May 16, 2014IEEE Journal of Biomedical and Health InformaticsOpen Access

Exploiting Prior Knowledge in Compressed Sensing Wireless ECG Systems

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Population

ECG records from the MIT-BIH Arrhythmia Database

Comparison

Modified model-based CoSaMP and modified… vs Current compressed sensing-based methods and…

Design

Other

Discussion

Member takes

Implication

May support efficient wireless ECG telecardiology; leaves open prospective clinical validation beyond database testing.

Structured PICO

Population

ECG records from the MIT-BIH Arrhythmia Database (specifically 10-min long single leads from records 100, 101, 102, 103, 107, 109, 111, 115, 117, 118, and 119)

Intervention

Modified model-based CoSaMP (MMB-CoSaMP) and modified model-based IHT (MMB-IHT) compressed sensing algorithms exploiting wavelet tree structure and common support between consecutive ECG segments

Comparator

Current compressed sensing (CS)-based methods (BPDN, BSBL) and state-of-the-art wavelet-based algorithms (SPIHT)

Outcome

Compression rate and reconstruction quality of the ECG signals

Exploiting the wavelet structure and common support of consecutive ECG segments in compressed sensing algorithms significantly improves ECG compression rates and reconstruction quality for wireless telecardiology.

Cite This Study

A 2014 study studied this question.

synapsesocial.com/papers/6a7df89c4d9a7e00d75ca7dc https://doi.org/10.1109/jbhi.2014.2325017

View Full Paper

Ask AI

Bookmark

Exploiting Prior Knowledge in Compressed Sensing Wireless ECG Systems

Discussion

Member takes

Implication

Structured PICO

Cite This Study

Exploiting Prior Knowledge in Compressed Sensing Wireless ECG Systems

Discussion

Member takes

Implication

Structured PICO

Cite This Study

Also Consider

Also Consider