Rincon Vallejos, Francisco JavierRecas Piorno, JoaquinKhaled, NadiaAtienza Alonso, David2011-08-102011-08-102011-08-10201110.1109/TITB.2011.2163943https://infoscience.epfl.ch/handle/20.500.14299/69957WOS:000297355000007This work is devoted to the evaluation of multilead digital wavelet transform (DWT)-based electrocardiogram (ECG) wave delineation algorithms, which were optimized and ported to a commercial wearable sensor platform. More specifically, we investigate the use of root-mean squared (RMS)-based multi-lead followed by a single-lead online delineation algorithm, which is based on a state-of-the-art offline singlelead delineator. The algorithmic transformations and software optimizations necessary to enable embedded ECG delineation notwithstanding the limited processing and storage resources of the target platform are described, and the performance of the resulting implementations are analyzed in terms of delineation accuracy, execution time and memory usage. Interestingly, RMS-based multi-lead delineation is shown to perform equivalently to the best single-lead delineation for the 2-lead QT database (QTDB), within a fraction of a sample duration of the Common Standards for Electrocardiography (CSE) committee tolerances. Finally, a comprehensive evaluation of the energy consumption entailed by the considered algorithms is proposed, which allows very relevant insights into the dominant energy-draining functionalities and which suggests suitable design guidelines for longlasting wearable ECG monitoring systems.ECGembedded systemsambulatory electrocardiogrammulti-leaddelineationdigital wavelet transformwireless sensor nodeWBSNbody area networksenergy-constrained systemsreal-timesystem-level designsingle-leadenergy optimizationtext::journal::journal article::research article