An open access database for evaluating the algorithms of electrocardiogram rhythm and morphology abnormality detection
Over the past few decades, methods for classification and detection of rhythm or morphology abnormalities in ECG signals have been widely studied. However, it lacks the comprehensive performance evaluation on an open database. This paper presents a detailed introduction for the database used for the...
| Main Authors: | , , , , , , , , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2019
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/81375 http://hdl.handle.net/10220/49067 |
| _version_ | 1811688222432952320 |
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| author | Ng, Eddie Yin Kwee Liu, Feifei Liu, Chengyu Zhao, Lina Zhang, Xiangyu Wu, Xiaoling Xu, Xiaoyan Liu, Yulin Ma, Caiyun Wei, Shoushui He, Zhiqiang Li, Jianqing |
| author2 | School of Mechanical and Aerospace Engineering |
| author_facet | School of Mechanical and Aerospace Engineering Ng, Eddie Yin Kwee Liu, Feifei Liu, Chengyu Zhao, Lina Zhang, Xiangyu Wu, Xiaoling Xu, Xiaoyan Liu, Yulin Ma, Caiyun Wei, Shoushui He, Zhiqiang Li, Jianqing |
| author_sort | Ng, Eddie Yin Kwee |
| collection | NTU |
| description | Over the past few decades, methods for classification and detection of rhythm or morphology abnormalities in ECG signals have been widely studied. However, it lacks the comprehensive performance evaluation on an open database. This paper presents a detailed introduction for the database used for the 1st China Physiological Signal Challenge 2018 (CPSC 2018), which will be run as a special section during the ICBEB 2018. CPSC 2018 aims to encourage the development of algorithms to identify the rhythm/morphology abnormalities from 12-lead ECGs. The data used in CPSC 2018 include one normal ECG type and eight abnormal types. This paper details the data source, recording information, patients' clinical baseline parameters as age, gender and so on. Meanwhile, it also presents the commonly used detection/classification methods for the abovementioned abnormal ECG types. We hope this paper could be a guide reference for the CPSC 2018, to facilitate the researchers familiar with the data and the related research advances. |
| first_indexed | 2024-10-01T05:28:47Z |
| format | Journal Article |
| id | ntu-10356/81375 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:28:47Z |
| publishDate | 2019 |
| record_format | dspace |
| spelling | ntu-10356/813752020-03-07T13:19:22Z An open access database for evaluating the algorithms of electrocardiogram rhythm and morphology abnormality detection Ng, Eddie Yin Kwee Liu, Feifei Liu, Chengyu Zhao, Lina Zhang, Xiangyu Wu, Xiaoling Xu, Xiaoyan Liu, Yulin Ma, Caiyun Wei, Shoushui He, Zhiqiang Li, Jianqing School of Mechanical and Aerospace Engineering DRNTU::Engineering::Mechanical engineering Database Electrocardiogram Over the past few decades, methods for classification and detection of rhythm or morphology abnormalities in ECG signals have been widely studied. However, it lacks the comprehensive performance evaluation on an open database. This paper presents a detailed introduction for the database used for the 1st China Physiological Signal Challenge 2018 (CPSC 2018), which will be run as a special section during the ICBEB 2018. CPSC 2018 aims to encourage the development of algorithms to identify the rhythm/morphology abnormalities from 12-lead ECGs. The data used in CPSC 2018 include one normal ECG type and eight abnormal types. This paper details the data source, recording information, patients' clinical baseline parameters as age, gender and so on. Meanwhile, it also presents the commonly used detection/classification methods for the abovementioned abnormal ECG types. We hope this paper could be a guide reference for the CPSC 2018, to facilitate the researchers familiar with the data and the related research advances. 2019-07-02T02:25:44Z 2019-12-06T14:29:33Z 2019-07-02T02:25:44Z 2019-12-06T14:29:33Z 2018 Journal Article Liu, F., Liu, C., Zhao, L., Zhang, X., Wu, X., Xu, X., . . . Ng, E. Y. K. (2018). An open access database for evaluating the algorithms of electrocardiogram rhythm and morphology abnormality detection. Journal of Medical Imaging and Health Informatics, 8(7), 1368-1373. doi:10.1166/jmihi.2018.2442 2156-7018 https://hdl.handle.net/10356/81375 http://hdl.handle.net/10220/49067 10.1166/jmihi.2018.2442 en Journal of Medical Imaging and Health Informatics © 2018 American Scientific Publishers. All rights reserved. |
| spellingShingle | DRNTU::Engineering::Mechanical engineering Database Electrocardiogram Ng, Eddie Yin Kwee Liu, Feifei Liu, Chengyu Zhao, Lina Zhang, Xiangyu Wu, Xiaoling Xu, Xiaoyan Liu, Yulin Ma, Caiyun Wei, Shoushui He, Zhiqiang Li, Jianqing An open access database for evaluating the algorithms of electrocardiogram rhythm and morphology abnormality detection |
| title | An open access database for evaluating the algorithms of electrocardiogram rhythm and morphology abnormality detection |
| title_full | An open access database for evaluating the algorithms of electrocardiogram rhythm and morphology abnormality detection |
| title_fullStr | An open access database for evaluating the algorithms of electrocardiogram rhythm and morphology abnormality detection |
| title_full_unstemmed | An open access database for evaluating the algorithms of electrocardiogram rhythm and morphology abnormality detection |
| title_short | An open access database for evaluating the algorithms of electrocardiogram rhythm and morphology abnormality detection |
| title_sort | open access database for evaluating the algorithms of electrocardiogram rhythm and morphology abnormality detection |
| topic | DRNTU::Engineering::Mechanical engineering Database Electrocardiogram |
| url | https://hdl.handle.net/10356/81375 http://hdl.handle.net/10220/49067 |
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