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ECG abnormality det...
ECG abnormality detection Based on Multi-domain combination features and LSTM
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- Liu, Qingshan (författare)
- Anhui Jianzhu University, Power Quality Analysis and Load Detection Technology Laboratory, Hefei, China
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- Gao, Cuiyun (författare)
- Anhui Jianzhu University, Power Quality Analysis and Load Detection Technology Laboratory, Hefei, China
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- Zhao, Yang (författare)
- Anhui Jianzhu University, Power Quality Analysis and Load Detection Technology Laboratory, Hefei, China
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- Huang, Songqun (författare)
- Second Military Medical University, Department of Cardiovasology Changhai Hospital, Shanghai, China
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- Zhang, Yuqing (författare)
- Anhui Jianzhu University, Power Quality Analysis and Load Detection Technology Laboratory, Hefei, China
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- Lu, Zhonghai (författare)
- KTH,Elektronik och inbyggda system
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(creator_code:org_t)
- Institute of Electrical and Electronics Engineers (IEEE), 2023
- 2023
- Engelska.
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Ingår i: 2023 4th International Conference on Computer Engineering and Application, ICCEA 2023. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 565-569
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Most scholars use fixed-length sample to ECG abnormalities based on MIT-BIH dataset, which lead to information loss. To address this problem, this paper proposes a method for ECG abnormality detection based on TSH-L method. The TSH-L method include:(1) Use the 3R ECG sample selection method to select ECG samples.(2) Extract multi-domain combination features including time-domain features, frequency domain features and time-frequency domain features.(3) LSTM is used for classification, and the algorithm is trained and tested based on the MIT-BIH dataset, obtain relatively optimal features as spliced normalized fusion features including kurtosis, skewness and RR interval time domain features, STFT-based sub-band spectrum features, and harmonic ratio features. Experiments show that: TSH-L method proposed in the paper has a high accuracy of 97.74% for the detection of ECG abnormalities of MIT-BIH dataset. The method 3R-TSH-L proposed in this paper is expected to be widely used in family-oriented healthcare.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Annan elektroteknik och elektronik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Other Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)
Nyckelord
- 3R ECG samples
- ECG abnormality
- MIT-BIH
- Multi-domain combination features
- TSH-L
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)