March 4, 2016PLoS ONEOpen Access

Simple and Robust Realtime QRS Detection Algorithm Based on Spatiotemporal Characteristic of the QRS Complex

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Population

MIT-BIH arrhythmia database and AHA ECG database (a total of 435,700 beats)

Design

Other

Authors

JKJinkwon KimYonsei University Health System

Discussion

Member takes

Implication

Supports real-time QRS detection in noisy ECGs; leaves open prospective clinical validation.

Structured PICO

Population

MIT-BIH arrhythmia database and AHA ECG database (a total of 435,700 beats)

Intervention

Realtime QRS detection algorithm based on the dual criteria of the amplitude and duration of QRS complex

Outcome

Sensitivity (SE) and positive predictivity value (PPV) of QRS detectionsurrogate

The proposed simple and robust realtime QRS detection algorithm demonstrates high sensitivity and positive predictive value, even in noisy environments.

Cite This Study

Jinkwon Kim (2016) studied this question.

synapsesocial.com/papers/6a8d17e1851ec846c20e5758 https://doi.org/10.1371/journal.pone.0150144

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Simple and Robust Realtime QRS Detection Algorithm Based on Spatiotemporal Characteristic of the QRS Complex

Discussion

Member takes

Implication

Structured PICO

Cite This Study

Simple and Robust Realtime QRS Detection Algorithm Based on Spatiotemporal Characteristic of the QRS Complex

Discussion

Member takes

Implication

Structured PICO

Cite This Study

Also Consider

Also Consider