August 15, 2011Open Access

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

Q: What is the clinical evidence from this study?

Study design: Other. Population: Electrocardiogram (ECG) monitoring (n=105). Intervention: RMS-based multilead wavelet-based ECG delineation algorithm vs. Single-lead delineation algorithm. Primary outcome: Delineation accuracy (mean error and standard deviation of characteristic wave boundaries).

Key Result

The RMS-based multilead delineation algorithm performed equivalently to the best single-lead delineation for the 2-lead QT database, operating within a fraction of a sample duration of the CSE committee tolerances.

Structured PICO

Population

105 records of 15-minute two-lead ECG recordings from the QT database, spanning 3,600 beats with manual annotations by expert cardiologists.

Intervention

RMS-based multilead digital wavelet transform (DWT)-based ECG wave delineation algorithms optimized for the Shimmer embedded wearable sensor platform.

Comparator

State-of-the-art offline single-lead delineator and online single-lead delineation.

Outcome

Delineation accuracy (sensitivity, positive predictivity, mean error, standard deviation of error), execution time, and memory usage.surrogate

Optimized RMS-based multilead DWT algorithms enable accurate, real-time ECG wave delineation on low-power wearable sensor nodes.

Limitations

Validation limited to 2-lead ECG excerpts due to memory limitations of the target embedded sensor platform
Needs extension to higher dimensional excerpts to fully evaluate performance and advantage of multilead delineation

Abstract

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.

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Cite This Study

Rincón et al. (Mon,) conducted a other in Electrocardiogram (ECG) monitoring (n=105). RMS-based multilead wavelet-based ECG delineation algorithm vs. Single-lead delineation algorithm was evaluated on Delineation accuracy (mean error and standard deviation of characteristic wave boundaries). The RMS-based multilead delineation algorithm performed equivalently to the best single-lead delineation for the 2-lead QT database, operating within a fraction of a sample duration of the CSE committee tolerances.

synapsesocial.com/papers/6a26c6fbfe746c3205c4a3cd https://doi.org/https://doi.org/10.1109/titb.2011.2163943

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