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A 38.4 nW, 1.2 V, 250-Hz, 2nd-Order gm - C LPF With Degenerative SCP Transconductors Achieving 800-mVPP Input Range and 82.1- μVrms IRN for ECG Acquisition
(2025-01-01)
Thanapitak, Surachoke
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Pawarangkoon, Prajuab
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Surakampontorn, Wanlop
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Ahmad, Rafidah
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Abdullah Zawawi, Ruhaifi
In this brief, a 2{^{\text {nd} -order gm - C lowpass filter with a practical input linear range of 400mV P dedicated to ECG signal acquisition is proposed. This filter employs a degenerative source-coupled-pair circuit as a gm cell. It enhances the linear input range by a factor of × 4 compared with the source follower filter. Additionally, to mitigate the effect of current source mismatch, a dynamic element matching technique is applied. By doing so, HD2 is suppressed more than 1.5 dB over the entire passband frequency. This proposed filter is implemented in a 0.18 μ m CMOS process. It offers a 250-Hz bandwidth with input-referred noise and a dynamic range of 82.1 μ Vrms and 67.34 dB, respectively. The power consumption of 38.4 nW is achieved with a 1.2 V supply. Compared with other recent nano-power filters, the proposed filter provides the highest linear input range with competitive Figure-of-Merit to the top-tier designs. It is therefore beneficial to the practical implementation of a low-power ECG acquisition system.
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High-order chebyshev notch filter based on MO-OTA and its application in Biosensor
(2021-05-19)
Srisamranrungrueang, Siradanai
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Wongprommoon, Natapong
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Prommee, Pipat
This paper presents a high-order notch filter based on multiple output OTA (MO-OTA). The signal flow graph (SFG) method is applied as a design procedure based on the RLC prototype. The RLC Chebyshev low-pass filter is used as an original prototype. The network transform is applied to convert the LPF to a notch filter. From the SFG, the denormalized network can be replaced by integrators and differentiators. The current-mode lossy and lossless types of integrator and differentiator are realized by using CMOS MO-OTA and grounded capacitor. A simple and low-complexity structure is achieved and constructed by 9 MO-OTAs and 6 grounded capacitors. The stop-band frequency between 10Hz-1kHz can be electronically tuned by the bias current between 1-100 μA. The low power supply ±0.75V is required which consumes the power 15mW at 100μA bias current. An application in ECG signal with power line interference (PLI) removal is included.
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Multi-parameter vital sign telemedicine system using web socket for covid-19 pandemics
(2021-03-01)
Pintavirooj, Chuchart
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Keatsamarn, Tanapon
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Treebupachatsakul, Treesukon
Telemedicine has become an increasingly important part of the modern healthcare infras-tructure, especially in the present situation with the COVID-19 pandemics. Many cloud platforms have been used intensively for Telemedicine. The most popular ones include PubNub, Amazon Web Service, Google Cloud Platform and Microsoft Azure. One of the crucial challenges of telemedicine is the real-time application monitoring for the vital sign. The commercial platform is, by far, not suitable for real-time applications. The alternative is to design a web-based application exploiting Web Socket. This research paper concerns the real-time six-parameter vital-sign monitoring using a web-based application. The six vital-sign parameters are electrocardiogram, temperature, plethysmogram, percent saturation oxygen, blood pressure and heart rate. The six vital-sign parameters were encoded in a web server site and sent to a client site upon logging on. The encoded parameters were then decoded into six vital sign signals. Our proposed multi-parameter vital-sign telemedicine system using Web Socket has successfully remotely monitored the six-parameter vital signs on 4G mobile network with a latency of less than 5 milliseconds.
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Mathematical modeling ECG waveform using abel's bernstein polynomials
(2019-12-01)
Chutchavong, Vanvisa
This paper presents the new mathematical model with Abel's Bernstein polynomials, that we use to approximate the curve of ECG. The Abel's Bernstein polynomials can simulate a curve of ECG that has a similarity to the normal ECG waveform and the ECG-ID Database (ecgiddb). As the results, Abel's Bernstein Polynomials models can reduce the value of order (n) and reduce the step of design procedure more than the Bernstein polynomial, Bézier-Bernstein model and Rational Bézier-Bernstein Model those are quite easy to realize an ECG waveform implementing circuit at a low cost.
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Changes in Pulse Transit Time during Psychological Stress Test
(2018-07-02)
Chuenchom, Thanapat
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Tretriluxana, Suradej
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Chitsakul, Kitiphol
Preliminary study of psychological stress on physiological parameters has been reported. Six healthy college students (male=3, female=3) participated in the modified Trier Social Stress Test (TSST). Their Electrocardiogram (ECG), Photoplethysmogram (PPG) were monitored in 5-stage experiment. Two Pulse Transit Time (PTT) were generated within each cardiac cycle from the period of R-wave presented in ECG to (1) the peak (systolic pressure) in PPG; 'PTT+' and (2) the valley (diastolic pressure) in PPG; 'PTT-'. The mean and standard deviation of these two PTTs were reported across the stages. More data will be recruited for statistical comparison in the future.
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Study of ECG variation in daily activity
(2017-12-19)
Samona, Yanisa
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Pintavirooj, C.
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Visitsattapongse, S.
Electrocardiogram (ECG) records electrical activity of the heart spreading through the heart muscle to make the heart contract. Recently ECG has been captured attention as biometric feature due to its uniqueness and large reliabilities for human identifications. In this study we aimed to verify the conservative ECG of human in their activities to ensure whether it is suitable to be used as biometric devices. Experiment studies involved 6 participants of which the age ranges is between 21 and 23. We test the robustness of ECG under various situation including health condition, emotional state and heart rate variation. The recorded ECG signal is forwarded for analysis using Matlab. Correlation coefficient of ECG Fourier transform is used as criterion to validate the ECG robustness. The result indicates that ECG is not stable and seems to vary with daily activity and emotional state. This will hampers ECG to be used as Biometric.
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Implementation of ECG portable device for real-time signal monitoring
(2017-11-24)
Purahong, B.
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Thongkrairat, S.
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Anuwongpinit, T.
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Chutchavong, V.
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Aoyama, H.
In this paper presents a system for heart rate signal analysis in ECG (Electrocardiography) format using STM32f7 board. Electrode is used for recording the signal with stick on body in lead 2 orientations. Signal processing method are used upper average, slope and interval checking algorithm to process ECG signal in real-time. In experiment, to acquire a frequency of heart beat and display ECG signal and heart rate on STM32f7 board compare with wearable device that result have error rate less than 1%. This system is portable to use and sufficient battery for recording signal to analyze and monitor throughout the day.
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Modified beat segmentation for DTW based ECG compression
(2015-01-26)
Chompusri, Yotaka
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Dejhan, Kobchai
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Yimman, Surapun
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Charbkaew, Noppadol
The proposed ECG compression method presents the new beat segmentation algorithm. Because this proposed compression method uses the residual difference between original ECG signal beat and the reference ECG beat, the ECG signal must be separated into each beat before doing the compression process. That is the duty of beat segmentation process. Therefore, this process is important step of the selective Mapping Technique ECG compression method. The main goal of this work is to design the beat segmentation algorithm which is the most suitable for this compression method. And this proposed beat segmentation algorithm is designed to replace the complicated operation algorithm. Consequently, this proposed beat segmentation algorithm uses only simple operation such as accumulation and shift operation. And moreover, the decision rule is not complicated as the previous method. The test results show that more than half of tested signals return higher compression ratio (CR). In addition, almost quarter of tested signals have better performance of percent root mean square difference (PRD). Therefore this is the alternative method for the best comparing selection.
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A mathematical model for ECG waveform using rational Bézier curves and Bernstein polynomials
(2014-01-01)
Chutchavong, V.
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Nualon, K.
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Sangaroon, O.
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Janchitrapongvej, K.
This paper presents a mathematical model for ECG waveform using Rational Bezier curves and Bernstein polynomials. There are three mathematical models; the Bernstein polynomials model, the Bézier-Bernstein model and the Rational Bézier-Bernstein model. All mathematical models can generate the ECG waveform which is similar to the normal ECG waveform. Moreover, all mathematical models can simulate a normal ECG waveform as well. As the results, the Rational Bezier-Bernstein model is a simple form, easy to make a circuit and lower cost in the implementation of the ECG waveform. © 2014 IEEE.
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Acoustic cardiac signals analysis: A Kalman filter-based approach
(2012-12-05)
Salleh, Sheik Hussain
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Hussain, Hadrina Sheik
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Swee, Tan Tian
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Ting, Chee Ming
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Noor, Alias Mohd
Auscultation of the heart is accompanied by both electrical activity and sound. Heart auscultation provides clues to diagnose many cardiac abnormalities. Unfortunately, detection of relevant symptoms and diagnosis based on heart sound through a stethoscope is difficult. The reason GPs find this difficult is that the heart sounds are of short duration and separated from one another by less than 30 ms. In addition, the cost of false positives constitutes wasted time and emotional anxiety for both patient and GP. Many heart diseases cause changes in heart sound, waveform, and additional murmurs before other signs and symptoms appear. Heart-sound auscultation is the primary test conducted by GPs. These sounds are generated primarily by turbulent flow of blood in the heart. Analysis of heart sounds requires a quiet environment with minimum ambient noise. In order to address such issues, the technique of denoising and estimating the biomedical heart signal is proposed in this investigation. Normally, the performance of the filter naturally depends on prior information related to the statistical properties of the signal and the background noise. This paper proposes Kalman filtering for denoising statistical heart sound. The cycles of heart sounds are certain to follow first-order Gauss-Markov process. These cycles are observed with additional noise for the given measurement. The model is formulated into state-space form to enable use of a Kalman filter to estimate the clean cycles of heart sounds. The estimates obtained by Kalman filtering are optimal in mean squared sense. © 2012 Zeng et al, publisher and licensee Dove Medical Press Ltd.

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