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Algorithm for Mobile Platform-Based Real-Time QRS Detection.


ABSTRACT: Recent advancements in smart, wearable technologies have allowed the detection of various medical conditions. In particular, continuous collection and real-time analysis of electrocardiogram data have enabled the early identification of pathologic cardiac rhythms. Various algorithms to assess cardiac rhythms have been developed, but these utilize excessive computational power. Therefore, adoption to mobile platforms requires more computationally efficient algorithms that do not sacrifice correctness. This study presents a modified QRS detection algorithm, the AccYouRate Modified Pan-Tompkins (AMPT), which is a simplified version of the well-established Pan-Tompkins algorithm. Using archived ECG data from a variety of publicly available datasets, relative to the Pan-Tompkins, the AMPT algorithm demonstrated improved computational efficiency by 5-20×, while also universally enhancing correctness, both of which favor translation to a mobile platform for continuous, real-time QRS detection.

SUBMITTER: Neri L 

PROVIDER: S-EPMC9920820 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Algorithm for Mobile Platform-Based Real-Time QRS Detection.

Neri Luca L   Oberdier Matt T MT   Augello Antonio A   Suzuki Masahito M   Tumarkin Ethan E   Jaipalli Sujai S   Geminiani Gian Angelo GA   Halperin Henry R HR   Borghi Claudio C  

Sensors (Basel, Switzerland) 20230202 3


Recent advancements in smart, wearable technologies have allowed the detection of various medical conditions. In particular, continuous collection and real-time analysis of electrocardiogram data have enabled the early identification of pathologic cardiac rhythms. Various algorithms to assess cardiac rhythms have been developed, but these utilize excessive computational power. Therefore, adoption to mobile platforms requires more computationally efficient algorithms that do not sacrifice correct  ...[more]

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