Development and Evaluation of Multilead Wavelet-Based ECG Delineation Algorithms for Embedded Wireless Sensor Nodes

• Published in: IEEE transactions on information technology in biomedicine Vol. 15; no. 6; pp. 854 - 863
• Main Authors: Rincón, F., Recas, J., Khaled, N., Atienza, D.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.11.2011
• Subjects: Algorithms; Ambulatory electrocardiogram; Biomedical monitoring; Databases, Factual; delineation; Diagnosis, Computer-Assisted - methods; digital wavelet transform; Electrocardiography; Electrocardiography - methods; Electrocardiography, Ambulatory - methods; energy-constrained systems; Humans; multilead; Real time systems; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Wavelet Analysis; Wavelet transforms; Wireless communication; Wireless sensor networks; wireless sensor node; Wireless Technology - instrumentation
• ISSN: 1089-7771; 1558-0032; 1558-0032
• DOI: 10.1109/TITB.2011.2163943

This 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 multilead followed by a single-lead online delineation algorithm, which is based on a state-of-the-art offline single-lead 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 multilead 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 long-lasting wearable ECG monitoring systems.