The electrocardiogram (ECG) is one of the most important physiological signals to monitor the health status of a patient. Technological advances allow the size and weight of ECG acquisition devices to be strongly reduced so that wearable systems are now available, even though the computational power and memory capacity is generally limited. An ECG signal is affected by several artifacts, among which the baseline wandering (BW), i.e., a slowly varying variation of its trend, represents a major disturbance. Several algorithms for BW removal have been proposed in the literature. In this paper, we propose new methods to face the problem that require low computational and memory resources and thus well comply with a wearable device implementation.
Adaptive quadratic regularization for baseline wandering removal in wearable ECG devices / Argenti, F.; Facheris, L.; Giarrè, Laura. - (2016). (Intervento presentato al convegno 2016 24th European Signal Processing Conference (EUSIPCO) tenutosi a Budapest nel Settembre 2016) [10.1109/EUSIPCO.2016.7760542].