Abstract
Bipolar ECG leads captured from sensors placed in a comfortable wearable-band on the left upper-arm, can provide ECG signals of sufficient quality after signal-enhancement processing, for reliable heart rhythm analysis in long-term ECG-monitoring and enabling clinical arrhythmias assessment. This study presents an inhouse built cable-free, wearable sensor system (WAMECG1) for a bipolar arm-ECG lead capture and wireless data transmission over a Wi-Fi link. The system’s functional blocks were integrated into a comfortable, ergonomically designed arm-band ECG wearable device.
A retrospective pilot analysis on the WASTCArD arm-ECG mapping database from our previous work, was carried out to find the optimal axis rotation of the bipolar arm-Lead electrodes pair, with respect to the body frontal plane and the arm axilla point; this was found to be at -60o axis rotation. Then, signal quality of the recorded far-field bipolar arm-ECG was validated in a pilot trial with 10 volunteer subjects at rest, using the prototype device. The overall R-peak detection accuracy was 99.67%. Without using any signal enhancement algorithm, the average signal-to-noise-ratio (SNR) values was 16.73. Therefore, the performance assessment results assured the performance of the wearable arm-band prototype device.
A retrospective pilot analysis on the WASTCArD arm-ECG mapping database from our previous work, was carried out to find the optimal axis rotation of the bipolar arm-Lead electrodes pair, with respect to the body frontal plane and the arm axilla point; this was found to be at -60o axis rotation. Then, signal quality of the recorded far-field bipolar arm-ECG was validated in a pilot trial with 10 volunteer subjects at rest, using the prototype device. The overall R-peak detection accuracy was 99.67%. Without using any signal enhancement algorithm, the average signal-to-noise-ratio (SNR) values was 16.73. Therefore, the performance assessment results assured the performance of the wearable arm-band prototype device.
| Original language | English |
|---|---|
| Title of host publication | 2020 Computing in Cardiology Proceedings |
| Publisher | Computing in Cardiology |
| Number of pages | 4 |
| Volume | 47 |
| ISBN (Electronic) | 2325-887X |
| DOIs | |
| Publication status | Published (in print/issue) - 15 Dec 2020 |
| Event | Computing in Cardiology 2020 - Rimini Palacongressi, Rimini, Italy Duration: 13 Sept 2020 → 16 Sept 2020 https://www.cinc2020.org/ |
Conference
| Conference | Computing in Cardiology 2020 |
|---|---|
| Abbreviated title | CINC 2020 |
| Country/Territory | Italy |
| City | Rimini |
| Period | 13/09/20 → 16/09/20 |
| Internet address |
Keywords
- wireless arm wearable sensor
- ECG monitoring armband
- bipolar arm-ECG leads
- heart rhythm monitoring
- arm-ECG R peak detection performance
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Armband sensors location assessment for left Arm-ECG bipolar leads waveform components discovery tendencies around the MUAC line
Escalona, O., Mukhtar, S., McEneaney, D. & Finlay, D., 24 Sept 2022, (Published online) In: Sensors (Switzerland). 22, 19, 22 p., 7240.Research output: Contribution to journal › Article › peer-review
Open AccessFile4 Link opens in a new tab Citations (Scopus)136 Downloads (Pure)
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