a zigbee-based ecg transmission for a low cost solution in home care services delivery

8/8/2019 A ZigBee-Based ECG Transmission for a Low Cost Solution in Home Care Services Delivery

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Mediterranean Journal of Pacing and Electrophysiology

A ZigBee-based ECG transmission for a low cost solution in home care services delivery

F. Vergari, V. Auteri, C. Corsi, C. Lamberti

Dipartimento di Elettronica, Informatica e Sistemistica (DEIS)

ALMA MATER STUDIORUM, Universita’ di Bologna

Viale Risorgimento, 2. 40136 BOLOGNA

Introduction

Telemedicine can make available the benefits of new technologies, especially information and

communications, in providing medical care. In particular it can promote international collaboration,

facilitate integration of eHealth in health systems, support interregional initiatives among groups of

countries that speak a common language, and document the best practices and report on them.

Home care provided in the patient's home is one of the main field in which telemedicine can effectively

change the way of providing health care. The availability of portable and communicant devices, services

and systems, is very useful for health purposes for filing, exchange and treatment of medical data, if

regulated by specific administrative, legal and ethical rules. It allows fast out-of-hospital assistance and

integrated services to elderly, sick, disabled, lonely citizens and support to the families.

Italian experience in telemedicine is very limited and primarily regards tele-consultation in radiology and

home care in selected patient populations. Only few application fields are spread all around the country,

such as 118, CUP and networks for organ transplantation. In 2006, Italian population counted 59 million

of people of which 14.1% between 0 and 14 years and 19.9% over 65 years. 35% of senior citizens lived

alone. In addition, in this environment, the citizen/patient's needs are changing since they want to be

more responsible of their own health care, acting as consumers, and they require painless and non-

invasive methods of diagnostic and treatments. In the face of these changes, home care services could

represent an efficient answer to these needs.

Heart disease is the main cause of early disability and premature death in western countries and its

incidence increases with age. Most of the cardiac deaths occur outside of the hospital and new

strategies are needed to reduce the time before treatment and to detect as early as possible the onset

of cardiac events. The ECG is the only useful diagnostic tool that is immediately available to assess the

probability of cardiac events. Therefore many studies have been focused in the design of a highly

http://en.wikipedia.org/wiki/Health_care

http://en.wikipedia.org/wiki/Patient

http://en.wikipedia.org/wiki/Home

http://en.wikipedia.org/wiki/Home

http://en.wikipedia.org/wiki/Patient

http://en.wikipedia.org/wiki/Health_care



intelligent, extremely friendly and easy to use, personal portable device for the early detection and

interpretation of ECG and the transmission of alarms to the relevant healthcare providers.

OLDES (Older People’s e-services at home) is an EU co-funded project under the IST Programme that

offers new technological solutions to improve the quality of life of older people, through the

development of a very low cost and easy to use entertainment and health care platform, designed to

ease the life of the elderly in their homes. The project aims: to improve the quality of life and health

conditions of the senior citizens (fragile/alone, or affected by pathologies); to keep them at their home

for longer, contributing in keeping them active; to guarantee a correct use of the social and health

services limiting the welfare costs. From a technological point of view, a new communication system

(based on a technological/computer sciences networks and on the local social resources), involving the

social sanitary services and the local social resources, has been proposed. The system monitors and

collects updated biological data, integrating in a single board a device for signal acquisition, processingand wireless communication (“motes”) in order to create a “Body Area Networks”: a varying number of

motes can acquire biological signals and complementary ones, transmit them to a remote “base station”

for the processing. The medical devices installed at the patient's home include a sphygmomanometer, a

digital scale, a coagulometer, a glucosimeter, a digital thermometer, a 1-lead ECG, a saturimeter and a

spirometer. These devices are connected to a “house concentrator”, a low cost pc, responsible for

acquisition, storage and transmission of sensors data to a central server (Figure 1). In case of alarm,

data are automatically transmitted from the server to healthcare providers or healthcare providers and

physicians, anytime, can connect to the server to check the patient’s status.

Figure 1. Medical devices selected for the OLDES project accomplishment



The most important feature of these devices is represented by the mean of interaction between the

patient and the whole system. Since the main users are elderly patients, it is necessary to simplify the

use of the computer and of the system itself. Mouse and keyboard have been replaced by a remotecontrol which is the only mean of interaction between the patient and the system: pressing conveniently

the buttons, the user controls all the system’s functionalities.

Materials and Methods

In this project, we realized a portable, wireless ZigBee based ECG monitoring device prototype. The

device is able to acquire, sample and transmit over the air a single lead ECG signal to a remote base

station (e.g. PC, laptop) in real time.

Considering the peculiar features of telemedicine, that is the absence of direct contact between thepatient and the physician and wireless connectivity, is fundamental for the development of efficient

remote monitoring systems in order to provide continuous, real-time and accurate information about

health conditions of the patient.

The availability of new low power, highly flexible wireless protocols paved the way for many innovative

applications in telemedicine, along with a series of new challenges and difficult design decisions.

For the choice of a reliable, robust and flexible transmission wireless protocol, some aspects must be

considered: battery life of remote nodes, data loss over the air, device pairing, limited range, ease of

network creation and maintenance, data relay over different nodes, multiple data incoming on the base

station at the same time. ZigBee is one of the most prominent wireless protocols that offers an efficient

relay protocol, good transmission range, flexible network structure (allowing various network

topologies) with emphasis on power consumption efficiency, supporting several “low power”

transmission modes which allow for higher autonomy and battery life. In Table 1, ZigBee protocol

features are compared with other transmission protocols. Using real time ECG waveform data is a good

“stress test” for this transmission protocol.



Table 1. Wireless protocol features

In Figure 2 the architecture of the ECG monitoring device prototype is shown.

Figure 2. Single lead ECG monitoring system architecture

The ECG signal is acquired through a single lead, amplified and filtered by an analog circuit and then

sampled by a low power microcontroller (TI MSP430F149) mounted on a Multi-Sensor-Board (developed

by Ducati Sistemi) that includes accelerometer, compass and GPS. Therefore data is transmitted over

the air using a ZigBee module (Telegesis ETRX1).

The system in its current version supports only a point to point network connection and the developed

MSP430 firmware allows the acquisition of either the ECG signal or data from the sensor array but not

all of them at the same time.

The base station is composed of a Telegesis ZigBee module connected to the PC through a UART to USB

transceiver form FTDI; the end terminal can be any computer equipped with a USB port and running an

operative system for which is compatible USB to UART FTDI driver. On the base station an application

reads the data stream from USB port applies some filtering and visualizes the real time ECG track on the

screen.

The data processing flow chain can be represented as shown in Figure 3.



Figure 3. Data processing flow chain

The analog circuit is kept very simple trying to minimize board space. The signal, acquired by a couple of

electrodes, is preconditioned trough capacitive coupling for blocking unwanted DC components and a

high frequency low pass passive filter in order to avoid the RF interference. The signal is then amplified

trough a low-power high CMRR instrumentation amplifier (AD623); after this, it is filtered with an active

low-pass filter at 17 Hz (that warrants a very clean signal, good enough for monitoring purposes) and

amplified in order to span the full range of the A/D converter. The global gain of the circuit is 750

allowing an input range of ± 2 mV (Figure 4).

Figure 4. Schematic description of the analog circuit

Following the analog circuit, the signal is sampled by the ADC of the MSP430F149 with a sampling

frequency of 500 Hz and a resolution of 12 bit. Double buffering is used to prevent data loss during

transmission; when a buffer is full, the bytes transmission starts and the sampling buffer is switched.

The microcontroller sends the samples trough an UART port to the ZigBee module that takes care of



sending data to the receiver (the “coordinator” in ZigBee terms). The ZigBee module also supports a

deep sleep mode in which power consumption is measured as low as a 2.3 mW ; therefore the relation

between the sampling rate, the buffer size and baud rate is very relevant in order to reduce as much as

possible the power consumption.

The coordinator receives the data sent by the ECG Monitor and processes them trough a custom built

.NET C# application that performs real-time visualization, QRS detection and computation of HRV

parameters. To perform the QRS detection, a modified Pan and Tompkins algorithm is used; first, the

signal is filtered by a pass-band filter; then, following a differentiation step, the absolute value is taken

and a running average is performed on the resulting signal. At this point, a dynamic threshold is

computed, considering half of the difference between the maximum and minimum of the signal in a

moving window lasting three seconds. The local maximum is finally identified on the original signal.

Once the RR time series has been acquired is then possible to display HR and HRV information (Figure 5).

Figure 5. A: ECG signal pre- (up) and post-processing (bottom); B: Final ECG signal and HR display; C: HRV

frequency analysis (left) and intervals histogram (middle), together with the HRV time domain measurements

(right)



Discussion and Conclusion

The aim of our project was to realize a wireless ECG monitoring device prototype, able to acquire,

sample and transmit a single lead ECG signal using a ZigBee protocol for its low-power functionalities.

In this system since power consumption is very influenced by the ETRX1 (75% of the total), there is a

wide gap between the system functioning with the radio module in transmission mode and in deep

sleep. The attempting to realize an optimized storing/transmission cycle in order to reduce the

consumption of power keeping Telegesis module in sleep mode as long as possible failed since, if too

many bytes are sent to the radio module too quickly, the module is not able to send all of them,

resulting in a data loss at the receiver end. Therefore, it was not possible to realize an optimized

store/sleep-store/send cycle as we intended to. To override this limitation some possible solutions are

available in order to reduce the amount of bytes to send to the transmission buffer: data compression

or motes local processing. A proprietary firmware for the ZigBee stack on the ETRX1 module is also analternative solution.

The test regarding module signal coverage was performed using two indicators of signal strength that

we can read by commands implemented in the firmware of Telegesis module: the Link Quality Indicator

(LQI) and the Received Signal Strength Indication (RSSI). We used the RSSI as the preferred indicator and

the results of our test are shown in Figure 6. As we expected, the RSSI is much stronger outdoor while

indoor the signal strength falls quickly; however the coverage is good enough to cover two or three

rooms depending on the walls thickness and the relative position of transmitter and receiver as shown.

Figure 6. Received Signal Strength Indicator (RSSI) test results, indoor (left) and outdoor (right)



Regarding ZigBee protocol, the flexibility and robustness of the network protocol should be investigated.

ZigBee strength lies in its ability to support a wide variety of network topologies: for continuous

monitoring (at home or hospital) the range and signal strength provided by a point-to-point connection

would not be adequate to provide full coverage of the environment; a network with a “sink” (the base

station), the sensor, and a number of “router” nodes would be an ideal set-up that should be tested.

Finally, the integration of information collected from various sensors on the Multi Sensor Board should

be investigated since it could provide additional information regarding the status of the patient, for

example the data from the accelerometer, together with the ECG signal, could allow the monitoring of

the subject’s activity.

In this study we proposed a solution based on an intelligent wireless personal ECG monitor that has

professional recording and processing capabilities on the house concentrator; it is concretely cost saving

and no specific infrastructure is required; healthcare providers are involved only if necessary andcommunications are based on standard external tools. The proposed solution is included in a complete

project, that represents a real example of how healthcare could become personalized, wearable,

ubiquitous moving from “how to treat patients” to “how to keep people healthy and prevent illness” ,

supporting healthy lifestyle, increasing emphasis on prevention instead of treatment, transferring the

secondary care to primary care (like in Scandinavian countries) and providing the basis for early

discharge, cheaper recovery and rehabilitation in home situation, improving access to service supplying

support at any time and place.

References

www.oldes.eu

www.istat.it

Telegesis, ETRX1-ETRX2 AT Commands Manual http://www.telegesis.com/pdf/Zigbee/TG-ETRX-

R211-Commands.pdf

Heart Rate Variability. Standards of measurements, physiological interpretation, and clinical use:

Task force of the European Society of Cardiology, and the North American Society of Pacing and

Electrophysiology, Circulation. 1996;93:1043 –1065.

J. Pan and W. J. Tompkins, A real-time QRS detection algorithm. IEEE Trans. Biomed. Eng., BME-

32 (3):230-236, 1985.

http://www.oldes.eu/


http://www.istat.it/






K. Srinivasan and P. Levis. Rssi is under appreciated. In Third Workshop on Embedded

Networked Sensors (EmNets 2006), May 30-31 2006 ACM 1-59593-9/06/0005, Stanford

University, 2006.

a zigbee-based ecg transmission for a low cost solution in home care services delivery

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