Year: 2024
Type: conference-paper
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.
Authors: Suparna Veeturi, Vignesh Ravichandran, Alex Cerullo, Shubham Chomal, Yalda Shahriari, Stephanie Carreiro, Krishna Venkatasubramanian, Kunal Mankodiya, Dhaval Solanki
Language: English
Topic: ECG Monitoring and Analysis
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: green
Award: G1584987017
OpenAlex ID: W4408443116
