Evaluating Dry Electrodes and Bioinstrumentation for Wearable Arm ECG Acquisition

Arm-based electrocardiogram (ECG) offers a more comfortable and user-friendly alternative to traditional chest ECG for wearable cardiac monitoring in daily health applications. However, arm ECG faces challenges such as capturing extremely low-amplitude signals in the microvolt range and significant electromyogram (EMG) noise contamination. The aim of this study was to evaluate the performance of dry electrodes for arm and chest ECG monitoring using gold standard BIOPAC and proposed mDAQ systems. This study consisted of two phases. In Phase 1, we evaluated different dry electrode materials, including silver knit fabric and gold-plated electrodes, with six healthy adult participants (N = 3 males and N = 3 females) having upper arm circumference ranging from 27 to 42 cm. We used a BIOPAC system as a gold standard to collect arm ECG, upper arm EMG, and reference chest ECG during standardized movement tasks. Results showed that silver knit electrodes demonstrated superior QRS energy (0.705 ± 0.151), surpassing chest gel floating ECG QRS energy (0.328 ± 0.026), with lower EMG interference across movement conditions. In Phase 2, we developed a bioinstrumentation system (mDAQ) optimized for dry electrodes, demonstrating reliable ECG acquisition in both chest Lead I and arm configurations. We validated our bioinstrumentation with sixteen healthy adult participants (N = 8 male and N = female). The mDAQ system maintained high signal consistency with a skewness effect size of 0.963 and showed a mean heart rate bias of only -1.842 bpm compared to the BIOPAC system, confirming its viability for wearable ECG monitoring applications.

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Published
2024-11-19
DOI
https://doi.org/10.23919/e-textiles63767.2024.10914169
Citations
1
Primary Topic
Neuroscience and Neural Engineering
Type
article
Field-Weighted Citation Impact
0.27

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Evaluating Dry Electrodes and Bioinstrumentation for Wearable Arm ECG Acquisition

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article

Evaluating Dry Electrodes and Bioinstrumentation for Wearable Arm ECG Acquisition

K. Venkatasubramanian, Stephanie Carreiro, Yalda Shahriari, Kunal Mankodiya, Shubham Chomal, Dhaval Solanki, Vignesh Ravichandran, Suparna Veeturi, Alex Cerullo
article en
1 citations

Abstract

Arm-based electrocardiogram (ECG) offers a more comfortable and user-friendly alternative to traditional chest ECG for wearable cardiac monitoring in daily health applications. However, arm ECG faces challenges such as capturing extremely low-amplitude signals in the microvolt range and significant electromyogram (EMG) noise contamination. The aim of this study was to evaluate the performance of dry electrodes for arm and chest ECG monitoring using gold standard BIOPAC and proposed mDAQ systems. This study consisted of two phases. In Phase 1, we evaluated different dry electrode materials, including silver knit fabric and gold-plated electrodes, with six healthy adult participants (N = 3 males and N = 3 females) having upper arm circumference ranging from 27 to 42 cm. We used a BIOPAC system as a gold standard to collect arm ECG, upper arm EMG, and reference chest ECG during standardized movement tasks. Results showed that silver knit electrodes demonstrated superior QRS energy (0.705 ± 0.151), surpassing chest gel floating ECG QRS energy (0.328 ± 0.026), with lower EMG interference across movement conditions. In Phase 2, we developed a bioinstrumentation system (mDAQ) optimized for dry electrodes, demonstrating reliable ECG acquisition in both chest Lead I and arm configurations. We validated our bioinstrumentation with sixteen healthy adult participants (N = 8 male and N = female). The mDAQ system maintained high signal consistency with a skewness effect size of 0.963 and showed a mean heart rate bias of only -1.842 bpm compared to the BIOPAC system, confirming its viability for wearable ECG monitoring applications.

Vol. 2024
University of Massachusetts Chan Medical School (US), University of Rhode Island (US)
National Institutes of Health, National Institute of Biomedical Imaging and Bioengineering
Affordable and clean energy
Openalex Percentile: Top 41%
Neuroscience and Neural Engineering
0.27
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