The purpose of the Evaluating ECG capturing using sound-card of PC/Laptop is provided portable and low
cost ECG monitoring system using laptop and mobile phones. There is no need to interface microcontroller
or any other device to transmit ECG data. This research is based on hardware design,
implementation, signal capturing and Evaluation of an ECG processing and analyzing system which attend
the physicians in heart disease diagnosis. Some important modification is given in design part to avoid all
definitive ECG instrument problems faced in previous designs. Moreover, attenuate power frequency noise
and noise that produces from patient's body have required additional developments. The hardware design
has basically three units: transduction and conditioning Unit, interfacing unit and data processing unit.
The most focusing factor is the ECG signal/data transmits in laptop/PC via microphone pin. The live
simulation is possible using SOUNDSCOPE software in PC/Laptop. The software program that is written
in MATLAB and LAB-View performs data acquisition (record, stored, filtration) and several tasks such as
QRS detection, calculate heart rate.
International Journal of Computational Engineering Research(IJCER) ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Classification and Detection of ECG-signals using Artificial Neural NetworksGaurav upadhyay
Electrocardiogram (ECG), a noninvasive technique is used as a primary diagnostic tool for
cardiovascular diseases. A cleaned ECG signal provides necessary information about the
electrophysiology of the heart diseases and ischemic changes that may occur. It provides
valuable information about the functional aspects of the heart and cardiovascular system. The
objective of the thesis is to automatic detection of cardiac arrhythmias in ECG signal.
Recently developed digital signal processing and pattern reorganization technique is used in
this thesis for detection of cardiac arrhythmias. The detection of cardiac arrhythmias in the
ECG signal consists of following stages: detection of QRS complex in ECG signal; feature
extraction from detected QRS complexes; classification of beats using extracted feature set
from QRS complexes. In turn automatic classification of heartbeats represents the automatic
detection of cardiac arrhythmias in ECG signal. Hence, in this thesis, we developed the
automatic algorithms for classification of heartbeats to detect cardiac arrhythmias in ECG
signal.QRS complex detection is the first step towards automatic detection of cardiac
arrhythmias in ECG signal. A novel algorithm for accurate detection of QRS complex in ECG
signal peak classification approach is used in ECG signal for determining various diseases . As
known the amplitudes and duration values of P-Q-R-S-T peaks determine the functioning of
heart of human. Therefore duration and amplitude of all peaks are found. R-R and P-R
intervals are calculated. Finally, we have obtained the necessary information for disease
detection .For detection of cardiac arrhythmias; the extracted features in the ECG signal will
be input to the classifier. The extracted features contain morphological l features of each
heartbeat in the ECG signal. This project is implemented by using MATLAB software. An
interface was created to easily select and process the signal. “.dat” format is used the for ECG
signal data. We have detected bradycardia and tachycardia. Massachusetts Institute of
Technology Beth Israel Hospital (MIT-BIH) arrhythmias database has been used for
performance analysis.
Acquiring Ecg Signals And Analysing For Different Heart AilmentsIJERA Editor
This paper describes and focuses on acquiring and identification of cardiac diseases using ECG waveform in LabVIEW software, which would bridge the gap between engineers and medical physicians. This model work collects the waveform of an affected person. The waveform is analyzed for diseases and then a report is sent to the doctor through mail. Initially the waveforms are collected from the person using EKG sensor with the help of surface electrodes and the hardware controlled by MCU C8051, acquires ECG and also Phonocardiogram (PCG) synchronously and the waveform is sent to the PC installed with LabVIEW software through DAQ-6211. The waveform in digital format is saved and sent to the loops containing conditions for different diseases. If the waveform parameters coincide with any of the looping statements, particular disease is indicated. Simultaneously the patient PCG report is also collected in a separate database containing all information, which will be sent to the doctor through mail.
A Wireless ECG Plaster for Real-Time Cardiac Health Monitoring in Body Senso...ecgpapers
In this paper we present a wireless ECG plaster
that can be used for real-time monitoring of ECG in cardiac
patients. The proposed device is light weight (25 grams),
wearable and can wirelessly transmit the patient’s ECG signal to
mobile phone or PC using ZigBee. The device has a battery life of
around 26 hours while in continuous operation, owing to the
proposed ultra-low power ECG acquisition front end chip. The
prototype has been verified in clinical trials.
International Journal of Computational Engineering Research(IJCER) ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Classification and Detection of ECG-signals using Artificial Neural NetworksGaurav upadhyay
Electrocardiogram (ECG), a noninvasive technique is used as a primary diagnostic tool for
cardiovascular diseases. A cleaned ECG signal provides necessary information about the
electrophysiology of the heart diseases and ischemic changes that may occur. It provides
valuable information about the functional aspects of the heart and cardiovascular system. The
objective of the thesis is to automatic detection of cardiac arrhythmias in ECG signal.
Recently developed digital signal processing and pattern reorganization technique is used in
this thesis for detection of cardiac arrhythmias. The detection of cardiac arrhythmias in the
ECG signal consists of following stages: detection of QRS complex in ECG signal; feature
extraction from detected QRS complexes; classification of beats using extracted feature set
from QRS complexes. In turn automatic classification of heartbeats represents the automatic
detection of cardiac arrhythmias in ECG signal. Hence, in this thesis, we developed the
automatic algorithms for classification of heartbeats to detect cardiac arrhythmias in ECG
signal.QRS complex detection is the first step towards automatic detection of cardiac
arrhythmias in ECG signal. A novel algorithm for accurate detection of QRS complex in ECG
signal peak classification approach is used in ECG signal for determining various diseases . As
known the amplitudes and duration values of P-Q-R-S-T peaks determine the functioning of
heart of human. Therefore duration and amplitude of all peaks are found. R-R and P-R
intervals are calculated. Finally, we have obtained the necessary information for disease
detection .For detection of cardiac arrhythmias; the extracted features in the ECG signal will
be input to the classifier. The extracted features contain morphological l features of each
heartbeat in the ECG signal. This project is implemented by using MATLAB software. An
interface was created to easily select and process the signal. “.dat” format is used the for ECG
signal data. We have detected bradycardia and tachycardia. Massachusetts Institute of
Technology Beth Israel Hospital (MIT-BIH) arrhythmias database has been used for
performance analysis.
Acquiring Ecg Signals And Analysing For Different Heart AilmentsIJERA Editor
This paper describes and focuses on acquiring and identification of cardiac diseases using ECG waveform in LabVIEW software, which would bridge the gap between engineers and medical physicians. This model work collects the waveform of an affected person. The waveform is analyzed for diseases and then a report is sent to the doctor through mail. Initially the waveforms are collected from the person using EKG sensor with the help of surface electrodes and the hardware controlled by MCU C8051, acquires ECG and also Phonocardiogram (PCG) synchronously and the waveform is sent to the PC installed with LabVIEW software through DAQ-6211. The waveform in digital format is saved and sent to the loops containing conditions for different diseases. If the waveform parameters coincide with any of the looping statements, particular disease is indicated. Simultaneously the patient PCG report is also collected in a separate database containing all information, which will be sent to the doctor through mail.
A Wireless ECG Plaster for Real-Time Cardiac Health Monitoring in Body Senso...ecgpapers
In this paper we present a wireless ECG plaster
that can be used for real-time monitoring of ECG in cardiac
patients. The proposed device is light weight (25 grams),
wearable and can wirelessly transmit the patient’s ECG signal to
mobile phone or PC using ZigBee. The device has a battery life of
around 26 hours while in continuous operation, owing to the
proposed ultra-low power ECG acquisition front end chip. The
prototype has been verified in clinical trials.
Heart rate detection using hilbert transformeSAT Journals
Abstract The electrocardiogram (ECG) is a well known method that can be used to measure Heart Rate Variability (HRV). This paper describes a procedure for processing electrocardiogram signals (ECG) to detect Heart Rate Variability (HRV). In recent years, there have been wide-ranging studies on Heart rate variability in ECG signals and analysis of Respiratory Sinus Arrhythmia (RSA). Normally the Heart rate variability is studied based on cycle length variability, heart period variability, RR variability and RR interval tachogram. The HRV provides information about the sympathetic-parasympathetic autonomic stability and consequently about the risk of unpredicted cardiac death. The heart beats in ECG signal are detected by detecting R-Peaks in ECG signals and used to determine useful information about the various cardiac abnormalities. The temporal locations of the R-wave are identified as the locations of the QRS complexes. In the presence of poor signal-to-noise ratios or pathological signals and wrong placement of ECG electrodes, the QRS complex may be missed or falsely detected and may lead to poor results in calculating heart beat in turn inter-beat intervals. We have studied the effects of number of common elements of QRS detection methods using MIT/BIH arrhythmia database and devised a simple and effective method. In this method, first the ECG signal is preprocessed using band-pass filter; later the Hilbert Transform is applied on filtered ECG signal to enhance the presence of QRS complexes, to detect R-Peaks by setting a threshold and finally the RR-intervals are calculated to determine Heart Rate. We have implemented our method using MATLAB on ECG signal which is obtained from MIT/BIH arrhythmia database. Our MATLAB implementation results in the detection of QRS complexes in ECG signal, locate the R-Peaks, computes Heart Rate (HR) by calculating RR-internal and plotting of HR signal to show the information about HRV. Index Terms: ECG, QRS complex, R-Peaks, HRV, Heart Rate signal, RSA, Hilbert Transform, Arrhythmia, MIT/BIH, MATLAB and Lynn’s filters
The basics of the biomedical equipments, ECG, EMG, EEG, Pace maker, Defibrillator, Lasik, Robotics Surgery, ICU, Bio-Telemetry system, Plasma Medicine, etc are discussed and the video link of the topics are also given.
Identification of Myocardial Infarction from Multi-Lead ECG signalIJERA Editor
Electrocardiogram (ECG) is the cheap and noninvasive method of depicting the heart activity and abnormalities.
It provides information about the functionality of the heart. It is the record of variation of bioelectric potential
with respect to time as the human heart beats. The classification of ECG signals is an important application since
the early detection of heart diseases/abnormalities can prolong life and enhance the quality of living through
appropriate treatment. Since the ECG signals, while recording are contaminated by several noises it is necessary
to preprocess the signals prior to classification. Digital filters are used to remove noise from the signal. Principal
component analysis is applied on the 12 lead signal to extract various features. The present paper shows the
unique feature, point score calculated on the basis of the features extracted from the ECG signal. The point
score calculation is tested for 40 myocardial infarction ECG signals and 25 Normal ECG signals from the PTB
Diagnostic database with 94% sensitivity.
Classification of Arrhythmia from ECG Signals using MATLABDr. Amarjeet Singh
An Electrocardiogram (ECG) is defined as a test
that is performed on the heart to detect any abnormalities in
the cardiac cycle. Automatic classification of ECG has
evolved as an emerging tool in medical diagnosis for effective
treatments. The work proposed in this paper has been
implemented using MATLAB. In this paper, we have
proposed an efficient method to classify the ECG into normal
and abnormal as well as classify the various abnormalities.
To brief it, after the collection and filtering the ECG signal,
morphological and dynamic features from the signal were
obtained which was followed by two step classification
method based on the traits and characteristic evaluation.
ECG signals in this work are collected from MIT-BIH, AHA,
ESC, UCI databases. In addition to this, this paper also
provides a comparative study of various methods proposed
via different techniques. The proposed technique used helped
us process, analyze and classify the ECG signals with an
accuracy of 97% and with good convenience.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
Cardiac Pacemakers: Function,
Troubleshooting, and Management
Part 1 of a 2-Part Series
Siva K. Mulpuru, MD, Malini Madhavan, MBBS, Christopher J. McLeod, MBCHB, PHD, Yong-Mei Cha, MD,
Paul A. Friedman, MD
Population with pacemaker implants varies by age, sex or race and it is used when heart
beats too slowly or when there is irregularity in the beating or there is blockage. Artificial cardiac
pacemaker is a medical device that uses electrical impulses delivered by electrodes contracting the
heart muscles in order to regulate the beating of the heart. This paper presents an integrated fail safe
pacemaker which will produces the artificial pulse whenever the missed pulse in being produced by
the heart. Unit will function as an advanced dual chamber pacemaker type that can pace both atrium
and ventricle and hence functions like a normal heart. The device will monitor the electrical activities
of the heart through the cardiac signal ECG of the patient. Device status and vital parameters can be
monitored using Bluetooth wireless communication and displayed on an Android Platform.
Portable ECG Monitoring System using Lilypad And Mobile Platform-PandaBoardIJSRD
New wireless system for biomedical purposes gives new possibilities for monitoring of essential function in human being. Wearable biomedical sensors will give the patient the freedom to be capable of moving readily and still be under continuously monitoring regularity of heartbeats identify any damage to the heart and devices used to regulate the heart and thereby to better quality of patient care. This paper describes a new concept for wireless and portable electrocardiogram (ECG) sensor transmitting signals to a monitoring station at the remote location within specific range, and this concept is intended for monitoring people with impairments in their cardiac activity. The proposed work helps to overcome this problem. With the advancement in Arduino and mobile technology, it is possible to design a portable ECG device which capture ECG of patient and monitor it on mobile platform. This report goes over low power Arduino, mobile platform Panda board and Zigbee technology to couple ECG over mobile board.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Heart rate detection using hilbert transformeSAT Journals
Abstract The electrocardiogram (ECG) is a well known method that can be used to measure Heart Rate Variability (HRV). This paper describes a procedure for processing electrocardiogram signals (ECG) to detect Heart Rate Variability (HRV). In recent years, there have been wide-ranging studies on Heart rate variability in ECG signals and analysis of Respiratory Sinus Arrhythmia (RSA). Normally the Heart rate variability is studied based on cycle length variability, heart period variability, RR variability and RR interval tachogram. The HRV provides information about the sympathetic-parasympathetic autonomic stability and consequently about the risk of unpredicted cardiac death. The heart beats in ECG signal are detected by detecting R-Peaks in ECG signals and used to determine useful information about the various cardiac abnormalities. The temporal locations of the R-wave are identified as the locations of the QRS complexes. In the presence of poor signal-to-noise ratios or pathological signals and wrong placement of ECG electrodes, the QRS complex may be missed or falsely detected and may lead to poor results in calculating heart beat in turn inter-beat intervals. We have studied the effects of number of common elements of QRS detection methods using MIT/BIH arrhythmia database and devised a simple and effective method. In this method, first the ECG signal is preprocessed using band-pass filter; later the Hilbert Transform is applied on filtered ECG signal to enhance the presence of QRS complexes, to detect R-Peaks by setting a threshold and finally the RR-intervals are calculated to determine Heart Rate. We have implemented our method using MATLAB on ECG signal which is obtained from MIT/BIH arrhythmia database. Our MATLAB implementation results in the detection of QRS complexes in ECG signal, locate the R-Peaks, computes Heart Rate (HR) by calculating RR-internal and plotting of HR signal to show the information about HRV. Index Terms: ECG, QRS complex, R-Peaks, HRV, Heart Rate signal, RSA, Hilbert Transform, Arrhythmia, MIT/BIH, MATLAB and Lynn’s filters
The basics of the biomedical equipments, ECG, EMG, EEG, Pace maker, Defibrillator, Lasik, Robotics Surgery, ICU, Bio-Telemetry system, Plasma Medicine, etc are discussed and the video link of the topics are also given.
Identification of Myocardial Infarction from Multi-Lead ECG signalIJERA Editor
Electrocardiogram (ECG) is the cheap and noninvasive method of depicting the heart activity and abnormalities.
It provides information about the functionality of the heart. It is the record of variation of bioelectric potential
with respect to time as the human heart beats. The classification of ECG signals is an important application since
the early detection of heart diseases/abnormalities can prolong life and enhance the quality of living through
appropriate treatment. Since the ECG signals, while recording are contaminated by several noises it is necessary
to preprocess the signals prior to classification. Digital filters are used to remove noise from the signal. Principal
component analysis is applied on the 12 lead signal to extract various features. The present paper shows the
unique feature, point score calculated on the basis of the features extracted from the ECG signal. The point
score calculation is tested for 40 myocardial infarction ECG signals and 25 Normal ECG signals from the PTB
Diagnostic database with 94% sensitivity.
Classification of Arrhythmia from ECG Signals using MATLABDr. Amarjeet Singh
An Electrocardiogram (ECG) is defined as a test
that is performed on the heart to detect any abnormalities in
the cardiac cycle. Automatic classification of ECG has
evolved as an emerging tool in medical diagnosis for effective
treatments. The work proposed in this paper has been
implemented using MATLAB. In this paper, we have
proposed an efficient method to classify the ECG into normal
and abnormal as well as classify the various abnormalities.
To brief it, after the collection and filtering the ECG signal,
morphological and dynamic features from the signal were
obtained which was followed by two step classification
method based on the traits and characteristic evaluation.
ECG signals in this work are collected from MIT-BIH, AHA,
ESC, UCI databases. In addition to this, this paper also
provides a comparative study of various methods proposed
via different techniques. The proposed technique used helped
us process, analyze and classify the ECG signals with an
accuracy of 97% and with good convenience.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
Cardiac Pacemakers: Function,
Troubleshooting, and Management
Part 1 of a 2-Part Series
Siva K. Mulpuru, MD, Malini Madhavan, MBBS, Christopher J. McLeod, MBCHB, PHD, Yong-Mei Cha, MD,
Paul A. Friedman, MD
Population with pacemaker implants varies by age, sex or race and it is used when heart
beats too slowly or when there is irregularity in the beating or there is blockage. Artificial cardiac
pacemaker is a medical device that uses electrical impulses delivered by electrodes contracting the
heart muscles in order to regulate the beating of the heart. This paper presents an integrated fail safe
pacemaker which will produces the artificial pulse whenever the missed pulse in being produced by
the heart. Unit will function as an advanced dual chamber pacemaker type that can pace both atrium
and ventricle and hence functions like a normal heart. The device will monitor the electrical activities
of the heart through the cardiac signal ECG of the patient. Device status and vital parameters can be
monitored using Bluetooth wireless communication and displayed on an Android Platform.
Portable ECG Monitoring System using Lilypad And Mobile Platform-PandaBoardIJSRD
New wireless system for biomedical purposes gives new possibilities for monitoring of essential function in human being. Wearable biomedical sensors will give the patient the freedom to be capable of moving readily and still be under continuously monitoring regularity of heartbeats identify any damage to the heart and devices used to regulate the heart and thereby to better quality of patient care. This paper describes a new concept for wireless and portable electrocardiogram (ECG) sensor transmitting signals to a monitoring station at the remote location within specific range, and this concept is intended for monitoring people with impairments in their cardiac activity. The proposed work helps to overcome this problem. With the advancement in Arduino and mobile technology, it is possible to design a portable ECG device which capture ECG of patient and monitor it on mobile platform. This report goes over low power Arduino, mobile platform Panda board and Zigbee technology to couple ECG over mobile board.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Right-Leg-Driven Circuit and Instrumentation Amplifier in ECG Acquisition SystemJewel Haque
In an ECG (Electrocardiogram) acquisition system, instrumentation amplifiers are commonly used to amplify the small electrical signals generated by the heart and reject common-mode noise. The term "Right-Leg-Driven Circuit" (RLD) is a technique used to improve the common-mode rejection ratio (CMRR) in instrumentation amplifiers, specifically in ECG applications where high CMRR is crucial for accurate signal acquisition.
Here's an overview of how a Right-Leg-Driven Circuit and an Instrumentation Amplifier are used in an ECG acquisition system:
Instrumentation Amplifier (IA):
An Instrumentation Amplifier is a differential amplifier with high input impedance and high common-mode rejection capability. It amplifies the voltage difference between two input terminals (ECG electrodes in this case) while rejecting any common-mode signals (such as interference or noise) that are present on both input terminals.
The IA typically consists of three operational amplifiers (Op-Amps) configured to provide the desired amplification and filtering.
Right-Leg-Driven Circuit (RLD):
The Right-Leg-Driven Circuit is a technique used to reduce the common-mode voltage at the patient's right leg electrode. This is important because the reference electrode (usually the right leg electrode) should ideally have a common-mode voltage close to the patient's common-mode voltage to ensure accurate ECG measurements and patient safety.
RLD works by actively driving the right leg electrode to match the common-mode voltage of the patient. This is usually done using an auxiliary electrode placed on the patient's right leg and a feedback loop to maintain the voltage at the right leg electrode close to the patient's common-mode voltage.
The RLD circuit is connected to one of the inputs of the instrumentation amplifier to effectively subtract the common-mode voltage from the ECG signal, further improving CMRR.
The combined use of an Instrumentation Amplifier and a Right-Leg-Driven Circuit helps achieve high common-mode rejection and accurate ECG signal acquisition by:
Amplifying the small differential ECG signal.
Rejecting common-mode noise and interference.
Reducing the common-mode voltage at the right leg electrode to minimize the risk of electrical shock to the patient and to ensure accurate measurements.
ECG acquisition systems are critical for monitoring heart health, and these techniques are essential to obtain reliable and accurate ECG waveforms while maintaining patient safety by minimizing common-mode voltage differences. Implementing such systems requires careful design and consideration of electrode placement, amplifier characteristics, and signal processing techniques to achieve optimal performance.
DENOISING OF ECG SIGNAL USING FILTERS AND WAVELET TRANSFORMIJEEE
This paper presents a comparison of methods for denoising the Electrocardiogram signal. The methods are applied on
MIT-BIH arrhythmia database and implemented using MATLAB software.
A Wireless Methodology of Heart Attack Detectionijsrd.com
The wrist watch with Heart Attack Detection is equipment that is used daily to indicate heart condition, to detect heart attack and to call for emergency help. It was designed specially to help patients with heart disease.This includes three common sub units. They are Circuit, Analysis Algorithm, and Bluetooth Communication. The first one is to wear on the wrist of the patient to captures the abnormal heart beat waves from the victim and the alternate methods are installed under the stick. This project is based on the previous project “Wireless Heart Attack Detector with GPS†of Fall 2004 [1]. we consider a big improvement in reducing the complexity of the project greatly, in saving power consumption of the project to run much fewer codes and in making the project to run at a faster time. No wire is attached to the wrists. In our project, the ECG waveform is transmitted wirelessly from the wrists to the watch. This gives the user great flexibility while the program is switched on and running. User can drive safely, can use restroom easily and can function normally like without the project. Previous project had the wire connection. All the hardware on the walking watch would have been strapped to the wrists. This will not make the project functional and marketable. Our project is completely portable. Heart condition is displayed in our project. The previous project did not inform the user about his heart condition. We display the heart condition through two LEDs as low-risk (alert level between 4 and 6) and high risk (alert level between 7 and 9). The user can know their heart condition and take proper action to avoid the fatal moment. Proper action could be slowing down and taking a rest.
Project Report on ECG Transmitter using Agilent ADS (Advance System Design)Manu Mitra
In 1996, Intellidesign Pty Ltd (then IntelliMed) was approached by a cardiologist to design an ECG Holter monitor. This original device was a two or three lead, single channel ECG device, which could continuously record for a maximum of one hour. Additionally, the device had Polar Chest Strap capabilities for the added functionality as a Heart Rate monitor. The device could operate in four different modes: 1-hour ECG Recording Mode, in which the device would record one continuous hour of near diagnostic quality ECG trace during exercise; Event Recording Mode, in which the device would record up to 60, one minute segments around a recorded event, over a period of up to 24 hours; Heart rate Recording Mode, in which the unit would have the capacity to record up to 24 hours of heart rate information; and ECG Telemetry Mode, in which the unit would transmit, via a Radio Frequency (RF) link, a real-time ECG signal to a receiver unit. The purpose of this project is to design ECG transmitter using the software Agilent ADS.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
An Electrocardiograph based Arrythmia Detection SystemDr. Amarjeet Singh
Cardiac disorders turn out to be a serious disease if
not diagnosed and treated at the earliest. Arrhythmia is a
cardiac disorder that exists as a result of irregular heart beat
conditions. There are several variants in this type of disorder
which can be only diagnosed only when patient is under an
intensive care conditions and also the patient with such
disorder do not experience and physical symptoms. Such
diseases turn out to be deadly if not treated early. A detection
system is thus required which is capable of detecting these
arrhythmias in real time and aid in the diagnosis. An FPGA
based arrhythmia detection system is designed and
implemented here which can detect second degree AV block
type of arrhythmia. The designed system was simulated and
tested with ECG signal from MIT-BH database and the
results revealed that a robust arrhythmia detection system
was implemented.
Denoising of Radial Bioimpedance Signals using Adaptive Wavelet Packet Transf...iosrjce
In recent years, the accurate computer aided diagnosis of the cardiovascular diseases is gaining
momentum. In addition to accuracy, non-invasiveness of the measurement techniques has become the need of
the hour. Impedance cardiography is one such method which has become a synonym for indirect assessment of
monitoring the stroke volume, cardiac output and other hemodynamic parameters by monitoring the blood
volume changes of the body. Changes occurring in the blood volume within a certain body segment due to
various physiological processes are captured in terms of the impedance variations of that segment. But this
method is affected by electrical noise such as power line hum and motion and respiratory artifacts due to
movement of the subject while acquiring the bioimpedance signal. This can cause errors in the automatic
extraction of the characteristic points for estimation the hemodynamic parameters. This paper presents two
algorithms for baseline wander removal from the bioimpedance waveform obtained at the radial pulse of the left
hand, one based on wavelet packet decomposition and the other based on the Kalman filter. The impedance
signals have been acquired by using the peripheral pulse analyzer. The results for the wavelet packet decomposition are found to be better than that of the Kalman filter.
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Similar to Evaluating ECG Capturing Using Sound-Card of PC/Laptop (20)
8th International Conference of Information Technology, Control and Automatio...ijics
8th International Conference of Information Technology, Control and Automation (ITCA 2020) will provide an excellent international forum which contributes new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The conference focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this conference is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
International Journal of Instrumentation and Control Systems (IJICS)ijics
International Journal of Instrumentation and Control Systems (IJICS) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Instrumentation Engineering and Control Systems. The journal focuses on all technical and practical aspects of Instrumentation Engineering and Control Systems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced instrumentation engineering, control systems and automation concepts and establishing new collaborations in these areas. Authors are solicited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the Instrumentation Engineering.
8th International Conference of Information Technology, Control and Automatio...ijics
8th International Conference of Information Technology, Control and Automation (ITCA 2020) will provide an excellent international forum which contributes new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The conference focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this conference is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
An angular momentum spinner includes two or more rotating arms loaded with an adjustable sliding block
for each arm and laid symmetrically about a rotating center. Each sliding block is controlled to move
along the corresponding rotating arm. Such a spinner can display the conservation of angular momentum
vividly and intuitively, and can also serve as an amusing toy for children. The spinner can be used as a
teaching equipment to demonstrate the theorem of angular momentum conveniently, intuitively and
amusingly.
A STUDY ON APPLICATION OF BAYES’ THEOREM IN APPIN TECHNOLOGYijics
Mathematics is the only word that conquers the whole world. Mathematics comprises each and every concept that exists in this world. Statistics and probability are the two main concepts that are dealing with the statistical survey of this world. Of these two concepts, Probability has one of the Main applications of dealing with mathematics that is very much useful in real life applications. In this paper, Bayes’ Theorem and its applications are discussed deeply with its application problems using the data which was collected for the company named Appin Technology during the industrial exposure training. This application helped me to give some useful ideas to the company to improve their production level.
8th International Conference of Information Technology, Control and Automatio...ijics
8th International Conference of Information Technology, Control and Automation (ITCA 2020) will provide an excellent international forum which contributes new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The conference focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this conference is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
International Journal of Instrumentation and Control Systems (IJICS)ijics
International Journal of Instrumentation and Control Systems (IJICS) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Instrumentation Engineering and Control Systems. The journal focuses on all technical and practical aspects of Instrumentation Engineering and Control Systems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced instrumentation engineering, control systems and automation concepts and establishing new collaborations in these areas. Authors are solicited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the Instrumentation Engineering.
International Journal of Instrumentation and Control Systems (IJICS)ijics
International Journal of Instrumentation and Control Systems (IJICS) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Instrumentation Engineering and Control Systems. The journal focuses on all technical and practical aspects of Instrumentation Engineering and Control Systems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced instrumentation engineering, control systems and automation concepts and establishing new collaborations in these areas. Authors are solicited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the Instrumentation Engineering.
International Journal of Instrumentation and Control Systems (IJICS)ijics
International Journal of Instrumentation and Control Systems (IJICS) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Instrumentation Engineering and Control Systems. The journal focuses on all technical and practical aspects of Instrumentation Engineering and Control Systems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced instrumentation engineering, control systems and automation concepts and establishing new collaborations in these areas. Authors are solicited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the Instrumentation Engineering.
International Journal of Instrumentation and Control Systems (IJICS)ijics
International Journal of Instrumentation and Control Systems (IJICS) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Instrumentation Engineering and Control Systems. The journal focuses on all technical and practical aspects of Instrumentation Engineering and Control Systems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced instrumentation engineering, control systems and automation concepts and establishing new collaborations in these areas. Authors are solicited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the Instrumentation Engineering.
International Journal of Instrumentation and Control Systems (IJICS)ijics
International Journal of Instrumentation and Control Systems (IJICS) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Instrumentation Engineering and Control Systems. The journal focuses on all technical and practical aspects of Instrumentation Engineering and Control Systems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced instrumentation engineering, control systems and automation concepts and establishing new collaborations in these areas. Authors are solicited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the Instrumentation Engineering.
5th International Conference on Networks, Communications, Wireless and Mobile Computing (NCWMC 2020) looks for significant contributions to the Computer Networks, Communications, wireless and mobile computing for wired and wireless networks in theoretical and practical aspects. Original papers are invited on computer Networks, network protocols and wireless networks, Data communication Technologies, network security and mobile computing. The goal of this Conference is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
International Journal of Instrumentation and Control Systems (IJICS)ijics
International Journal of Instrumentation and Control Systems (IJICS) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Instrumentation Engineering and Control Systems. The journal focuses on all technical and practical aspects of Instrumentation Engineering and Control Systems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced instrumentation engineering, control systems and automation concepts and establishing new collaborations in these areas. Authors are solicited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the Instrumentation Engineering.
International Journal of Instrumentation and Control Systems (IJICS)ijics
International Journal of Instrumentation and Control Systems (IJICS) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Instrumentation Engineering and Control Systems. The journal focuses on all technical and practical aspects of Instrumentation Engineering and Control Systems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced instrumentation engineering, control systems and automation concepts and establishing new collaborations in these areas. Authors are solicited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the Instrumentation Engineering.
International Journal of Instrumentation and Control Systems (IJICS)ijics
International Journal of Instrumentation and Control Systems (IJICS) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Instrumentation Engineering and Control Systems. The journal focuses on all technical and practical aspects of Instrumentation Engineering and Control Systems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced instrumentation engineering, control systems and automation concepts and establishing new collaborations in these areas. Authors are solicited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the Instrumentation Engineering.
International Journal of Instrumentation and Control Systems (IJICS)ijics
International Journal of Instrumentation and Control Systems (IJICS)
ISSN : 2249 - 1147 [Online]; 2319 - 412X [Print]
http://airccse.org/journal/IJICS/ijics.html
Call For Papers
Important Dates
· Submission Deadline : January 11, 2020
· Acceptance Notification : February 11, 2020
· Final Manuscript Due : February 19, 2020
International Journal of Instrumentation and Control Systems (IJICS)ijics
International Journal of Instrumentation and Control Systems (IJICS) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Instrumentation Engineering and Control Systems. The journal focuses on all technical and practical aspects of Instrumentation Engineering and Control Systems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced instrumentation engineering, control systems and automation concepts and establishing new collaborations in these areas. Authors are solicited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the Instrumentation Engineering.
A STUDY ON APPLICATION OF BAYES’ THEOREM IN APPIN TECHNOLOGYijics
Mathematics is the only word that conquers the whole world. Mathematics comprises each and every concept that exists in this world. Statistics and probability are the two main concepts that are dealing with the statistical survey of this world. Of these two concepts, Probability has one of the Main applications of
dealing with mathematics that is very much useful in real life applications. In this paper, Bayes’ Theorem and its applications are discussed deeply with its application problems using the data which was collected for the company named Appin Technology during the industrial exposure training. This application helped me to give some useful ideas to the company to improve their production level.
An angular momentum spinner includes two or more rotating arms loaded with an adjustable sliding block for each arm and laid symmetrically about a rotating center. Each sliding block is controlled to move along the corresponding rotating arm. Such a spinner can display the conservation of angular momentum vividly and intuitively, and can also serve as an amusing toy for children. The spinner can be used as a teaching equipment to demonstrate the theorem of angular momentum conveniently, intuitively and amusingly.
Integrating Fault Tolerant Scheme With Feedback Control Scheduling Algorithm ...ijics
In order to provide Quality of Service (QoS) in open and unpredictable environment, Feedback based
Control Scheduling Algorithm (FCSA) is designed to keep the processor utilization at the scheduling
utilization bound. FCSA controls CPU utilization by assigning task periods that optimize overall control
performance, meeting deadlines even if the task execution time is unpredictable and through performance
control feedback loop.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Knowledge engineering: from people to machines and back
Evaluating ECG Capturing Using Sound-Card of PC/Laptop
1. International Journal of Instrumentation and Control Systems (IJICS) Vol.4, No.1, January 2014
Evaluating ECG Capturing Using Sound-Card of
PC/Laptop
B. N. Patel1, D. N. Shah2
1,2
Department of instrumentation and control, Sarvajanik College of Engineering and
Technology Surat, Gujarat, INDIA
Abstract
The purpose of the Evaluating ECG capturing using sound-card of PC/Laptop is provided portable and low
cost ECG monitoring system using laptop and mobile phones. There is no need to interface microcontroller or any other device to transmit ECG data. This research is based on hardware design,
implementation, signal capturing and Evaluation of an ECG processing and analyzing system which attend
the physicians in heart disease diagnosis. Some important modification is given in design part to avoid all
definitive ECG instrument problems faced in previous designs. Moreover, attenuate power frequency noise
and noise that produces from patient's body have required additional developments. The hardware design
has basically three units: transduction and conditioning Unit, interfacing unit and data processing unit.
The most focusing factor is the ECG signal/data transmits in laptop/PC via microphone pin. The live
simulation is possible using SOUNDSCOPE software in PC/Laptop. The software program that is written
in MATLAB and LAB-View performs data acquisition (record, stored, filtration) and several tasks such as
QRS detection, calculate heart rate.
Keywords
ECG, Instrumentation Amplifier (AD620), Sound-scope, MATLEB, LAB-View and ECG monitoring system.
1. Introduction
What is an ECG?
The Heart is a muscle formed that allows it to act as a pump for blood circulation in a body. The
heart pumps blood when the muscle cells making up the heart wall contract, generating their
action potential. This potential creates electrical currents that spread from the heart throughout a
body.The electrical potential between various locations shows differences due to spreading
electrical currents in the body. The electrical potential can be detected and recorded by placement
of electrodes on skin. The cardiac electrical potential waveform generated by these bio-potentials
is called the Electrocardiogram (ECG).
Electro-conduction system of Heart
The conduction system of the heart is shown in figure 1. It consists of the Senatorial (SA) node,
bundle of his, Atrioventricular (AV) node, the bundle branches, and Purkinje fibres. The SA node
serves as a pacemaker for the heart and it provides the trigger signal. It is a small bundle of cells
located on the rear wall of the right atrium, just below the point where the superior vena cava is
DOI : 10.5121/ijics.2014.4102
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2. International Journal of Instrumentation and Control Systems (IJICS) Vol.4, No.1, January 2014
attached. The SA node fires electrical impulses through the bioelectric mechanism. It is capable
of self excitation but is under control of the CNS so that the heart rate can be adjusted
automatically to meet varying requirements.
Fig 1: Electro-Conduction System of Heart
When the SA node discharges a pulse, then electrical current spreads across the atria, causing
them to contract. Blood in the atria is forced by the contraction through the valves to the
ventricles. The velocity of propagation for the SA node action potential is about 30cm/s in the
atrial tissue. There is a band of specialized tissue between the SA node and AV node, however in
which the velocity of propagation is faster than it is in atrial tissue. This internal conduction
pathway carries the signal to the ventricals. The muscle cells of ventricles are actually excited by
purkinje fibres. The action potential travels along these fibres at the much faster rate on the order
of 2 to 4 m/s. The fibres are arranged in two bundles, one branch on left and another is on right.
Fig 2: Typical ECG Waveform
Conduction in the fibres is very rapid. The action potentials generated in SA node stimulates the
muscle fibres of the myocardium, causing them to contract. When the muscle in the contraction, it
is become shorter, and the volume of the ventricular chamber is less, so blood is constricted out.
The shortening or tensing of so many muscles at one time creates a mass electrical signal that can
be detected by electrodes place on the surface of the patient’s chest. This electrical dispatch can
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3. International Journal of Instrumentation and Control Systems (IJICS) Vol.4, No.1, January 2014
be plotted as a function of time and the resultant waveform is known as Electrocardiogram
(ECG).
Different Methods of ECG Capturing
There are various Methods available of ECG capturing and evaluating.
1) ECG Machine
2) Portable ECG Monitor
3) ECG Readout Device
4) PC based ECG system
5) Using sound card of PC
2. Circuit Design
Introductory Description of Circuit Design
The aim is to design a sensitive amplifier circuit that can detect ECG (Electrocardiogram) signals
found from electrodes applied at the left arm (LA), Right arm (RA) and right leg (RL). The
difference between the right-arm (RA) lead and the left-arm (LA) lead is amplified by circuit with
the right-leg (RL) lead as the ground or reference node. The circuit needs a two stage
instrumentation amplifier which has buffering stage and amplification stage. After that filtering
stage is required for signal filtration.
Fig 3: General Block Diagram of ECG Amplifier
A general block diagram of a modern ECG amplifier is shown in Fig. 3. It is designed around an
instrumentation amplifier. In addition, the instrumentation amplifier has feature of an automatic
offset (DC) cancellation circuit to keep the output always zero averaged. The electrical safety is
provided by driven-right leg circuit and the interference is reduced under normal operational
conditions. Low-pass filter provides further amplification and limit the bandwidth of the circuit.
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4. International Journal of Instrumentation and Control Systems (IJICS) Vol.4, No.1, January 2014
Electrode placement
ECG is recording most commonly between the Right Arm (RA) and the Left Arm (LA).
Sometimes another two combinations using the Left Leg (LL) are also used clinically (RA−LL
and LA−LL). For common ground of the Instrumentation amplifier, there are one another
electrode connects to the patient. This is attached to the right leg.
Fig 4: Typical Electrode Placement
The movement of electrode with respect to the electrolyte is mechanically disturbed. So, the
distribution of charge at the interface and results in a momentaneous change of the half−cell
potential until equilibrium can be restored. If one electrode is moved while the other remains
stable, a potential difference appears between the two electrodes during this movement. Due to
this kind of movement the potential is referred to as movementartifactand this can be a grievous
cause of interference in the measurement of ECG.
Theoretical Design
To fulfil the requirements of our ECG amplifier, we need to design a cascade circuit, which is a
combination of a Instrumentation Amplifier, a Low Pass Filter, a High Pass Filter and a gain
stage. For reducing noises, the order of cascade stages is considered. For example, in the
following cascade Figure, the output noise is
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5. International Journal of Instrumentation and Control Systems (IJICS) Vol.4, No.1, January 2014
Fig 5: Cascade Design of Amplifier
Cascade design is on the basis of placing high gain stages in the signal path. All the same, the
High Pass Filter stage should be placed immediately after the differential amplifier to remove DC
offset.
Instrumentation Amplifier AD620
The AD620 is a low cost, high accuracy of 40 ppm with maximum nonlinearity instrumentation
amplifier that requires only one external resistor to set gains of 1 to 1000. The AD620 has low
offset voltage of 50 mV max and offset drift of 0.6 mV/°C max.
Fig 6: Pin Diagram of AD620
Furthermore, it has low noise, low input bias current and low power which makes it well suited
for medical applications such as ECG and non-invasive blood pressure monitors.Gain of the
AD620 is set by connecting a single external resistor RG, as shown commonly used gains and RG
resistor values. The internal gain resistors R1 and R2. Trimmed to an absolute value of 24.7KΩ,
allowing the gain to be programmed accurately with a single external resistor. These resistors are
affected by the accuracy and temperature coefficient included in the gain accuracy.
G = 1 + (49.4 k/RG)................ (1)
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6. International Journal of Instrumentation and Control Systems (IJICS) Vol.4, No.1, January 2014
Table 1: Values of Rg for settling Gain of AD620
The stability and temperature drift of the external gain setting resistor, RG, also affects gain.
RG’s contribution to gain accuracy and drift can be directly inferred from the gain equation.
There are many important features of AD620 such as gain set with one resistor, wide range power
supply, 100dB min CMRR (common-mode rejection ratio), low noise and excellent DC
performance. AD620 is used in many applications like portable battery operated system,
physiological amplifier: EEG, ECG, EMG, multi channel data acquisition, ECG and medical
instrumentation etc.
Designed Circuit
Fig 7: ECG Circuit with Right Leg Driven Circuit
Frequency Adjustment
The average heart rate of a person is around 1.1Hz and the signal level is very weak thus to avoid
interference from other signals, a band pass filter is needed. The desired frequencies (between
0.05 Hz and 150Hz) can be achieved via operational amplifier, capacitors and Resistors where the
values are found for the high pass and low pass respectively.
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7. International Journal of Instrumentation and Control Systems (IJICS) Vol.4, No.1, January 2014
Low pass 0.05
High Pass 150
For High Pass filter
For Low Pass filter
=
=
R = 3.18 MΩ, C= 1µF
R = 106 KΩ, C= 0.01µF
Fig 8: Filter Circuit for ECG
Thus the filter supplies a gain of 5. The Resistor 3.18MΩ connected to non-inverting input is for
keeping the balance and symmetry.
Right Leg Driven Circuit
Fig 9: Right Leg Driven Circuit
The aim of right leg driven circuit is reducing the effect of noise. The common mode signal taken
from the both ends of the Rg (gain resistance of AD620) is given back to body as a reference.
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8. International Journal of Instrumentation and Control Systems (IJICS) Vol.4, No.1, January 2014
G=
Ω
Ω
Ω
The values of the resistances are 25KΩ for the input resistance. Also a low pass filter with 150Hz
cut-off frequency is existent with R = 10KΩ and c =106nf. The gain of the circuitry is defined by
1MΩ resistance.
Output DC level Shifting
The last stage of the circuit is both designed to provide the necessary gain and the necessary
voltage shifting to make the signal appear on the limits is 0 to 5 volts. This stage is expected to
have a gain of 25. Since the amount of voltage shifting is unknown the voltage shifting is applied
after the first ECG signal is observed. Initially an inverting amplifier with R1=5KΩ and
R2=125KΩ used.
Realization of The circuit
The circuit is first realized on breadboard. Some of the values have changed due to the
availability of the resistors and capacitors. For the operational amplifier op07 is used in all stages.
While the circuitry is being built each stage is checked by a given signal which would not cause
clipping.
Changes with Realization
1) AD620
Installing Rg as 8.4KΩ gave unwanted gain so the value had to be increased to decrease the gain.
Inserting a 27KΩ resulted with a gain of 10, even though it was unexpected, in order to not using
a larger resistance, the 27KΩ is accepted and the extra gain is corrected by changing the last
stage.
2) Band-pass stage
For the high-pass filter a resistance of 3.18MΩ is used. The resistance is in fact labelled as 3MΩ,
however its exact value was 3.18MΩ. For the low-pass filter the 106 is realize as an 112KΩ and
the 21.2KΩ is realize as a 21.8KΩ (series combination of 3.8KΩ and 18KΩ)
3) Output DC Level Shifting
The amount of shifting is done by supplying is done by supplying the inverting input and
supplying the shifting dc voltage from the non-inverting input, thus the amount of dc input can be
found by dividing the desired DC voltage level by non-inverting gain of the stage.
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9. International Journal of Instrumentation and Control Systems (IJICS) Vol.4, No.1, January 2014
Fig 10: Gain Stage and DC level Shifter
However due to non-ideal of op07 the non-inverting input lowered the gain. With an interactive
method the correct values are found. The input dc voltage is supplied from Vdc by a voltage
divider.
Modification
To prevent the signal being lost in the 50Hz interface, a 50Hz notch filter is designed and
implemented.
Fig 11: Schematic of Notch Filter
Complete ECG Circuit
Fig 12: Complete ECG Circuit
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10. International Journal of Instrumentation and Control Systems (IJICS) Vol.4, No.1, January 2014
Soundcard of Laptop
A sound card also known as an audio card which has facilitates the input and output of audio
signals to and from a computer under control of computer programs. Typical uses of sound cards
include providing the audio component for multimedia applications such as music composition,
editing video or audio, presentation, education, and entertainment (games). Many computers have
in built sound capabilities, while others require further soundcard expansion cards to provide for
audio potentiality.
Fig 13: Soundcard Hardware
Sound card has usually functioned of analogue-to-digital converter (ADC), which converts
recorded or generated analogue data into a digital format. The output signal is connected to an
amplifier, headphones, or external device using standard interconnects. For higher data rates and
multiple functions, there is more advanced card commonly include more than one chip .
Microphone Pin Configuration
The diagram below illustrates how to configure a standard stereo microphone plug. The tip of the
pin is the left channel, the ring type metal portion is the right channel, and the rest of the pin is the
ground. There is one plastic ring between two channels which separates the channel and ground.
Use a multimeter or continuity tester to determine the channel identifications of the solder logs.
Fig 14: Microphone Pin
1 – Signal (audio) out left channel/Channel-1
2 – Signal (audio) out right channel/Channel-2
3 – Ground – common for microphone and audio out.
Heart Pulse Detector Circuit
Photoplethysmography (PPG) is a non-invasive method of measuring the variation in blood
volume in tissues using a light source and a detector which is the principle of heart pulse detector
circuit.
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11. International Journal of Instrumentation and Control Systems (IJICS) Vol.4, No.1, January 2014
Fig 15: Heart Pulse Sensor
Since the change in blood volume is synchronous to the heart beat, this technique can be used to
calculate the heart rate. For reflectance PPG, the light source and the light detector are both
placed on the same side of a body part. The light is emitted into the tissue and the reflected light
is measured by the detector. PPG can be applied to any parts of human body. In either case,
the detected light reflected from or transmitted through the body part will fluctuate according to
pulse rate blood flow caused by the beating of the heart.
3. Software Description
Sound Card Scope
The PC based Soundcard Oscilloscope obtains its data with 96 kHz and 16 Bit resolution from the
soundcard. The data source can be selected in the Windows mixer such as Microphone, Line-In
or Wave.
Fig 16: Sound Scope Display
The frequency range depends on which kind of a soundcard already in laptop/pc, but 20-20000Hz
should be possible with all modern cards. The oscilloscope contains in further a signal generator
for 2 channels for Sine, Square, Triangular and Saw tooth wave forms in the frequency range
from 0 to 20 kHz. These signals are available at the speaker output of the sound card.
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Implementation Steps in Sound Scope
1) Run sound scope software.
2) Go settings and Check windows Sound parameters
3) Change Input tab as Microphone / Line In.
4) Select the channel-1 / Channel-2 as microphone pin wire connection.
5) Set the Amplitude and Time Division
6) Run the simulation and Check the waveform.
7) Pause simulation and store data file.
MATLAB Simulink
Define soundcard in MATLAB
For data acquisition of ECG signal, it is very important to interface sound card in MATLAB.
There is a facility available to interface sound card in MATLAB for particular frequency up to 96
kHz. It records data fro given time interval after that we have to plot data and apply different
operation related evolution and analysis of ECG signal.
MATLAB code for Sound card interface
AI = analoginput(‘winsound’);
addchannel(AI, 1);
Fs = 5000;% Sample Rate is 100 Hz
set (AI, ‘SampleRate’, Fs)
duration = 5;
% 5 second acquisition
set(AI, ‘SamplesPerTrigger’, duration*Fs);
start(AI);
data = getdata(AI);
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delete(AI)
plot(data,’DisplayName’,’data’,’YdataSource’,’data’);
figure(gcf)
Filter of signal in MATLAB
Some common ECG Filtering tasks are performed which are Baseline wander filter and Power
line interference filter. When filtering any biomedical signal care should be taken not to falsify
the desired information in any condition. A major intrest is how the QRS complex affects the
output of the filter. Sometimes the filter often carry out a large unwanted impulse and possible
distortion caused by the filter should be cautiously quantified.
Apply Butterworth Filter /Base line Filter
Baseline filter is included extragenoeous low-frequency for high-bandwidth components and it
can be caused by movements of electordes which effects electrode impedance, Respiration and
Body movements. Which can cause troubles to analysis mostly when analise the low-frequency
ST-T segment.
MATLAB Code :
sig = data
plot(sig)
[A,B] = BUTTER(2,0.002)
subplot(211),plot(data);
subplot(212),plot(filter(A,B,data));
Apply Notch filter / Power Line Filter
Electromagnetic fields from power lines can cause 50/60 Hz sinusoidal disturbance, possibly
companioned by some of its constant frequency. Such noise can cause problems interpreting lowamplitude waveforms and unauthentic waveforms can be introduced. Naturally care should be
taken to keep power lines as far as possible and shield and ground them but this is not always
possible everywhere.
MATLAB Code :
input=data
plot(input)
fs=750;
N=length(input);
t = ((0:length(input)-1)./fs); %Time Interval
t=t’;
figure(1)
plot(t, input)
xlabel(‘Sampling frequency’)
ylabel(‘Volts’)
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Ys = fft(input)/N;
i_space=linspace(0,.5,N/2); %adjusting the frequency range at particular interval
frq = fs*i_space;
Ys = Ys(1:ceil(N)/2);
plot(frq,2*abs(Ys))
xlabel(‘Frequency in Hz’)
ylabel(‘|Y(f)|’)
%intialization
F_0=0.33;
Delta_F=0.1;
[b,a] = iirnotch (F_0,Delta_F);%creates coefficient vectors a and b
fvtool(b,a);
refined=filter(b,a,input); %filter signal
[H Hf] = freqz(b,a,N); %returns transfer function
amp=abs(H);
figure(2)
plot(Hf*fs,amp)
xlabel(‘Frequency in Hz’)
ylabel(‘|H(f)|’)
%Attempting different values of delta F
subplot(3,1,1)
plot(t,refined)
title(‘Refined ECG Signal when delta F=1’)
xlabel(‘Sampling Frequency’)
ylabel(‘volt’)
F_0=0.6;
Delta_F=0.001;
[b,a] = iirnotch (F_0,Delta_F);%creates coefficient vectors a and b
refined=filter(b,a,input); %filter signal
subplot(3,1,2)
plot(t,refined)
title(‘Refined ECG Signal when delta F=5’)
xlabel(‘Sampling Frequency’)
ylabel(‘volt’)
F_0=0.9;
Delta_F=0.0001;
[b,a] = iirnotch (F_0,Delta_F,fs);%creates coefficient vectors a and b
refined=filter(b,a,input); %filter signal
subplot(3,1,3)
plot(t,refined)
title(‘Refined ECG Signal when delta F=10’)
xlabel(‘Sampling Frequency’)
ylabel(‘volt’)
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%interference
interference=input-refined;
plot(t, interference)
title(‘Interference’)
xlabel(‘Sampling Frequency’)
ylabel(‘volt’)
Heart Beat Count
The data signal hold and sample with particular sample frequency for counting the heart pulses.
Then count the dominant peak of signal which corresponds to heart pulses.Peaks are defined to be
samples greater than their two nearest neighbours and greater than 1 and divides beat counted by
signal.
MATLAB Code:
%progaram to determine the BPM of ECG signal
sig = data;
plot(sig)
xlabel(‘Samples’);
ylabel(‘Electrical Activity’);
title(‘Ecg Signal sampled at 100Hz’);
hold on
plot(sig,’ro’)
%count the dominant peaks in the signal(these 25orrespond to heart beats)
% - peaks are defined to be samples greater than their two nearest neighbours and greater than 1
beat_count = 1;
for k = 2 : length(sig) – 1
if(sig(k) > sig(k-1) & sig(k) > sig(k+1) & sig(k) > 1) %k
%disp(‘Prominent Peak found’)
beat_count = beat_count + 1
end
end
%Devide the beats counted by the signal duration (in minutes)
beat_count = 1;
fs = 4000;
N = length(sig);
duration_in_seconds = N*0.1/fs;
duration_in_minutes = duration_in_seconds/60;
BPM = beat_count/duration_in_minutes
sig = sig(1:500);
hold off
plot(sig)
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LAB-View
This technical description will introduce the concepts required to build a basic system with LABView. The most important building blocks for any LAB-view application, including the front
panel, block diagram, palettes, controls, and indicators. Graphical Programming Basics see how
to connect functions and work with a variety of data types when constructing applications.
Common Tools view a collection of important tools and common user functions that all users
should be familiar with LAB-View.
Lab View Design To get ECG data
The basic block diagram of the ECG signal condition is shown in fig 17. The filtrations procedure
describes below and detail of specification of software components.
Fig 17: Block Diagram of ECG in LAB-View
Acquire Sound Block
[1] Error in describes error conditions that occur before this function runs and this input provides
standard error in functionality.
[2]Path out identifies the ECG data stored in wave file.
[3] Total number of samples have total number of channels selection and the number of bits per
sample in the wave file.
[4]Format shows the sample rate, the number of channels and the number of bits per sample in
the wave file.
[5]Sample rate (S/s) selects sampling rate for the wave file. Common rates are 44,100 S/s,22,050
S/s and 11.025 S/s.
[6]Number of channels specifies which channel of soundcard in the wave file. This input can
accept as many channels as sound card supports. For most sound cards 1 is Mono and 2 is Stereo.
[7]Bits per sample are the quality of each sample in bits. Common resolutions are 16 bits and 8
bits but 16 bits are more accurate than 8 bits.
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[8]Error out contains error information. This output provides standard error out functionality.
Biosignal Filtering (Waveform Classical / Array Filter) Block
[1]Type specifies the classical filter to apply to input biosignal 0 Low-pass,1 High-pass and 2
Band-pass
[2]Freq specs specify the frequency specifications for the classical filter.
[3]Fpass 1 specifies the first pass band edge frequency in hertz. The default is 0.2.
[4]Fpass 2 specifies the second pass band edge frequency in hertz. This VI ignores Fpass 2 for
low pass and high pass filters. The default is 0.
[5]Fstop 1 specifies the second stop band edge frequency in hertz. The default is 0.3.
[6]Fstop 2 specifies the second stop band edge frequency in hertz. This VI ignores for low pass
and high pass filters. The default is 0.1.
[7]Ripple specs specifies the ripple specifications for the classical filter.
[8]Pass band specifies the ripple level in the pass band. The default is 0.1.
[9]Stop band specifies the ripple level in the stop band. The default is 60.
[10]Error in describes error conditions that occur before this function runs.
[11]Out returns the filter that this VI applies to the input biosignal.
[12]Error out contains error information. This output provides standard error out functionality.
ECG Feature Extractor (Waveform QRS) Block
[1]QRS detector parameter specifies the parameters that this VI uses to detect QRS waves.
[2]Rough highest heart rate determines the approximate highest heart rate of the ECG signal in
beats per minute (bpm) and the default value is 60 bpm.
[3]Peak detection initial threshold determines the initial threshold for QRS complex detection.
[4]Threshold factor defines the factor that VI uses to determine the threshold for separating
noise peaks and QRS waves. Threshold factor must be greater than 0 and less than 1.
[5]Error in describes error conditions that occur before this function runs and this input provides
standard error in functionality
[6]QRS time returns the occurring times of detected QRS complexes. This QRS time by using
the input ECG signal, which might be a preprocessed signal.
[7]QRS peak returns the amplitudes of the detected QRS complexes. QRS peak through the input
ECG signal, which might be preprocessed..
[8]Error out contains error information. This output provides standard error out functionality
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Bio-Medical Tool connectivity
The Biomedical Workbench in LAB-View Biomedical Toolkit provides applications for bio
signal and biomedical image analysis. These applications enable to apply biomedical solutions
using Lab VIEW. These applications to log and play biosignals, simulate and generate biosignals,
analyzebiosignals, and view biomedical images. The application can acquire real world and realtime biomedical data by using biomedical sensors and National Instruments hardware. The
applications in Biomedical Workbench is extract features from electrocardiogram (ECG) signals,
to analyze heart rate variability (HRV), and to measure blood pressure.
ECG Feature Extractor
ECG feature Extractor imports ECG signals from different file types. See Biosignal Viewer for
file formats supported. It imports ECG signals from a data acquisition (DAQ) device and
integrates robust
Fig 18: ECG feature Extractor
extraction algorithms to detect ECG features, such as the QRS Complex, P wave, and T wave. It
transfers RR interval data to Heart Rate Variability Analysis application and exports ECG
features reports for printing.
Heart Rate Variability (HRV) Analyzer
HRV analyzer synchronizes RR intervals from the ECG Feature Extractor application and
imports RR intervals from an electrocardiogram (ECG) file that the ECG Feature Extractor
application generates or from a text file that contains RR intervals.
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19. International Journal of Instrumentation and Control Systems (IJICS) Vol.4, No.1, January 2014
Fig 20: Heart Rate Variability Analyzer
It provides a variety of analysis methods for HRV analysis including Statistics (including
histogram), Poincare plot, FFT spectrum, AR spectrum, STFT spectrogram, Gabor spectrogram,
wavelet coefficients, DFA plot and recurrence map.
4. Results
[1] Designed circuit output
Waveform in sound scope
MATLAB Output
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MATLAB Filtrations output
Heart Beat Result in LAB-View
Filtrations in LAB-View
Heart Beat Result in MATLAB
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[2] Heart pulse sensor output
Digital Oscilloscope Output
Sound Scope Output
MATLAB Output
5. Conclusion
Evaluating ECG Capturing Using sound Card of PC/laptop is designed and performed without
interfacing microcontroller or any other data transmission devices. The transformations of ECG
signal from circuit to laptop via micro-phone jack which is already connected with inbuilt
soundcard. This method has low cost and less complexity. Only it required basic knowledge of
circuit design and programming skills. In circuit design, various electronics and bio-medical
instrumentation’s principle are used. AD620 is a specific instrumentation amplifier. This is used
specially in bio-medical application because it has high CMRR and low input noise amplifier.
There are high-pass, low-pass, band-pass and notch filters are designed for reduced frequency
oriented noise.
The Sound-scope is a one of the software which shows the live or real time simulation of ECG
signal which transmit through micro-phone pin. MATLAB is stored the data in sampling
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22. International Journal of Instrumentation and Control Systems (IJICS) Vol.4, No.1, January 2014
frequency of soundcard. In which sample and hold process carry out and various operations such
are filtration and beat count performed by programme. In LAB-View, the basic block diagram
designed and each block has facility of set all function and variable value with bio-medical tool
connectivity.
When the circuit is implemented, sensitivity of the circuit is very high. There is some minor
change and movement affect the output wave. After, the take care by using special ECG lead
cables and shield cable is used for interface a circuit. Circuit is totally cover with the aluminium
foil paper so that, noise interference from environment and electrical & electronics components is
reduced.
Acknowledgement
We welcome this opportunity to express our devout appreciation and regards to our Head of
Department Dr. UtpalPandya, Department of instrumentation & control Engineering, Sarvajanik
college of engineering and Technology, Surat, for his unconditional guidance. He always
bestowal parental care upon us and expressd keen interest in solving our problems. An erudite
teacher, a tremendous person and a strict disciplinarian, we consider ourselves fortunate to have
worked under his supervision. Without his co-operation, the extensive work involved in
compiling background information and preparing the paper for publication would not be possible.
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seminarprojects.com/s/biomedical-projects-using-labview
sites.google.com/site/fionaproj/home/beng-401/ecg-circuit
engineerslabs.com/ecg-circuit-analysis-and-design-simulation
www.edaboard.com› Forum › AnalogDesign › Analog Circuit Design
www.docircuits.com/learn/category/ecg/
http://e2e.ti.com/support/amplifiers/precision_amplifiers/f/14/t/148599.aspx
http://www.biosemi.com/publications/artikel5.htm
http://healthcare.analog.com/en/patientmonitoring/ecg-diagnostic-line-powered/segment/health.html
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Authors
Bhavikkumar Patel received B.E.degree in Instrumentation and Control Engineering
from the Gujarat Technological University, India. His area of interest covers Biomedical Instrumentation and Automation aswell as PLC and SCADA.
Dhrumil Shah has received B.E. degree in Instrumentation and Control Engineering
from Gujarat Technological University, India. He also seeks some of his interests in
control system designing and Signal Conditioning.
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