Wearable Electrocardiogram Quality Assessment Using Wavelet Scattering and LSTM.

ABSTRACT: As the fast development of wearable devices and Internet of things technologies, real-time monitoring of ECG signals is quite critical for cardiovascular diseases. However, dynamic ECG signals recorded in free-living conditions suffered from extremely serious noise pollution. Presently, most algorithms for ECG signal evaluation were designed to divide signals into acceptable and unacceptable. Such classifications were not enough for real-time cardiovascular disease monitoring. In the study, a wearable ECG quality database with 50,085 recordings was built, including A/B/C (or high quality/medium quality/low quality) three quality grades (A: high quality signals can be used for CVD detection; B: slight contaminated signals can be used for heart rate extracting; C: heavily polluted signals ne

SUBMITTER: Liu F 

PROVIDER: S-EPMC9281614 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature