Sensitivity of Electrocardiogram on Electrode-Pair Locations for Wearable Devices: Computational Analysis of Amplitude and Waveform Distortion

An electrocardiogram (ECG) is used to observe the electrical activity of the heart via electrodes on the body surface. Recently, an ECG with fewer electrodes, such as a bipolar ECG in which two electrodes are attached to the chest, has been employed as wearable devices. However, the effect of differ...

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Main Authors: Kiyoto Sanjo, Kazuki Hebiguchi, Cheng Tang, Essam A. Rashed, Sachiko Kodera, Hiroyoshi Togo, Akimasa Hirata
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Biosensors
Subjects:
Online Access:https://www.mdpi.com/2079-6374/14/3/153
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author Kiyoto Sanjo
Kazuki Hebiguchi
Cheng Tang
Essam A. Rashed
Sachiko Kodera
Hiroyoshi Togo
Akimasa Hirata
author_facet Kiyoto Sanjo
Kazuki Hebiguchi
Cheng Tang
Essam A. Rashed
Sachiko Kodera
Hiroyoshi Togo
Akimasa Hirata
author_sort Kiyoto Sanjo
collection DOAJ
description An electrocardiogram (ECG) is used to observe the electrical activity of the heart via electrodes on the body surface. Recently, an ECG with fewer electrodes, such as a bipolar ECG in which two electrodes are attached to the chest, has been employed as wearable devices. However, the effect of different geometrical factors and electrode-pair locations on the amplitude and waveform of ECG signals remains unclear. In this study, we computationally evaluated the effects of body morphology, heart size and orientation, and electrode misalignment on ECG signals for 48 scenarios using 35 bipolar electrode pairs (1680 waveforms) with a dynamic time warping (DTW) algorithm. It was observed that the physique of the human body model predominantly affected the amplitude and waveform of the ECG signals. A multivariate analysis indicated that the heart–electrode distance and the solid angle of the heart from the electrode characterized the amplitude and waveform of the ECG signals, respectively. Furthermore, the electrode locations for less individual variability and less waveform distortion were close to the location of electrodes V<sub>2</sub> and V<sub>3</sub> in the standard 12-lead. These findings will facilitate the placement of ECG electrodes and interpretation of the measured ECG signals for wearable devices.
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spelling doaj.art-8a741a983ab4411ba8714f8a899558a92024-03-27T13:28:16ZengMDPI AGBiosensors2079-63742024-03-0114315310.3390/bios14030153Sensitivity of Electrocardiogram on Electrode-Pair Locations for Wearable Devices: Computational Analysis of Amplitude and Waveform DistortionKiyoto Sanjo0Kazuki Hebiguchi1Cheng Tang2Essam A. Rashed3Sachiko Kodera4Hiroyoshi Togo5Akimasa Hirata6Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, JapanDepartment of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, JapanFaculty of Information Science and Electrical Engineering, Kyushu University, Fukuoka 819-0395, JapanGraduate School of Information Science, University of Hyogo, Kobe 650-0047, JapanDepartment of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, JapanNTT Device Innovation Center, NTT Corporation, Atsugi 243-0198, JapanDepartment of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, JapanAn electrocardiogram (ECG) is used to observe the electrical activity of the heart via electrodes on the body surface. Recently, an ECG with fewer electrodes, such as a bipolar ECG in which two electrodes are attached to the chest, has been employed as wearable devices. However, the effect of different geometrical factors and electrode-pair locations on the amplitude and waveform of ECG signals remains unclear. In this study, we computationally evaluated the effects of body morphology, heart size and orientation, and electrode misalignment on ECG signals for 48 scenarios using 35 bipolar electrode pairs (1680 waveforms) with a dynamic time warping (DTW) algorithm. It was observed that the physique of the human body model predominantly affected the amplitude and waveform of the ECG signals. A multivariate analysis indicated that the heart–electrode distance and the solid angle of the heart from the electrode characterized the amplitude and waveform of the ECG signals, respectively. Furthermore, the electrode locations for less individual variability and less waveform distortion were close to the location of electrodes V<sub>2</sub> and V<sub>3</sub> in the standard 12-lead. These findings will facilitate the placement of ECG electrodes and interpretation of the measured ECG signals for wearable devices.https://www.mdpi.com/2079-6374/14/3/153electrocardiogramnumerical human modelscalar-potential finite-difference methodwearable device
spellingShingle Kiyoto Sanjo
Kazuki Hebiguchi
Cheng Tang
Essam A. Rashed
Sachiko Kodera
Hiroyoshi Togo
Akimasa Hirata
Sensitivity of Electrocardiogram on Electrode-Pair Locations for Wearable Devices: Computational Analysis of Amplitude and Waveform Distortion
Biosensors
electrocardiogram
numerical human model
scalar-potential finite-difference method
wearable device
title Sensitivity of Electrocardiogram on Electrode-Pair Locations for Wearable Devices: Computational Analysis of Amplitude and Waveform Distortion
title_full Sensitivity of Electrocardiogram on Electrode-Pair Locations for Wearable Devices: Computational Analysis of Amplitude and Waveform Distortion
title_fullStr Sensitivity of Electrocardiogram on Electrode-Pair Locations for Wearable Devices: Computational Analysis of Amplitude and Waveform Distortion
title_full_unstemmed Sensitivity of Electrocardiogram on Electrode-Pair Locations for Wearable Devices: Computational Analysis of Amplitude and Waveform Distortion
title_short Sensitivity of Electrocardiogram on Electrode-Pair Locations for Wearable Devices: Computational Analysis of Amplitude and Waveform Distortion
title_sort sensitivity of electrocardiogram on electrode pair locations for wearable devices computational analysis of amplitude and waveform distortion
topic electrocardiogram
numerical human model
scalar-potential finite-difference method
wearable device
url https://www.mdpi.com/2079-6374/14/3/153
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