from the EMG record of the target

muscle. Note that the term “non-target muscles” refers to muscles that are not of interest to

the experimenter. Even if the adjacent muscles are synergists, there should be little or no

overlap in the precise timing of peaks and valleys in the EMG signal. However, for this

method to be effective, it is necessary to determine where the cross-related signal originates.

Although this remains somewhat speculative, this question could be answered by focusing on

the amplitude of the cross-related signal in all records: the cross-related EMG signal from

non-target muscles is likely to display a lower amplitude than the cross-correlated EMG from

target muscles (see section on bipolar spacing). Unfortunately, this method has a few

disadvantages. Firstly, it is necessary to place electrodes on all potential cross-talk sites and to

perform computations on the EMG dataset making the method somewhat cumbersome.

Secondly, De Luca (1997) points out that the properties of the conduction volume may cause

the signal to be scrambled in the frequency domain, which may cause the signals to appear

uncorrelated. Furthermore, it is not fully clear how to correct the data reliably for cross-talk.

Aims of the present study

Since facial muscles are 1) fairly small 2) in close proximity to one another and 3) may be

covered by adipose tissue, the recorded surface EMG is bound to suffer from cross-talk. This

hampers the interpretation of the recorded EMG. Several authors (see previous section) have

sought ways to reduce cross-talk in EMG recordings, but they have not specifically focused

on the facial region. Each of the available methods described in the previous section appears

to be accompanied by considerable drawbacks (e.g. cumbersome, eliminating significant

portion of the EMG signal, reducing signal amplitude, requiring additional equipment). This

study is aimed at reducing cross-talk between facial muscles at the level of data acquisition

with a minimum number of concomitant disadvantages.

The study centers round bipolar spacing, since this electrode parameter has shown to affect

the extent of cross-talk in EMG recordings considerably.


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Hypotheses

Main hypothesis:

I. The two electrode types yield different EMG signals.

However, two sub hypotheses are of specific interest:

II. The amplitude of the surface EMG signal is lower for surface electrodes with a small

bipolar spacing than for surface electrodes with a larger bipolar spacing.

III. Recordings of EMG with surface electrodes with a small bipolar spacing display a

higher degree of spatial selectivity than recordings with electrodes with a larger

bipolar spacing.


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Methods

Subjects and experimental task

Twenty healthy undergraduate students (10 males and 10 females, mean age: 22.2, SD: 3.5)

participated in the experiment. Testing took place in an electrically shielded, sound

attenuating cabin. During the experiment, subjects were seated in a comfortable reclining

chair. They received study credits for their voluntary cooperation.

The subject pool was divided into two groups of 10 subjects each (5 males and 5 females, see

section on EMG recordings). All subjects were asked to view 48 pictures from the IAPS

dataset (Lang et al., 1999; see appendix for details). The pictures were presented serially, thus

one at a time, on a monitor placed in front of the subjects. The distance between the subject

and the screen measured approximately 1.5 m

Each picture appeared on the screen for a 6 s period. Following each picture, subjects rated

the affective value of the picture on six five-point scales (see appendix for details), presented

on the monitor in series. In order to move the cursor on the screen, a response manipulandum

was affixed to the right-hand armrest of the chair. The manipulandum consisted of three

buttons placed in a triangular fashion. The buttons that made up the horizontal base of the

triangle were used to move the cursor horizontally whereas the top button was pressed to

enter their choice. As a default, the cursor was positioned at the first point of the five-point

scale. The manipulandum could be operated with a single finger.

The inter trial interval (ITI) is defined as the period between the last rating and the subsequent

picture and could range from 9 to 19 s. The interval between picture offset and the

presentation of the first scale measured 2.5 s. The first five scales were followed by an

interval of 1.5 s during which subjects watched a darkened screen. Subjects had to respond

within 9 s. The location of the cursor that conveyed their judgment was stored, even if they

failed to enter before the 9 s time-out. After 7 s subjects received a visual incitement to

respond by means of a change in font color. Subjects could control the length of the trial by

timing their responses. Theoretically, the absolute minimal interval between pictures

measured 19 s: subjects then had to respond within 1 ms and the ITI had to measure 9 s (viz.,

2.5 + (5* 1.5) + 9 = 19). However, this interval could measure up to 83 s when the subject

always required the maximum response interval and when the ITI measured 19 s (viz., 2.5 +

(5*1.5) + (6*9) + 19 = 83).


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The experiment was divided into 3 blocks. The first block counted 17 pictures, the subsequent

two blocks 16 pictures (the third block contained a picture already shown in block 1). A 5-

min rest period separated each block. The experiment took approximately 50 minutes in total,

apart from electrode montage and instructions.

EMG recording

EMG signals were differentially recorded (sampling rate of 1024 Hz) on a trial basis starting

from 4 seconds preceding stimulus presentation to 1 s post stimulus presentation (11 seconds

in total). The 4 s interval preceding stimulus presentation served as a baseline interval

whereas the 6 s period during stimulus presentation represented the active interval. EMG

signals were amplified and band-pass filtered (-3dB high-pass cutoff frequency at 3.8 Hz and

attenuation rate 31 dB per octave; -3 dB low-pass cutoff frequency at 520 Hz and attenuation

rate 13.5 dB per octave) and stored on a local harddisk.

Electrodes

Two types of electrodes were used in the experiment: conventional Ag-AgCl electrodes

(diameter recording surface: 2 mm) and custom built Ag bar electrodes (recording surface:

width1 mm, length 7 mm). The bipolar electrode spacings measured 15 mm (from center to

center) for the conventional electrodes and 5 mm for the custom built bar electrodes (figure

4). The casing of the custom built bar electrode was made of synthetic resin (width 10 mm,

length 10 mm, height 5 mm) and had indentations (width 1mm, length 7mm, depth 0.6 mm ±

0.2 mm) in which the Ag bars were placed. These indentations served as an electrolyte

reservoir. The reference electrode (diameter Ag-AgCl recording surface: 10 mm) was placed

on the forehead.

To prevent the detection surfaces of the bar electrodes from being electrically shunted, a bi-

adhesive non-conductive barrier was placed between the two indentations.


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Figure 4. Design of the bar electrode.

EMG from 8 facial muscles was bilaterally recorded, rendering 16 EMG electrode-pair sites

(figure 5). Electrode locations on corrugator supercilii, orbicularis oculi, zygomaticus major,

levator labii superioris alaeque nasi, masseter, orbicularis oris and mentalis were in

accordance with the guidelines presented by Fridlund and Cacioppo (1986). Electrodes on the

frontalis muscle were placed on an imaginary vertical line traversing the pupil of the eye, with

the lower electrode (in the case of the conventional electrodes) 15 mm above the upper border

of the eyebrow. The bar electrodes were placed in the center of the imaginary axis of the

conventional electrodes.


22

Figure 5. Electrode configuration.

In one group of subjects (N= 10: 5 male, 5 female) the conventional electrodes were placed

over the musculature of the left side of the face, whereas the custom built bar electrodes were

placed on the right side of the face. In the second group (N=10: 5 male, 5 female), the

electrodes were mounted vice versa. Thus, electrode montage was counterbalanced.

EMG analysis

In order to answer the research question reliably, a lengthy path of analysis should be

followed. As pointed out in the section on reducing cross-talk, it is possible if not essential to

focus on different aspects of the EMG signal to reveal and eliminate cross-talk. This paper

will describe an initial explorative analysis of one of the characteristics of the recorded EMG

signal aspects: the mean absolute value (MAV).

The experiment consisted of 48 trials per subject. The total number of trials is therefore (48 *

20 =) 960 trials. All trials were visually inspected in order to detect possible artifacts. These

could be clear non-physiological signals, disturbances caused by the movement of the


23

electrode relative to the skin and excessive muscle activity on multiple channels. Trials with

artifacts were removed from the dataset. This procedure resulted in 902 valid trials.

For each channel, the EMG activity in both the baseline interval and the active interval was

rectified and averaged over the length of the respective interval to calculate the MAV.

The MAV of the active interval was then compared to the MAV of the baseline interval. Two

distinct methods of comparison were employed:

1. Expressing the active MAV as a percentage of the baseline MAV: MAVperc

2. Subtracting the baseline MAV from the active MAV: MAVdelta

In the first method, z-scores of the MAVperc for each separate trial were calculated for each

of the 8 muscles in both electrode types. A trial yielded 8 z-scores for each electrode type: the

8 muscles in the subpopulation on which the z-scores were based. Thus, the z-scores were

based on the mean and the standard deviation of the 8 MAVsperc per trial. This process

resulted in (N pictures * N muscles * N electrode types * Nsubjects - (N rejected trials * 8 *

2) = 48 * 8 * 2 * 20 – 928 =) 14432 z-scores in total.

In the second method, z-scores of the MAVdelta for each separate trial were calculated for

each of the 8 muscles in both electrode types. A trial yielded 8 z-scores for each electrode

type: the 8 muscles in the subpopulation on which the z-scores were based. Thus, the z-scores

were based on the mean and the standard deviation of the 8 MAVsdelta per trial. This

procedure again resulted in 14432 z-scores in total.

These z-scores allow for a direct comparison between the two types of electrodes. Comparing

non-standardized scores seems pointless since the magnitude of both MAVperc and

MAVdelta are likely to differ substantially between electrode types, resulting in biased

measures. By calculating the MAVperc z-score and the MAVdelta z-score of a particular

muscle (as described above) this problem is circumvented.


24

Cross-talk is expected to prevail in neighboring muscles (see sections on cross-talk).

Therefore, the EMG signal at the following muscle-pairs was assumed to suffer from cross-

talk:

• frontalis and corrugator

• orbicularis oculi and levator

• orbicularis oculi and zygomaticus

• zygomaticus and levator

• zygomaticus and masseter

• orbicularis oris and mentalis

In addition, one may hypothesize that cross-talk will occur in the following muscle-pairs:

• orbicularis oris and masseter

• orbicularis oris and zygomaticus

To test whether the two electrode types do render different EMG signals, as the main

hypothesis (I) suggests, the MAVperc z-score of one of the two muscles in a muscle-pair was

subtracted from the other muscle’s MAVperc z-score. This was done for each trial. Thus, one

electrode type yielded 902 subtractions for each muscle-pair. The resultant of this procedure

was termed Dominant Muscle Value (DMV) and indicates which muscle of the two has a

higher MAVperc. This procedure was repeated for the MAVdelta z-scores. A difference in

DMV would confirm the main hypothesis (I) especially if the dominant muscle differs

between the two types of electrodes.

To compare the effectiveness of the electrode-types with regard to selectivity (as opposed to

cross-talk) the selective value (SV) was calculated. This was done as follows. Whenever the

subtraction described above (i.e. the subtraction per trial) rendered a negative measure its

value was converted into its opposite value. This procedure was repeated for the MAVdelta z-

scores. Thus, the SV does not reflect which of the two muscles in the muscle-pair is dominant

but only how large the difference between the two is. The electrode type that has the highest

SV is assumed to yield the more selective EMG recording. A difference in SV between the

two electrode types would confirm the main hypothesis (I). Furthermore, if the SV turns out

to be higher for the new electrodes hypothesis III would be confirmed.


25

Bear in mind that there are two DMVs and two SVs: DMVperc, DMVdelta, SVperc, and

SVdelta.

In order to test hypothesis (II) the MAVs in the baseline as well as in the active interval of

one electrode type are compared with the corresponding MAVs of the other electrode type.

Note that if the MAVs in both intervals turn out to be lower in the new electrodes, both

hypothesis I and II are confirmed.

To test whether the employed measure for selectivity (SV) is reliable, a muscle-pair that is

very unlikely to suffer from reciprocal cross-talk was encompassed in the analysis:

• corrugator and mentalis

Statistical analysis

To test whether the MAVs differed between electrode types (hypothesis I and II), a paired t-

test was performed on both the baseline MAV and the active MAV between electrode-type

for each muscle group.

To test whether the new electrodes rendered a more selective EMG recording (hypothesis I

and III), the SV of the bar electrodes was compared with the SV of the conventional

electrodes by means of a paired t-test over all trials.

To test whether the dominant muscle differed between the two electrode types (hypothesis I) a

t-test was performed on DMVperc in the cases where one of the two electrode types rendered

a DMVperc with a negative value while the other produced a positive value. A statistically

significant difference between the DMVperc in these cases indicates that the dominant muscle

differed between the two electrode types. This procedure was repeated for the DMVsdelta.

It may be hypothesized that the level of cross-talk is linearly related to the level of activity of

the signal source muscle (e.g. Solomonov et al., 1994). Therefore, four additional datasets

were created: a high MAVperc dataset, a low MAVperc dataset, a high MAVdelta dataset

and a low MAVdelta dataset. The datasets were created as follows. For each muscle in the

muscle pair the z-score over all 902 trials was computed. If the MAVperc of at least one of

the muscles in the muscle-pair differs from the mean (N=902) by more than one standard


26

deviation, the trial is added to the high MAVperc dataset, which is termed the “>1 SD

dataset”. Note that there are 4 MAVsperc that have to be considered: muscle 1 and muscle 2

measured with conventional electrodes and muscle 1 and 2 measured with the new bar

electrodes. This procedure is repeated for the MAVsdelta. If the MAVperc of none of the

muscles in the muscle-pair differs from the mean (N=902) by more than one standard

deviation, the trial is added to the low MAVperc dataset, which is termed “< 1 SD dataset”.

This procedure was again repeated for the MAVsdelta.

A paired t-test on the SVperc between new and old electrodes was carried out for each

muscle-pair in both the “> 1 SD dataset” and the “< 1 SD dataset” for both the MAVsperc and

the MAVsdelta. This was done to test whether the new electrodes rendered a more selective

EMG recording (hypothesis I and III) in one of the two additional datasets. This procedure

was repeated for the SVsdelta.

To test whether the dominant muscle differed between the two electrode types (hypothesis I)

in the two additional datasets, a t-test was performed on DMVperc in the cases where one of

the two electrode types rendered a DMVperc with a negative value while the other produced a

positive value. A statistically significant difference between the DMVperc in these cases

indicates that the dominant muscle differed between the two electrode types. This procedure

was repeated for the DMVsdelta.

To test whether the differences in SVperc between the two electrode types were caused by

several outliers with a high MAVperc, a non parametric test (binomial test) was performed in

all three datasets. In order to perform this test the SVsperc of the new electrodes were

subtracted from the SVsperc of the old electrodes. A negative value therefore denotes a

higher SVperc for the new electrodes. These Differential Scores (DS) were then converted to

a dichotomous dataset in which DSperc < 0 becomes -1 and DSperc > 0 becomes 1. The

binomial test was performed on this dichotomous dataset and was equivalent to a signtest.

This procedure was repeated for the SVsdelta.

The following scheme provides a summary of the statistical analyses carried out for each

target muscle-group:

Unconstraint dataset

• t-test baseline MAV new and baseline MAV old

• t-test active MAV new and active MAV old


27

• t-test between SVperc new and SVperc old

• t-test between SVdelta new and SVdelta old

• t-test between DMVperc new and DMVperc old

• t-test between DMVdelta new and DMVdelta old

• signtest on (SVperc old minus SVperc new)

• signtest on (SVdelta old minus SVdelta new)

> 1 SD dataset




< 1 SD dataset




> 1 SD dataset




< 1 SD dataset





28

Results

Amplitude

The MAVs old in both the baseline interval and active interval were significantly higher than

the MAVs new for all eight muscles (see figure 6 and 7, respectively). Table 1 and 2 provide

an overview of the performed paired t-tests on the MAVs between old and new electrodes in

the baseline and active interval, respectively.

0

10

20

30

40

50

60

70

80

fron_old

fron_new

corr_old

corr_new

ocul_old

ocul_new

leva_old

leva_new

zygo_old

zygo_new

mass_old

mass_new

oris_old

oris_new

ment_old

ment_new

MAV

Figure 6. MAV in the baseline interval for old and new electrodes. Note that the new

electrodes are characterized by a significantly lower MAV for all 8 muscles.


29

0

10

20

30

40

50

60

70

fron_old

fron_new

corr_old

corr_new

ocul_old

ocul_new

leva_old

leva_new

zygo_old

zygo_new

mass_old

mass_new

oris_old

oris_new

ment_old

ment_new

MAVs

Figure 7. MAV in the active interval for old and new electrodes. Note that the new

electrodes are characterized by a significantly lower MAV for all 8 muscles.

Muscle-pair t df p

frontalis_old vs frontalis_new 27.22 901 < 0.001

corrugator_old vs corrugator_new 37.75 901 < 0.001

orb. oculi_old vs orb. oculi_new 27.05 901 < 0.001

levator_old vs levator_new 34.11 901 < 0.001

zygomaticys_old vs zygomaticus_new 25.75 901 < 0.001

masseter_old vs masseter_new 17.74 901 < 0.001

orb. oris_old vs orb. oris_new 23.52 901 < 0.001

mentalis_old vs mentalis_new 34.72 901 < 0.001

Table 1. Results of the paired t-tests between new and old electrodes on the MAVs in

the baseline interval for all 8 muscles.


30

Muscle-pair t df p

frontalis_old vs frontalis_new 28.30 901 < 0.001

corrugator_old vs corrugator_new 38.08 901 < 0.001

orb. oculi_old vs orb. oculi_new 25.19 901 < 0.001

levator_old vs levator_new 26.48 901 < 0.001

zygomaticus_old vs zygomaticus_new 23.20 901 < 0.001

masseter_old vs masseter_new 16.36 901 < 0.001

orb. oris_old vs orb. oris_new 25.21 901 < 0.001

mentalis_old vs mentalis_new 33.93 901 < 0.001

Table 2. Results of the paired t-tests between new and old electrodes on the MAVs in

the active interval for all 8 muscles.

Selectivity

Unconstraint dataset

Figure 8 shows the SVperc of all muscle-pairs for both electrode types in the unconstraint

dataset. Note that the SVperc is significantly higher for the new electrodes in the muscle-pairs

frontalis/corruagator, oris/mentalis, oris/zygomaticus and corrugator/mentalis. In the

oculi/zygomaticus, oculi/levator, zygomaticus/levator muscle-pairs the SVperc turns out to be

significantly higher for the old electrodes than for the new electrodes. The paired t-tests did

not reveal any differences in the SVperc between old and new electrodes in the

zygomaticus/masseter and oris/masseter muscle-pairs. Table 3 provides an overview of the

performed paired t-tests on the SVsperc between old and new electrodes.

In addition, the DMVperc in both the oris/zygomaticus and the oris/mentalis muscle-pair has

a negative value for the old electrodes and a positive value for the new electrodes pointing to

differences in the muscle exhibiting preponderant activity. The difference in the DMVsperc

between the two electrode types are statistically significant: t (1, 901) = -3.54, p <0.001 and

t (1, 901) = -2.74, p < 0.001, respectively.


31

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

fron/corr_O

fron/corr_N

ocul/zygo_O

ocul/zygo_N

ocul/leva_O

ocul/leva_N

zygo/leva_O

zygo/leva_N

zygo/mass_O

zygo/mass_N

oris/ment_O

oris/ment_N

oris/mass_O

oris/mass_N

oris/zygo_O

oris/zygo_N

corr/ment_O

corr/ment_N

SVperc

Figure 8. SVperc of all muscle-pairs for both electrode types in the unconstraint

dataset (N=902).

Muscle-pair t df p

fron/corr_old vs fron/corr_new -3.56 901 < 0.001

ocul/zygo_old vs ocul/zygo_new 6.73 901 < 0.001

ocul/leva_old vs ocul/leva_new 5.07 901 < 0.001

zygo/leva_old vs zygo/leva_new 5.92 901 < 0.001

zygo/mass_old vs zygo/mass_new 0.51 901 0.609

oris/ment_old vs oris/ment_new -6.94 901 < 0.001

oris/mass_old vs oris/mass_new 0.04 901 0.965

oris/zygo_old vs oris/zygo_new -2.89 901 < 0.001

corr/ment_old vs corr/ment_new -5.38 901 < 0.001

Table 3. Results of the paired t-tests between new and old electrodes on the SVperc for

all muscle-pairs in the unconstraint dataset.


32

Figure 9 shows the SVdelta of all muscle-pairs for both electrode types in the unconstraint

dataset. Note that the SVdelta is significantly higher for the new electrodes in the muscle-

pairs oris/masseter and oris/zygomaticus. The SVdelta turns out to be higher for the old

electrodes in the muscle-pairs frontalis/corrugator, oculi/zygomaticus, zygomaticus/levator

and corrugator/mentalis. The paired t-tests did not reveal any differences in the SVperc

between old and new electrodes in the oculi/levator, zygomaticus/masseter and oris/mentalis

muscle-pairs. Table 4 provides an overview of the performed paired t-tests on the SVperc

between old and new electrodes.

In addition, the DMV in the masseter/oris muscle-pair has a negative value for new electrodes

and a positive value for old electrodes indicating that the muscle displaying preponderant

activity differs between electrodetypes. The difference in the DMVdelta between the two

electrode types in the masseter/oris muscle-pair is statistically significant: t (1, 901) = 4.59, p

< 0.001.

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

fron/corr_O

fron/corr_N

ocul/zygo_O

ocul/zygo_N

ocul/leva_O

ocul/leva_N

zygo/leva_O

zygo/leva_N

zygo/mass_O

zygo/mass_N

oris/ment_O

oris/ment_N

oris/mass_O

oris/mass_N

oris/zygo_O

oris/zygo_N

corr/ment_O

corr/ment_N

SVdelta

Figure 9. SVdelta of all muscle-pairs for both electrode types in the unconstraint

dataset (N=902).


33

Muscle-pair t df p

fron/corr_old vs fron/corr_new 6.58 901 < 0.001

ocul/zygo_old vs ocul/zygo_new 2.71 901 0.007

ocul/leva_old vs ocul/leva_new 0.74 901 0.462

zygo/leva_old vs zygo/leva_new 3.49 901 0.001


oris/ment_old vs oris/ment_new -0.19 901 0.852

oris/mass_old vs oris/mass_new -3.60 901 < 0.001

oris/zygo_old vs oris/zygo_new -6.21 901 < 0.001

corr/ment_old vs corr/ment_new 6.50 901 < 0.001

Table 4. Results of the paired t-tests between new and old electrodes on the SVdelta

for all muscle-pairs in the unconstraint dataset.

The signtest on SVperc in the unconstraint dataset (see table 5) indicates that the new

electrodes are more often characterized by a higher SVdelta than the old electrodes in the

oris/mentalis, oris/zygomaticus and corrugator/mentalis muscle-pairs. The opposite holds for

the oculi/zygomaticus, oculi/levator and zygomaticus/levator muscle-pairs. No statistically

significant differences were found for the frontalis/corrugator, zygomaticus/masseter and

oris/masseter muscle-pairs.

Muscle-

pair

N

(SV new>SV old)

N

(SV new<SV old)

N

total

observed p

(SV new>SV old) p

fron/corr 478 424 902 0.53 0.078

ocul/zygo 373 529 902 0.41 <0.001

ocul/leva 380 522 902 0.42 <0.001

zygo/leva 376 526 902 0.42 <0.001

zygo/mass 457 445 902 0.51 0.714

oris/ment 528 374 902 0.59 <0.001

oris/mass 451 451 902 0.50 1.000

oris/zygo 493 409 902 0.55 <0.001

corr/ment 501 401 902 0.56 <0.001

Table 5. Results of the signtest on (SVperc_old minus SVperc_new) for all muscle-

pairs in the unconstraint dataset.


34

The signtest on SVdelta in the unconstraint dataset (see table 6) indicates that the new

electrodes are more often characterized by a higher SVdelta than the old electrodes in the

oris/zygomaticus muscle-pair. The opposite holds for the frontalis/corrugator,

oculi/zygomaticus, oculi/levator, zygomaticus/levator, corrugator/mentalis. No statistically

significant differences were found for the zygomaticus/masseter, oris/mentalis and


Muscle-

pair

N

(SV new>SV old)

N

(SV new<SV old)

N

total

observed p

(SV new>SV old) p

fron/corr 357 545 902 0.40 <0.001

ocul/zygo 405 497 902 0.45 0.002

ocul/leva 392 510 902 0.43 <0.001

zygo/leva 385 517 902 0.43 <0.001

zygo/mass 450 452 902 0.50 0.973

oris/ment 458 444 902 0.55 0.665

oris/mass 470 432 902 0.52 0.218

oris/zygo 540 362 902 0.60 <0.001

corr/ment 370 532 902 0.41 <0.001

Table 6. Results of the signtest on (SVdelta_old minus SVdelta_new) for all muscle-

pairs in the unconstraint dataset.

Dataset > 1 SD

Figure 10 shows the SVperc of all muscle-pairs for both electrode types in the “>SD dataset”.

Note that the SVperc is significantly higher for the new electrodes in the frontalis/corrugator,

oris/mentalis and corrugator/mentalis muscle-pairs. In the oculi/levator and the

zygomaticus/levator muscle-pairs the SVperc turns out to be significantly higher for the old

electrodes than for the new electrodes. The paired t-tests did not reveal any differences in the

SVperc between old and new electrodes in the oculi/zygomaticus, zygomaticus/masseter,

oris/masseter and oris/zygomaticus muscle-pairs. Table 7 provides an overview of the

performed paired t-tests on the SVsperc between old and new electrodes.

No significant differences between the DMVperc were found.


35

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

fron/corr_O

fron/corr_N

ocul/zygo_O

ocul/zygo_N

ocul/leva_O

ocul/leva_N

zygo/leva_O

zygo/leva_N

zygo/mass_O

zygo/mass_N

oris/ment_O

oris/ment_N

oris/mass_O

oris/mass_N

oris/zygo_O

oris/zygo_N

corr/ment_O

corr/ment_N

SVperc

Figure 10. SVperc of all muscle-pairs for both electrode types in the “> 1 SD dataset”.

Muscle-pair t df p

fron/corr_old vs fron/corr_new -4.51 334 <0.001

ocul/zygo_old vs ocul/zygo_new 1.69 205 <0.093


zygo/leva_old vs zygo/leva_new 4.63 140 <0.001

zygo/mass_old vs zygo/mass_new 0.56 148 <0.574

oris/ment_old vs oris/ment_new -3.80 204 <0.001

oris/mass_old vs oris/mass_new 0.01 189 0.990

oris/zygo_old vs oris/zygo_new -1.29 175 0.198

corr/ment_old vs corr/ment_new -4.32 273 <0.001

Table 7 . Results of the paired t-tests between new and old electrodes on the SVperc for

all muscle-pairs in the “>1 SD dataset”.


36

Figure 11 shows the SVdelta of all muscle-pairs for both electrode types in the “> 1SD

dataset”. Note that the SVdelta is significantly higher for the new electrodes in the

oris/zygomaticus muscle-pair. The SVdelta turns out to be higher for the old electrodes in the

frontalis/corrugator and corrugator/mentalis muscle-pairs. The paired t-tests did not reveal

any differences in the SVdelta between old and new electrodes in the remaining muscle-pairs.

Table 8 provides an overview of the performed paired t-tests on the SVdelta between old and

new electrodes.

In addition, the DMV in the oculi/levator, zygomaticus/levator muscle-pairs has a positive

value for new electrodes and a negative value for old electrodes and vice versa for the

masseter/oris muscle pair. Thus, for the three muscle-pairs the muscle displaying

preponderant activity differs between the two types of electrodes. The difference in the

DMVdelta between the two electrode types in the three muscle-pair is statistically significant:

t(1, 167) = -2.19, p = 0.03; t(1, 133) = -2.22, p = 0.028 and t(1, 229) = 3.76, p < 0.001,

respectively.


37

0

0.5

1

1.5

2

2.5

fron/corr_O

fron/corr_N

ocul/zygo_O

ocul/zygo_N

ocul/leva_O

ocul/leva_N

zygo/leva_O

zygo/leva_N

zygo/mass_O

zygo/mass_N

oris/ment_O

oris/ment_N

oris/mass_O

oris/mass_N

oris/zygo_O

oris/zygo_N

corr/ment_O

corr/ment_N

SVdelta

Figure 11. SVdelta of all muscle-pairs for both electrode types in the “>1 SD dataset”.

Muscle-pair t df p

fron/corr_old vs fron/corr_new 4.39 318 <0.001


ocul/leva_old vs ocul/leva_new -0.16 167 0.873



oris/ment_old vs oris/ment_new -1.44 209 0.153

oris/mass_old vs oris/mass_new -1.58 229 0.115

oris/zygo_old vs oris/zygo_new -4.64 202 <0.001

corr/ment_old vs corr/ment_new 2.48 290 0.014

Table 8 . Results of the paired t-tests between new and old electrodes on the SVdelta

for all muscle-pairs in the “>1 SD dataset”.


38

The signtest on SVperc in the “>1 SD dataset” (see table 9) indicates that the new electrodes

are more often characterized by a higher SVperc than the old electrodes in the

frontalis/corrugator, oris/mentalis and corrugator/mentalis muscle-pairs. The opposite holds

for the oculi/levator and zygomaticus/levator muscle-pairs. No statistically significant

differences were found for the oculi/zygomaticus, zygomaticus/masseter, oris/masseter and

oris/zygomaticus muscle-pairs.

Muscle-

pair

N

(SV new>SV old)

N

(SV new<SV old)

N

total

observed p

(SV new>SV old) p

fron/corr 208 127 335 0.62 <0.001

ocul/zygo 93 113 206 0.45 0.186

ocul/leva 84 119 203 0.41 0.017

zygo/leva 46 95 141 0.33 <0.001

zygo/mass 75 74 149 0.50 1.000

oris/ment 123 82 205 0.60 0.005

oris/mass 98 92 190 0.52 0.717

oris/zygo 100 76 176 0.56 0.083

corr/ment 158 116 274 0.58 0.013


pairs in the“>1 SD dataset”.

The signtest on SVdelta in the “>1 SD dataset” (see table 10) indicates that the new electrodes

are more often characterized by a higher SVdelta than the old electrodes in the

oris/zygomaticus muscle-pair. The opposite holds for the frontalis/corrugator, oculi/levator

and corrugator/mentalis muscle-pairs. No statistically significant differences were found for

the oculi/zygomaticus, zygomaticus/levator, zygomaticus/masseter, oris/mentalis and



39

Muscle-

pair

N

(SV new>SV old)

N

(SV new<SV old)

N

total

observed p

(SV new>SV old) p

fron/corr 137 182 319 0.43 0.014

ocul/zygo 85 104 189 0.45 0.190

ocul/leva 68 100 168 0.40 0.017

zygo/leva 73 61 134 0.54 0.342

zygo/mass 75 98 173 0.43 0.094

oris/ment 113 97 210 0.54 0.301

oris/mass 119 111 230 0.48 0.644

oris/zygo 135 68 203 0.67 <0.001

corr/ment 121 170 291 0.42 0.005


pairs in the “>1 SD dataset”.

Dataset < 1 SD

Figure 12 shows the SVperc of all muscle-pairs for both electrode types in the “< 1SD

dataset”. Note that the SVperc is significantly higher for the new electrodes in the

frontalis/corrugator, oris/mentalis, oris/zygomaticus and corrugator/mentalis muscle-pairs.

Note that the difference between old and new electrodes is marginally significant in the

frontalis/corrugator muscle-pair. The SVperc turns out to be higher for the old electrodes in

the oculi/zygomaticus, oculi/levator and zygomaticus/levator muscle-pairs. The paired t-tests

did not reveal any differences in the SVperc between old and new electrodes in the

zygomaticus/masseter and oris/masseter muscle-pairs. Table 11 provides an overview of the

performed paired t-tests on the SVperc between old and new electrodes.

In addition, the DMV in the oris/zygomaticus muscle-pair has a positive value for new

electrodes and a negative value for old electrodes, indicating that the muscle displaying

preponderant activity differs between the two types of electrodes. The difference in the

DMVperc between the two electrode types in the three muscle-pair is statistically significant:

t(1, 173) = -2.80, p = 0.005.


40

0

0.2

0.4

0.6

0.8

1

1.2

1.4

fron/corr_O

fron/corr_N

ocul/zygo_O

ocul/zygo_N

ocul/leva_O

ocul/leva_N

zygo/leva_O

zygo/leva_N

zygo/mass_O

zygo/mass_N

oris/ment_O

oris/ment_N

oris/mass_O

oris/mass_N

oris/zygo_O

oris/zygo_N

corr/ment_O

corr/ment_N

SVperc

Figure 12. SVperc of all muscle-pairs for both electrode types in the

“< 1 SD dataset”.

Muscle-pair t df p

fron/corr_old vs fron/corr_new -1.95 590 0.051

ocul/zygo_old vs ocul/zygo_new 6.85 700 <0.001

ocul/leva_old vs ocul/leva_new 4.01 709 <0.001

zygo/leva_old vs zygo/leva_new 3.93 774 <0.001

zygo/mass_old vs zygo/mass_new -0.59 772 0.552

oris/ment_old vs oris/ment_new -6.63 716 <0.001

oris/mass_old vs oris/mass_new -1.16 747 0.247

oris/zygo_old vs oris/zygo_new -2.80 731 0.005

corr/ment_old vs corr/ment_new -4.32 649 <0.001

Table 11. Results of the paired t-tests between new and old electrodes on the SVperc for

all muscle-pairs in the “<1 SD dataset”.


41

Figure 13 shows the SVdelta of all muscle-pairs for both electrode types in the “< 1SD

dataset”. Note that the SVdelta is significantly higher for the new electrodes in the

zygomaticus/masseter, oris/masseter and oris/zygomaticus muscle-pairs. The SVdelta turns

out to be higher for the old electrodes in the frontalis/corrugator, oculi/zygomaticus,

zygomaticus/levator and corrugator/mentalis muscle-pairs. The paired t-tests did not reveal

any differences in the SVdelta between old and new electrodes in the oculi/levator and

oris/mentalis muscle-pairs. Table 12 provides an overview of the performed paired t-tests on

the SVperc between old and new electrodes.

In addition, the DMV in the oris/mentalis muscle-pair has a positive value for new electrodes

and a negative value for old electrodes, and vice versa for the masseter/oris muscle pair. This

indicates that the muscle displaying preponderant activity differs between the two types of

electrodes. The difference in the DMVdelta between the two electrode types in the three

muscle-pair is statistically significant: t(1, 709) = -2.05, p = 0.041; t(714) = 3.83, p <0.001,

respectively.


42

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

fron/corr_O

fron/corr_N

ocul/zygo_O

ocul/zygo_N

ocul/leva_O

ocul/leva_N

zygo/leva_O

zygo/leva_N

zygo/mass_O

zygo/mass_N

oris/ment_O

oris/ment_N

oris/mass_O

oris/mass_N

oris/zygo_O

oris/zygo_N

corr/ment_O

corr/ment_N

SVdelta

Figure 13. SVdelta of all muscle-pairs for both electrode types in the “< 1SD dataset”.

Muscle-pair t df p

fron/corr_old vs fron/corr_new 4.00 614 <0.001




zygo/mass_old vs zygo/mass_new -2.72 762 0.007

oris/ment_old vs oris/ment_new 0.21 709 0.835

oris/mass_old vs oris/mass_new -5.48 714 <0.001

oris/zygo_old vs oris/zygo_new -4.66 705 <0.001

corr/ment_old vs corr/ment_new 5.52 627 <0.001

Table 12. Results of the paired t-tests between new and old electrodes on the SVdelta

for all muscle-pairs in the “<1 SD dataset”.


43

The signtest on SVperc in the “<1 SD dataset” (see table 13) indicates that the new electrodes

are more often characterized by a higher SVperc than the old electrodes in the oris/mentalis,

oris/zygomaticus and corrugator/mentalis muscle-pairs. The opposite holds for the

oculi/zygomaticus, oculi/levator, zygomaticus/levator muscle-pairs. No statistically

significant differences were found for the frontalis/corrugator, zygomaticus/masseter and


Muscle-

pair

N

(SV new>SV old)

N

(SV new<SV old)

N

total

observed p

(SV new>SV old) p

fron/corr 294 297 591 0.50 0.934

ocul/zygo 284 417 701 0.41 <0.001

ocul/leva 304 406 710 0.43 <0.001

zygo/leva 340 435 775 0.44 0.001

zygo/mass 399 374 773 0.52 0.388

oris/ment 424 293 717 0.59 <0.001

oris/mass 384 364 748 0.51 0.487

oris/zygo 398 334 732 0.54 0.020

corr/ment 364 286 650 0.56 0.003


pairs in the“<1 SD dataset”.

The signtest on SVdelta in the “<1 SD dataset” (see table 14) indicates that the new electrodes

are more often characterized by a higher SVperc than the old electrodes in the oris/masseter

and oris/zygomaticus muscle-pairs. The opposite holds for the frontalis/corrugator,

oculi/zygomaticus, oculi/levator, zygomaticus/levator and corrugator/mentalis muscle-pairs.

No statistically significant differences were found for the zygomaticus/masseter and

oris/mentalis muscle-pairs.


44

Muscle-

pair

N

(SV new>SV old)

N

(SV new<SV old)

N

total

observed p

(SV new>SV old) p

fron/corr 245 370 615 0.40 <0.001

ocul/zygo 323 394 717 0.45 0.009

ocul/leva 332 410 742 0.45 0.005

zygo/leva 332 444 776 0.43 <0.001

zygo/mass 407 356 763 0.53 0.070

oris/ment 358 352 710 0.50 0.851

oris/mass 392 323 715 0.45 0.011

oris/zygo 412 294 706 0.58 <0.001

corr/ment 262 366 628 0.42 <0.001


pairs in the “<1 SD dataset”.


45

Discussion

To test whether a reduction of the bipolar spacing results in an increase in spatial selectivity

of EMG recordings in the facial region a comparative study between two electrode types was

performed. EMG from 8 facial muscles was bilaterally recorded, rendering 16 EMG

electrode-pair sites in total. Twenty subjects viewed 48 pictures presented in series while the

EMG from the electrode-pair sites was recorded.

The MAV of the new electrodes was lower than the MAV of the old electrodes in all eight

muscle-pairs both in the baseline interval and in the active interval. This finding supports the

notion that a small bipolar spacing causes a decrease in amplitude of the EMG signal (e.g.

Loeb & Gans, 1986; Jonas et al., 1999; Zedka et al., 1997). Note that the two electrode types

differed in more ways than just bipolar spacing. For instance, it is not clear what the effect of

the shape of the contacts on the amplitude of the EMG signal was (compare e.g. De Luca,

1997 with Jonas et al., 1999).

Although the Selectivity Values (SV) differed significantly between the two electrode types in

many cases, there does not appear to be a general effect of electrode-type on selectivity as

measured by the SV. Whereas some muscles-pairs show a higher SV when recorded with new

electrodes, others show a higher SV when old electrodes are used (see table 15). In general,

the old electrodes seem to have higher SVs.

The length of the bar electrodes may be a disadvantage in small muscles. The contacts may

intersect non-target muscles as well. Furthermore, the selective effect of electrode orientation

in such closely spaced bar electrodes may be less outspoken due to the configuration of the

contacts. However, there are a number of other factors that could lead to the reported results.

Since the electrode parameters were equal in all muscles one could hypothesize that this

finding may be a result of physiological properties of the recording site. Since the SV is

calculated by subtracting the MAVsperc (or delta) from one muscle of the muscle-pair from

the other, the MAVsperc (or delta) of both muscles determine the SV. If the MAVperc (or

delta) of one of the muscles is relatively low compared to the other this results in a relatively

high SV. If the MAVsperc (or delta) of both muscles are comparable, the SV will be fairly

low. Bear in mind that if the MAV in the active interval does not differ much from the MAV

in the baseline interval, the MAVperc (or delta) of that muscle will be low. The MAVsperc

(or delta) are standardized and relative (i.e. compared to a baseline) measures and thus


46

account for the magnitude of the absolute amplitude. However, in the case of an electrode-

pair that is not capable of detecting a reliable myoelectric signal both the active MAV and the

baseline MAV may be low although the muscle could be more active in the active interval.

The depth of the active muscle fibers and the relative placement on the muscle may cause

such a poor pick-up (e.g. Loeb & Gans, 1986). This could result in a high SV or in a low SV

depending on the MAVperc (or delta) of the other muscle in the muscle-pair. Note that the

new electrodes are more prone to suboptimal recording and placement due to their

dimensions. This could also explain the differences in Dominant Muscle Value between the

two electrode types.

In general, the results of the signtests seem to coincide with the results of the t-tests indicating

that the reported differences are not due to outliers. However, note that there are differences

between the results of both tests (see table 15) pointing to a lack of robustness of the SV

concept.

Table 15 shows that the three distinct datasets differ in the SVold and SVnew. Since the

MAVperc (or delta) is a relative measure, the absolute amplitude of the EMG signal is not an

issue. Therefore, it is well possible to find a MAVperc (or delta) that is fairly high but is

derived from two MAVs that are so low that they could be considered error. The “> 1 SD

dataset” is therefore believed to be the most valid dataset. Furthermore, Solomonow et al.

(1994) stated that lower amplitude EMG yields much lower cross-talk in neighboring

muscles. The differences in selectivity between the two electrode types were therefore

expected to be more outspoken in the “> 1 SD dataset”. Table 15 shows that this latter

assumption does not seem to hold. Note that there are few consistent results within each

dataset for the different tests and quantification methods (i.e. perc or delta). It is not clear

which method of quantification leads to a better measure of selectivity. The differences again

point to a lack of robustness of the SV concept.


47

unconstraint dataset > 1 SD dataset < 1 SD dataset

t % t Δ s % s Δ t % t Δ s % s Δ t % t Δ s % s Δ

fron/corr n o . o n o n o n o . o

ocul/zygo o o o o . . . . o o o o

ocul/leva o . o o o . o o o . o o

zygo/leva o o o o o . o . o o o o

zygo/mass . . . . . . . . . n . .

oris/ment n . n . n . n . n . n .

oris/mass . n . . . . . . . n . n

oris/zygo n n n n . n . n n n n n

corr/ment n o n o n o n o n o n o

Tabel 15. Overview of the comparisons between new and old electrodes on SVperc

(denoted by “ %”) and SVdelta (denoted by “Δ” ) in the three distinct

datasets. Results on both t-tests (denoted by “t”) and signtests (denoted by

“s”) are presented. “n” reflects a higher SV for the new electrodes whereas

“o” reflects a higher SV for the old electrodes. A dot (“.”) indicates that the

old and new electrodes did not differ significantly on SV.

There are several reasons why the SV concept is not robust. Firstly, the SV is based on the

assumption that activity, which is present in both muscles of a muscle-pair can be considered

to be a result of reciprocal cross-talk. This does not have to be the case, as the significant

differences in SV between new and old electrodes in the corrugator/mentalis muscle-pair

indicate. Furthermore, the used method cannot account for cross-talk that stems from other

not-recorded muscles. This myoelectric signal may be picked up by a less selective electrode

pair and not by the selective electrode pair, thereby adding to the MAVperc (or delta) of the

non-selective electrode pair. This may result in a higher SV for the non-selective electrode

pair, for instance if a nearby non-recorded muscle is coactivated.

It could be argued that the results may be (partly) explained by accounting for inter-subject

variability. A pilot-analysis, however, revealed that the results of the analysis at subject-level

did not differ from the presented results.


48

Conclusions

The two electrode types yield different EMG signals (hypothesis I). A reduced bipolar

spacing results in a decrease of the overall amplitude of the EMG signal (hypothesis I and II).

This study revealed no general increase in selectivity by means of a reduced bipolar spacing

(contrary to hypothesis III). However, Van Boxtel et al. (1984) pointed out that volume

conduction is a complicating factor, which affects the validity of integrated EMG measures.

The SV is such an integrated measure and although its simplicity may seem appealing, it

presumably lacks the detail required for a reliable analysis of the extent of cross-talk in EMG

records. Therefore, the SV by itself does not seem to be a valid measure for determining the

selectivity of an EMG recording. Future analysis should focus on frequency analysis and

multimuscle cross-correlation. Both may provide more direct measures of selectivity than

integrated measures.


49

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54

Acknowledgements

I am indebted to the following people for their contributions to this paper:

Ton Aalbers

Bert Bastiaansen

John van den Beesen

Ton van Boxtel

Franc Donkers

Charles Rambelje


55

Appendix

Secondary goal and stimulus selection

Distinct affective states are presumed to be reflected by different facial expressions. The

secondary goal of this experiment is to determine which facial muscles are activated during

distinct affective states. This research question will be addressed in a later stage. To be able to

answer this question, it is necessary to determine the experienced affective state as accurately

as possible and to measure facial muscle activity reliably. Previous attempts are assumed to

be unreliable due to cross-talk (A. van Boxtel, personal communication, June 2000). The

experienced affective state is ascertained by asking the subjects to judge the pictures by

means of six different five-point scales ranging from “not at all” to “very strongly” (Hoekstra,

1986). Each scale centers round one affective state: happy, sad, anger, surprise, disgust and

fear. Although this classification is not intended to be omnifarious, these six affective states

are thought to be universal (e.g. Ekman & Friesen, 1978).

Since the experienced affective state would ideally be as archetypical (i.e. uncontaminated) as

possible, the pictures need to be selected with care. Hence, a picture that would elicit a

combination of affective states would lead to inconclusive results: the relationship between a

distinct affective state and the recorded muscle activity would remain unclear.

In order to create a dataset of pictures that were associated with only one affective state a pilot

study was performed. 24 Subjects rated 144 pictures from the IAPS dataset (Lang et al., 1999)

on the six scales described above. 48 pictures were selected: 7 slides of each category and 6

neutral slides. The following criteria were used to select suitable pictures:

1) level of differentiation:

a) the mean score of a picture on one category should be higher than the score

on the other 5 categories and this difference should be statistically significant;

b) when the difference between the categories is not significant the picture with

the least number of insignificant differences was chosen;

2) highest value:

c) if several pictures met criterium a, the picture with the highest value on the

category was chosen;


56

This procedure yielded 42 pictures. 6 Neutral stimuli were selected by choosing the pictures

with the lowest overall values. The following 48 pictures were shown in the physiological

study (*.bmp):

1300 3062 7150

1302 3063 7175

1313 3150 7211

1321 3168 7238

1463 3230 7325

1721 4599 7380

1750 4613 7705

1930 4621 8040

1931 5510 9102

2205 5760 9220

2550 6230 9320

2575 6243 9560

2700 6260 9561

2800 7025 9570

3000 7050 9800

3060 7080 9810

improving the selectivity of surface emg recordings of facial muscles: effects of electrode...

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