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Book ChapterDOI

Wearable ECG SoC for Wireless Body Area Networks: Implementation with Fuzzy Decision Making Chip

05 Oct 2015-pp 67-86
TL;DR: Small size and low power consumption show the effectiveness of the proposed design, suitable for wireless wearable ECG monitoring devices.
Abstract: The work aims to present an ultra-low power Electrocardiogram (ECG) on a chip with an integrated Fuzzy Decision Making (FDM) chip for Wireless Body Sensor Networks (WBSN) applications. The developed device is portable, wearable, long battery life, and small in size. The device comprises two designed chips, ECG System-on-Chip and Fuzzy Decision Maker chip. The ECG on-chip contains an analog front end circuit and a 12-bit SAR ADC for signal conditioning, a QRS detector, and relevant control circuitry and interfaces for processing. The analog ECG front-end circuits precisely measure and digitize the raw ECG signal. The QRS complex with a sampling frequency of 256 Hz is extracted after filtering. The extracted QRS details are sent to the decision maker chip, where abnormalities/anomalies in patient’s health are detected and an alert signal is sent to the patient via wireless communication protocol. The patient’s ECG data is wirelessly transmitted to a PC, using ZigBee or a mobile phone. The chip is prototyped and employed in a standard 0.35 µm CMOS process. The operating voltage of Static RAM and digital circuits and analog core circuits are 3.3 V and 1 V, respectively. The total area of the device is about 6 \( \text{cm}^{\text{2}} \) and consumes about 8.5 µW. Small size and low power consumption show the effectiveness of the proposed design, suitable for wireless wearable ECG monitoring devices.

Summary (3 min read)

1. Introduction

  • According to World Health Organization (WHO), cardiovascular and modern human behavior-related diseases are the major cause of mortality worldwide.
  • Wearable sensors/electrodes (deployment in accordance with the clinical application) collect the physiological signals for monitoring the patient’s health status.
  • To aid low cost, ultra-low power design is essential for developing wearable devices.

2. Prior Art

  • Wireless Body Area Network (WBAN) is the fundamental component of a wireless ECG monitoring system.
  • WBAN allows the integration of various other components, like intelligent systems, miniaturized components, low-power sensor nodes, etc.
  • For terrestrial and space applications, physiological parameters of the astronauts in space should be monitored continuously.
  • An integrated wireless ECG SoC for WBSN applications is proposed in [6], which comprises a two-channel ECG front-end, an 8-bit SAR-ADC, a simple micro- controller, a SRAM memory, and RF-transceivers.
  • This increases the need for low cost and easy to use wearable wireless ECG sensors with integrated decision making to alert personnel.

3.1 System Overview

  • The proposed health care architecture includes two parts: (a) Main unit and (b) Remote unit, as shown in Fig.2.
  • The remote unit (personal gateway) can be a mobile phone or a personal computer with an USB interface.
  • The main unit records the ECG from wearable textile electrodes and wirelessly transfers the data to a remote unit.
  • The Fuzzy Decision Making (FDM) chip (3×3 fuzzy controller; nine rules are accessible) takes decisions when necessary.
  • ZigBee protocol is chosen as a wireless communication protocol (TI CC2420) to provide reasonable power consumption and adequate data rate.

A. ECG Analog Front-end Amplifier

  • The ECG front-end amplifier is mainly responsible for noise suppression, signal conditioning, and amplification, which comprises two phases as shown in Fig.3, namely, low noise AFG with band pass function and a programmable gain amplifier (PGA) to amplify the acquired ECG signals (from textile electrodes), with amplitude in a few millivolts, adopting a flip-over-capacitor technique.
  • The Low noise amplifier not only acts as a preamplifier, but also acts as a band pass filter function with bandwidth between 0.3 and 100 Hertz.
  • In the AFG design, two switches (S1 and S2) are integrated to settle down quicker when power is applied, due to the large resistance by the pseudo-resistors.

B. Analog to Digital Converter (ADC)

  • Successive Approximation Register (SAR) ADC is chosen for this WBSN application because of its moderate accuracy and low power overhead.
  • Fig. 4 depicts the architecture of the SAR ADC, adopted from literature.
  • The analog ECG output is driven directly by the preceding buffer stage, without the need of an additional hold amplifier, sampled through a bootstrapped switch and held in the capacitive 12 bit DAC, and is then used by open-loop Sample/Hold.
  • The reason for open-loop Sample/Hold is to obtain low power, low cost, fast settling, and less offset error.
  • An on-chip crystal oscillator is used to drive the logic and timing sequence for achieving low power consumption and low jitter.

C. Heart Rate Calculation and QRS Detection

  • The morphological filter [8] is adopted to reduce the noise artifacts present in the ECG data and to detect\estimate the QRS complex details and R-R intervals.
  • The filter comprises a pair of Opening and Closing operations, using dilation and erosion operators, which suppress peaks and valleys.
  • The current threshold is updated regularly when a new Rpeak is identified.
  • By counting the number of clocks between R peaks using a binary counter, R-R interval is measured.
  • A parallel-to-serial converter is integrated with the wearable system for transmitting the HR variable through the SPI interface.

D. System Control Unit and SPI Interface

  • System Control Unit (SCU) is solely responsible for generating the interface control signals, based on the host or main controller commands for all the blocks in ECG on-chip.
  • In-order to interface the chip with various host CPUs, the System Control Unit uses an asynchronous FIFO with 8 Kb buffers.
  • Data from the ADC and QRS block is continuously written into the FIFO at the sampling frequency of 256Hz.
  • Based on the FIFO status, FIFO write/read controllers generate many status signals, which are “full”, “nearly full”, “empty”, and “nearly empty.”.
  • A microcontroller is employed externally to communicate with the proposed wearable device via a duplex SPI communication interface.

4. Results and Discussion

  • The wearable ECG sensor node system fits perfectly on a shirt.
  • The main unit provides a versatile framework for incorporating sensing, monitoring, and information processing devices.
  • The inference performance test is done, based on physical activity under various conditions.
  • The abnormal ECG signal is measured and stored in the fuzzy inference engine.
  • A wearable smart shirt transfers the physiological ECG signals over a wireless sensor network at the test.

4.1 ECG Acquisition

  • To ensure comfort, the clothing is designed from a knitted conductive textile fabric for reducing flammability.
  • The conductive textile fabric is realized from a blended yarn of the composite containing silver nanoparticles, which provide electrical conductivity of the yarn and the resultant knitted fabric.
  • The content of silver nanoparticles provides corrosion resistance of textile electrodes, antibacterial and anti-allergic properties, and mechanical and electrical stability when exposed to sweat.
  • The designed conductive textile fabrics are circular in shape, with dimensions 5 × 5 cm. Fig.12 shows the wearable electrodes, which comprise a conductive fabric electrode pair and the wearable sensor node system placed on the wearer’s chest placement.
  • To provide a sufficient potential difference, the electrodes are positioned 100 mm apart.

4.2 Performance Evaluation

  • The status is continuously sent to the remote unit every 2 minutes or preset time in the controller.
  • When the signal is sensed, the system detects the status, and if abnormal, an alert signal is transmitted.
  • Therefore, the proposed system can make decisions, based on the acquired ECG data.
  • Number of data sets used for testing Number of data sets correctly classified Number of data sets wrongly classified Accuracy (%) Drowsiness 89 82 7 92 Sleep Onset 102 98 4 96 Normal 213 213 0 100 Fig.14 depicts the designed graphical user interface for the proposed architecture.
  • Designed Graphical User Interface for testing and measurements.

5. Concluding remarks

  • A wireless ECG on a chip with an integrated Fuzzy Decision making system is proposed for real-time ECG health monitoring.
  • The proposed wearable device is small, user-friendly, has a long battery life, and is capable of wirelessly transmitting ECG data continuously to a remote station for detailed diagnosis.
  • The FDM chip is integrated with ECG on Chip to take the decisions for alerting the patients when necessary.
  • The designed FDM responds immediately when anomalies are found in ECG data.
  • The proposed device has already been tested with a reference high-quality measurement system for verification of accuracy and showed that the accuracy of the proposed device is good enough, and the variation in key ECG parameters obtained from the proposed device and the reference device is acceptable for clinical usage.

6. References

  • Manikandan Pandiyan, Geetha Mani, Jovitha Jerome, Natarajan Sivaraman.
  • Design of an analog CMOS fuzzy logic controller chip.

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Wearable ECG SoC for Wireless Body Area Networks:
Implementation with Fuzzy Decision Making Chip
Manikandan Pandiyan, Geetha Mani
To cite this version:
Manikandan Pandiyan, Geetha Mani. Wearable ECG SoC for Wireless Body Area Networks: Im-
plementation with Fuzzy Decision Making Chip. 23th IFIP/IEEE International Conference on Very
Large Scale Integration - System on a Chip (VLSI-SoC), Oct 2015, Daejeon, South Korea. pp.67-86,
�10.1007/978-3-319-46097-0_4�. �hal-01578609�

© VLSI SoC 2015
Wearable ECG SoC for Wireless Body Area Networks:
Implementation with Fuzzy Decision Making Chip
1
Manikandan Pandiyan,
2
Geetha Mani
1
Mercedes-Benz Research & Development India, Bangalore, INDIA
2
School of Electrical Engineering, Vellore Institute of Technology, Vellore, INDIA
vanajapandi@gmail.com, geethamr@gmail.com
Abstract. The work aims to present an ultra-low power Electrocardiogram (ECG)
on a chip with an integrated Fuzzy Decision Making (FDM) chip for Wireless Body
Sensor Networks (WBSN) applications. The developed device is portable, wearable,
long battery life, and small in size. The device comprises two designed chips, ECG
System-on-Chip and Fuzzy Decision Maker chip. The ECG on-chip contains an ana-
log front end circuit and a 12-bit SAR ADC for signal conditioning, a QRS detector,
and relevant control circuitry and interfaces for processing. The analog ECG front-
end circuits precisely measure and digitize the raw ECG signal. The QRS complex
with a sampling frequency of 256 Hz is extracted after filtering. The extracted QRS
details are sent to the decision maker chip, where abnormalities/anomalies in patient’s
health are detected and an alert signal is sent to the patient via wireless communica-
tion protocol. The patient’s ECG data is wirelessly transmitted to a PC, using ZigBee
or a mobile phone. The chip is prototyped and employed in a standard 0.35µm CMOS
process. The operating voltage of Static RAM and digital circuits and analog core
circuits are 3.3 Volts and 1 Volt, respectively. The total area of the device is about
6!"
#
and consumes about 8.5µW. Small size and low power consumption show the
effectiveness of the proposed design, suitable for wireless wearable ECG monitoring
devices.
1. Introduction
According to World Health Organization (WHO), cardiovascular and modern human
behavior-related diseases are the major cause of mortality worldwide. These types of
cardiovascular related-diseases, like Cardiac arrhythmias, Atrial fibrillation, and Cor-
onary heart diseases, can be monitored and controlled with continuous personal
healthcare supervision [1-2]. Electrocardiogram (ECG) embodies the cardiovascular
condition, therefore, is considered one of the most important human physiological
signals. In applying measurement of physiological signals for continuous monitoring,
patients usually cannot carry a bulky instrument, which restricts their mobility and
makes them uncomfortable, with so many electrodes and cables attached to their bod-
ies. Therefore, there is growing demand for a compact wearable ECG acquisition
system [2]. Wearable monitoring devices can record physiological variables, like

ECG, blood pressure, etc. for several hours and store them in the memory for future
use. The stored ECG data can then be utilized by clinicians or cardiologists for further
diagnosis.
Fig. 1. Graphical Illustration of wearable health care monitoring
The graphical embodiment of a wearable system for continuous remote monitoring
is illustrated in Fig.1. Wearable sensors/electrodes (deployment in accordance with
the clinical application) collect the physiological signals for monitoring the patient’s
health status. These wearable sensors continuously monitor vital signs, like heart rate
and blood pressure, when the patient with chronic heart disease is undergoing clinical
involvement. Wearable devices are also applied in home-based rehabilitation inter-
ventions for continuous personal health monitoring. Wireless protocols can be inte-
grated with wearable systems to facilitate long-term health monitoring for patients
diagnosed with cardiac diseases. The wireless communication is relied upon and used
to transmit the physiological data continuously to a central place (an access point or a
mobile) and to remote central (server or emergency centre) via internet. In emergency
situations, an alarm/alert signal can be transmitted to the remote emergency centre for
facilitating medical assistance to patients. Family members or clinicians are also
alarmed when the patient is in an emergency condition through the technology and
enabled to monitor the patient’s medical status continuously. Even though there are
advantages of wearable devices, many future challenges should be addressed. This

primarily requires the support of innovative sensor technologies, especially Wireless
Body Sensor Networks (WBSN), formed with various wearable biomedical sensors.
Since the constraints on battery life and form factor are crucial, these sensors have a
very stringent power requirement. To aid low cost, ultra-low power design is essential
for developing wearable devices. In terms of cost, size, and performance, System-on-
Chip (SoC) implementation is an attractive option.
In this chapter, the development and deployment of the wearable ECG SoC moni-
toring system are studied, regarding key technology perspective. The following sec-
tions present the prior art and essential components of wearable devices, System
overview, Proposed ECG SoC, and Fuzzy Decision Maker Chip. Concluding remarks,
observations, and future reservations are discussed in the final section.
2. Prior Art
Wireless Body Area Network (WBAN) is the fundamental component of a wireless
ECG monitoring system. WBAN allows the integration of various other components,
like intelligent systems, miniaturized components, low-power sensor nodes, etc.
Therefore, the combination of SoC concepts, wearable technology, Wireless Sensor
Network (WSN), and research in artificial intelligence produce novel approaches,
resulting in better health care services. System-on-a-chip (SoC) is a felicitous option
for device development because of its small size, low power consumption, and lower
cost features. Developing SoC for Wireless Body Area Network applications intends
to carry healthcare monitoring closer from clinical intervention to domiciles. It allows
physiological signal monitoring to be conducted more regularly than limiting it to
hospitals or clinics. WBSN is foreseen as the next generation health care monitoring
platform, as it is considered a reliable, low-cost high-patient-safety health care moni-
toring system. In recent years, the development of ECG SoC for WSBN applications
has attracted much attention [2,14]. A wearable monitoring system is proposed in [3]
to monitor various physiological variables, such as ECG, blood pressure, and temper-
ature. Also, the Global Positioning System (GPS) co-ordinates of patient or wearer
with the acquired variables are transmitted wirelessly to a remote station.
Targeting patients with chronic high-risk heart/respiratory diseases, a wrist worn
wearable medical monitoring and alert system (AMON) monitors physiological vari-
ables. For terrestrial and space applications, physiological parameters of the astro-
nauts in space should be monitored continuously. To address the mentioned problem,
a wearable system, called ‘Life Guard’, is proposed [4] to monitor the health status of
astronauts. The deployment of a biopatch with integrated low-power SoC prototype is
proposed by Yang et al. [5] to facilitate features, such as a three-stage front-end signal
conditioning circuit, 8-bit successive-approximation-register (SAR) ADC, and a digi-
tal core. An integrated wireless ECG SoC for WBSN applications is proposed in [6],
which comprises a two-channel ECG front-end, an 8-bit SAR-ADC, a simple micro-

controller, a SRAM memory, and RF-transceivers. Many ECG SoCs implementations
for WBSN applications employ a microcontroller or microprocessor to establish the
remote gateway [7,14]. In worst cases, there is a need for an artificial intelligence
approach, integrated with wearable ECG SoC, when abnormal ECG episodes are to
be detected instantly. This solution addresses diseases, like cardiac arrhythmia or
silent myocardial ischemia, to be easily identified for clinical treatment. This increas-
es the need for low cost and easy to use wearable wireless ECG sensors with integrat-
ed decision making to alert personnel. The following sections narrate about an ultra-
low power ECG on Chip with integrated CMOS Fuzzy Decision Making Chip that
addresses the issues in existing solutions.
3. Wearable ECG System: With Decision Making
3.1 System Overview
The proposed health care architecture includes two parts: (a) Main unit and (b)
Remote unit, as shown in Fig.2. The Main unit contains wearable textile electrodes,
designed ECG front-end chip, FDM chip, a controller, and a ZigBee transceiver. The
remote unit (personal gateway) can be a mobile phone or a personal computer with an
USB interface. The main unit records the ECG from wearable textile electrodes and
wirelessly transfers the data to a remote unit. The designed ECG acquisition chip for
low power use is described in the next sub-section. The ECG acquisition chip com-
prises: (1) specially designed textile electrodes for acquiring the ECG; (2) a miniature
printed circuit board with ECG front end circuits; (3) Analog to Digital Conversion
unit; (4) QRS Detection; and (4) System control unit. The ECG data is buffered, using
low power microcontroller internal memory to minimize power consumption before
wirelessly sending it to the remote unit. The main unit also performs the other tasks,
such as system initialization, data buffering, and scheduling wireless communication.
The Fuzzy Decision Making (FDM) chip (3×3 fuzzy controller; nine rules are acces-
sible) takes decisions when necessary. Depending on applications, control voltages set
on IC pins change the rules of fuzzy inference. The study of the Fuzzy chip is ex-
plained in detail in subsequent sections. ZigBee protocol is chosen as a wireless
communication protocol (TI CC2420) to provide reasonable power consumption and
adequate data rate. The prototype uses a low power TI MSP430 microcontroller for
data management, wireless ZigBee baseband, and routing management. The prototype
model is designed for patients, regarding comfort and ease of use, thus, not affecting
regular activities of patients. In addition, the entire unit is sealed within a smart textile
shirt. So, the patient can wear and remove it easily.

References
More filters
Journal ArticleDOI
01 Dec 2004
TL;DR: The AMON system includes continuous collection and evaluation of multiple vital signs, intelligent multiparameter medical emergency detection, and a cellular connection to a medical center, and is validated by a medical study with a set of 33 subjects.
Abstract: This paper describes an advanced care and alert portable telemedical monitor (AMON), a wearable medical monitoring and alert system targeting high-risk cardiac/respiratory patients. The system includes continuous collection and evaluation of multiple vital signs, intelligent multiparameter medical emergency detection, and a cellular connection to a medical center. By integrating the whole system in an unobtrusive, wrist-worn enclosure and applying aggressive low-power design techniques, continuous long-term monitoring can be performed without interfering with the patients' everyday activities and without restricting their mobility. In the first two and a half years of this EU IST sponsored project, the AMON consortium has designed, implemented, and tested the described wrist-worn device, a communication link, and a comprehensive medical center software package. The performance of the system has been validated by a medical study with a set of 33 subjects. The paper describes the main concepts behind the AMON system and presents details of the individual subsystems and solutions as well as the results of the medical validation.

747 citations

Journal ArticleDOI
TL;DR: The paper describes a prototype Smart Vest system used for remote monitoring of physiological parameters and the clinical validation of the data are presented.

384 citations

Journal ArticleDOI
01 Nov 2010
TL;DR: A novel healthcare IT platform developed under the LOBIN project, which allows monitoring several physiological parameters, such as ECG, heart rate, body temperature, etc., and tracking the location of a group of patients within hospital environments, is described.
Abstract: This paper describes a novel healthcare IT platform developed under the LOBIN project, which allows monitoring several physiological parameters, such as ECG, heart rate, body temperature, etc., and tracking the location of a group of patients within hospital environments. The combination of e-textile and wireless sensor networks provides an efficient way to support noninvasive and pervasive services demanded by future healthcare environments. This paper presents the architecture, system deployment as well as validation results from both laboratory tests and a pilot scheme developed with real users in collaboration with the Cardiology Unit at La Paz Hospital, Madrid, Spain.

150 citations

Journal ArticleDOI
TL;DR: First generation wearable long-term 14-day patch ECG monitors that attach directly to the skin and require no electrodes and wires to operate enables very long- term monitoring of critical patients while they are carrying out daily activities.
Abstract: Present day 24-h Holter monitors have been shown to miss many arrhythmias that may occur infrequently or under specific circumstances. The advancement in electronic and adhesive technologies have enabled the development of first generation wearable long-term 14-day patch ECG monitors that attach directly to the skin and require no electrodes and wires to operate. This new technology is unobtrusive to the patients and offers them unprecedented mobility. It enables very long-term monitoring of critical patients while they are carrying out daily activities. The monitors are waterproof, offer good adhesion to the skin and can operate as either recorders or wireless streaming devices.

90 citations

Journal ArticleDOI
TL;DR: Simulation tests show a good functionality of controller in response to some inputs to confirm the success of the design and the application of the system to the synthesis of a second-order system in a feedback loop is also considered.

64 citations


"Wearable ECG SoC for Wireless Body ..." refers methods in this paper

  • ...In fuzzy interface, three basic circuits are used: a ramp generator (RG) circuit [8], a minimum circuit, and a fuzzy complementary circuit....

    [...]

  • ...A novel defuzzifier is used [8,10] in which the center of the area is...

    [...]

  • ...The ECG samples are loaded serially into the shift register and then added/subtracted (for dilation/erosion respectively) with the structure element g(x) [8]....

    [...]

  • ...The morphological filter [8] is adopted to reduce the noise artifacts present in the ECG data and to detect\estimate the QRS complex details and R-R intervals....

    [...]

  • ...Level shifter circuit (LSC) is used to compensate offset voltage [8]....

    [...]

Frequently Asked Questions (24)
Q1. What contributions have the authors mentioned in the paper "Wearable ecg soc for wireless body area networks: implementation with fuzzy decision making chip" ?

The work aims to present an ultra-low power Electrocardiogram ( ECG ) on a chip with an integrated Fuzzy Decision Making ( FDM ) chip for Wireless Body Sensor Networks ( WBSN ) applications. 

In fuzzy interface, three basic circuits are used: a ramp generator (RG) circuit [8], a minimum circuit, and a fuzzy complementary circuit. 

The content of silver nanoparticles provides corrosion resistance of textile electrodes, antibacterial and anti-allergic properties, and mechanical and electrical stability when exposed to sweat. 

According to World Health Organization (WHO), cardiovascular and modern human behavior-related diseases are the major cause of mortality worldwide. 

Power Spectral Density of HR variations is calculated, and the three frequency bands, such as Very low frequencies (VLF: 0-0.04 Hz), Low frequencies (LF: 0.04-0.15 Hz), and High frequencies (HF: 0.15-0.5 Hz), have been utilized. 

ZigBee protocol is chosen as a wireless communication protocol (TI CC2420) to provide reasonable power consumption and adequate data rate. 

The prototype model is designed for patients, regarding comfort and ease of use, thus, not affecting regular activities of patients. 

System Control Unit (SCU) is solely responsible for generating the interface control signals, based on the host or main controller commands for all the blocks in ECG on-chip. 

Rectangles of electrically conductive textile fabric in knitted design were stitched on the position of the pectoral muscles [13]. 

Developing SoC for Wireless Body Area Network applications intends to carry healthcare monitoring closer from clinical intervention to domiciles. 

The main idea is based on parallel conductances 𝑔\\, stating implicitly that the output voltage of the defuzzifier circuit is the average value of the inputs. 

An integrated wireless ECG SoC for WBSN applications is proposed in [6], which comprises a two-channel ECG front-end, an 8-bit SAR-ADC, a simple micro-controller, a SRAM memory, and RF-transceivers. 

Thisprimarily requires the support of innovative sensor technologies, especially Wireless Body Sensor Networks (WBSN), formed with various wearable biomedical sensors. 

The controller architecture in Fig. 6 is constructed with CMOS components, such as Membership function generator (MFG), MIN circuits and a defuzzifier (D blocks) circuit. 

Designed Graphical User Interface for testing and measurementsA wireless ECG on a chip with an integrated Fuzzy Decision making system is proposed for real-time ECG health monitoring. 

a Fuzzy Classifier chip meets the critical requirements of medical applications: no delay in response, reliable, high-safety, and low cost. 

The ECG front-end amplifier is mainly responsible for noise suppression, signal conditioning, and amplification, which comprises two phases as shown in Fig.3, namely, low noise AFG with band pass function and a programmable gain amplifier (PGA) to amplify the acquired ECG signals (from textile electrodes), with amplitude in a few millivolts, adopting a flip-over-capacitor technique. 

The features extracted from HRV and PSD are used to feed the fuzzy logic engine that computes epoch-by-epoch (30 or 60 seconds per period) inferences. 

The ECG samples are loaded serially into the shift register and then added/subtracted (for dilation/erosion respectively) with the structure element g(x) [8]. 

The impacts of wandering baseline drift are eradicated by subtracting the mean result of operations (opening and closing) with the original input. 

In applying measurement of physiological signals for continuous monitoring, patients usually cannot carry a bulky instrument, which restricts their mobility and makes them uncomfortable, with so many electrodes and cables attached to their bodies. 

Electrocardiogram (ECG) embodies the cardiovascular condition, therefore, is considered one of the most important human physiological signals. 

This increases the need for low cost and easy to use wearable wireless ECG sensors with integrated decision making to alert personnel. 

the combination of SoC concepts, wearable technology, Wireless Sensor Network (WSN), and research in artificial intelligence produce novel approaches, resulting in better health care services.