Wrist and arm body surface bipolar ECG leads signal and sensor study for long-term rhythm monitoring

2017 Computing in Cardiology (CinC)(2017)

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摘要
With cardiovascular disease and heart arrhythmias continuing to have a high mortality rate, it is important to monitor the electrocardiogram (ECG) signal in a noninvasive, long-term wearable device. In this study we investigate sensors and the ECG signal-to-noise ratio map along the left arm, for wearable arm-ECG monitoring devices. In a pilot study, 11 subjects attending a cardiology outpatient clinic, far-field left-arm ECG recordings included signals from a combination of dry and special pre-gelled BIS-Quatro™ sensor system, axially and transversally oriented along the left arm: on the wrist, upper forearm and upper arm. A total of 10 bipolar leads were recorded simultaneously (using 18 acquisition channels). Each subject was recorded for 8 minutes at rest, using the bio-potential acquisition system; all data was imported and processed using Matlab and MS Excel. Analysis was completed to evaluate signal-to-noise ratio (SNR) distribution maps. An average ECG SNR figure of 42.63 was found in the dry-electrode positioned on the upper arm bipolar lead, whilst the SNR ratio positioned on the wrist was 13.14. Similar to this, in the BIS-electrodes (gelled), there was an average ECG SNR figure of 89.25 on the upper arm and of 5.18 positioned on the wrist. This study clinically evidenced the ECG S/N map on the left arm. It reveals that bipolar arm-ECG SNR are consistently stronger on the upper arm, when recorded with the gelled BIS sensors.
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arm body surface bipolar ECG,sensor study,cardiovascular disease,heart arrhythmias,electrocardiogram signal,ECG signal-to-noise ratio map,wearable arm-ECG monitoring devices,left-arm ECG recordings,bio-potential acquisition system,signal-to-noise ratio distribution maps,bipolar arm-ECG SNR,gelled BIS sensors,rhythm monitoring,wris tbody surface bipolar ECG,dry pre-gelled BIS-Quatro sensor system,special pre-gelled BIS-Quatro sensor system,ECG S-N map,Matlab,MS Excel
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