The performance of a low-power single-lead armband in generating electrocardiogram (ECG) signals from the chest and left arm was validated against a BIOPAC MP160 benchtop system in real-time. The filtering performance of three adaptive filtering algorithms, namely least mean squares (LMS), recursive least squares (RLS), and extended kernel RLS (EKRLS) in removing white (W), power line interference (PLI), electrode movement (EM), muscle artifact (MA), and baseline wandering (BLW) noises from the chest and left-arm ECG was evaluated with respect to the mean squared error (MSE). Filter parameters of the used algorithms were adjusted to ensure optimal filtering performance. LMS was found to be the most effective adaptive filtering algorithm in removing all noises with minimum MSE. However, for removing PLI with a maximal signal-to-noise ratio (SNR), RLS showed lower MSE values than LMS when the step size was set to 1 × 10⁻⁵. We proposed a transformation framework to convert the denoised left-arm and chest ECG signals to their low-MSE and high-SNR surrogate chest signals. With wide applications in wearable technologies, the proposed pipeline was found to be capable of establishing a baseline for comparing left-arm signals with original chest signals, getting one step closer to making use of the left-arm ECG in clinical cardiac evaluations.

Electrocardiography (ECG) is an essential technique to assess cardiovascular conditions and monitor physical activities. While the concept is mature, issues surrounding sampling convenience and device adoption as well as maintaining signal quality under artifacts remain a problem. In this article, we present a high-performing wearable ECG armband on the upper left arm. It is equipped with miniaturized hardware, capable of data storage and wireless communication. We evaluate different electrode configurations by conducting ECG measurements both at the static state and under motion and using improved algorithms to quantify data quality and assess the agreement between the proposed new technique and the gold standard. The optimal electrode position is determined by balancing wearable suitability and signal quality. We propose an electronic textile (E-textile) armband with improved design. It offers favorable wearing comfort and a fashionable appearance without sacrificing data quality. Its contact pressure is measured to get a better picture of intimacy and clothing comfort. Our system provides real-time and noise-resilient ECG data without interrupting daily life and can be implemented in use cases that warrant continuous ECG monitoring.