Invention Grant
- Patent Title: GPU-based parallel electrocardiogram signal analysis method, computer readable storage medium and device
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Application No.: US15389978Application Date: 2016-12-23
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Publication No.: US10258250B2Publication Date: 2019-04-16
- Inventor: Ye Li , Xiaomao Fan , Furu Xiang , Yunpeng Cai , Fen Miao
- Applicant: SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY CHINESE ACADEMY OF SCIENCES
- Applicant Address: CN Shenzhen, Guangdong
- Assignee: SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY CHINESE ACADEMY OF SCIENCES
- Current Assignee: SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY CHINESE ACADEMY OF SCIENCES
- Current Assignee Address: CN Shenzhen, Guangdong
- Agency: Hamre, Schumann, Mueller & Larson, P.C.
- Main IPC: A61B5/04
- IPC: A61B5/04 ; A61B5/0456 ; A61B5/00 ; A61B5/0472

Abstract:
The present disclosure provides a GPU-based parallel electrocardiogram signal analysis method, comprising: performing a filtering process of electrocardiogram signals through a long interval artifact removal and a short interval artifact removal; performing a QRS detection of the filtering-processed electrocardiogram signals through an R-wave position extraction, a QRS complex start and end positions extraction and a QRS complex width extraction; performing an abnormal waveform classification of the QRS-detected electrocardiogram signals through template creation; wherein at least one of the long interval artifact removal, the short interval artifact removal, the R-wave position extraction, the QRS complex width extraction and the creation template is performed by a multiple threads at a GPU device side in parallel, any thread being read through its unique index number to process corresponding data. By executing one or more steps of the electrocardiogram signal analysis at GPU in parallel, the present disclosure increases the analysis speed of the electrocardiogram signals.
Public/Granted literature
- US20170105643A1 GPU-BASED PARALLEL ELECTROCARDIOGRAM SIGNAL ANALYSIS METHOD, COMPUTER READABLE STORAGE MEDIUM AND DEVICE Public/Granted day:2017-04-20
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