Sustainability and predictive accuracy evaluation of gel and embroidered electrodes for ECG monitoring

• DOI: 10.1016/j.bspc.2024.106632
• Publication Date: 2024-07-18T15:30:47Z
• Authors: Ghada Ben Othman; Atal Anil Kumar; Faten Ben Hassine; Dana Copot; Lilia Sidhom; Ernest N. Kamavuako; Mohamed Trabelsi; Clara Mihaela Ion...; Inès Chihi
• Keywords: SIGNAL (programming language); Interface (matter); Instrumentation

Despite standards on electrocardiogram (ECG) monitoring in medical diagnostics, signal acquisition is prone to noisy artifacts and relies greatly the quality of skin contact transducing interference. Electrodes, serving as indispensable conduits ECG acquisition, act crucial interface between human body recording instrumentation. The usage traditional gel electrodes may provoke irritation, by contrast, advent embroidered electrodes, a contemporary innovation, holds promise more comfort monitoring. However, sustainability quotient predictive precision these novel require in-depth investigation. This paper endeavours comprehensive evaluation both concerning acquisition. Simultaneously, study aims construct polynomial regression model leveraging advanced machine learning (ML) tools. inferred predicts signals based experimental data obtained from electrodes. methodology encompasses systematic collection, preprocessing, insightful analysis, application data-driven techniques. findings this highlight viability compelling alternative, transcending paradigms. Employing ML tools, developed achieves accuracy, reflected robust R2 values extending up 94.9%.