Sensitivity and Adjustment Model of Electrocardiographic Signal Distortion Based on the Electrodes’ Location and Motion Artifacts Reduction for Wearable Monitoring Applications

Fabian Castaño; Alher Mauricio Hernández

doi:10.20944/preprints202105.0627.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 24 May 2021 / Approved: 26 May 2021 / Online: 26 May 2021 (10:22:00 CEST)

Wearable vital signs monitoring and specially the electrocardiogram have taken important role due to the information that provide about high-risk diseases, it has been evidenced by the needed to increase the health service coverage in home care as has been encouraged by WHO. Some wearables devices have been developed to monitor the ECG in which the location of the measurement electrodes is modified respect to the Einthoven model. However, mislocation of the electrodes on the torso can lead to the modification of acquired signals, diagnostic mistakes and misinterpretation of the information in the signal. This work presents a volume conductor evaluation and an ECG signal waveform comparison when the location of electrodes is changed, to find a electrodes’ location that reduces distortion of interest signals. In addition, effect of motion artifacts and electrodes’ location on the signal acquisition are evaluated. A group of volunteers was recorded to obtain ECG signals, the result was compared with a computational model of the heart behavior through the EA ECG, DTW and SNR methods to quantitatively determine the signal distortion. It was found that while the Einthoven method is followed, it is possible to acquire the ECG signal from the patient’s torso or back without a significant difference, and the electrodes position can be moved 6cm at most from the suggested location by the Einthoven triangle in Mason-Likar’s method.

Sensitivity analysis; Motion artifacts; Electrocardiography; Instrumentation and measurement; Bioelectromagnetism

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Sensitivity and Adjustment Model of Electrocardiographic Signal Distortion Based on the Electrodes’ Location and Motion Artifacts Reduction for Wearable Monitoring Applications

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