Classifying Normal and Abnormal Status Based on Video Recordings of Epileptic Patients
Based on video recordings of the movement of the patients with epilepsy, this paper proposed a human action recognition scheme to detect distinct motion patterns and to distinguish the normal status from the abnormal status of epileptic patients. The scheme first extracts local features and holistic...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/459636 |
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| _version_ | 1832563337206956032 |
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| author | Jing Li Xiantong Zhen Xianzeng Liu Gaoxiang Ouyang |
| author_facet | Jing Li Xiantong Zhen Xianzeng Liu Gaoxiang Ouyang |
| author_sort | Jing Li |
| collection | DOAJ |
| description | Based on video recordings of the movement of the patients with epilepsy, this paper proposed a human action recognition scheme to detect distinct motion patterns and to distinguish the normal status from the abnormal status of epileptic patients. The scheme first extracts local features and holistic features, which are complementary to each other. Afterwards, a support vector machine is applied to classification. Based on the experimental results, this scheme obtains a satisfactory classification result and provides a fundamental analysis towards the human-robot interaction with socially assistive robots in caring the patients with epilepsy (or other patients with brain disorders) in order to protect them from injury. |
| format | Article |
| id | doaj-art-0a5b496947f94fc1a503fffb9b5707fe |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-0a5b496947f94fc1a503fffb9b5707fe2025-02-03T01:20:27ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/459636459636Classifying Normal and Abnormal Status Based on Video Recordings of Epileptic PatientsJing Li0Xiantong Zhen1Xianzeng Liu2Gaoxiang Ouyang3Department of Electrical and Automatic Engineering, School of Information Engineering, Nanchang University, Nanchang 330031, ChinaDepartment of Medical Biophysics, University of Western Ontario, Room E5-137, SJHC, 268 Grosvenor Street, London, ON, N6A 4V2, CanadaThe Comprehensive Epilepsy Center, Departments of Neurology and Neurosurgery, Peking University People’s Hospital, Beijing 100044, ChinaState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, ChinaBased on video recordings of the movement of the patients with epilepsy, this paper proposed a human action recognition scheme to detect distinct motion patterns and to distinguish the normal status from the abnormal status of epileptic patients. The scheme first extracts local features and holistic features, which are complementary to each other. Afterwards, a support vector machine is applied to classification. Based on the experimental results, this scheme obtains a satisfactory classification result and provides a fundamental analysis towards the human-robot interaction with socially assistive robots in caring the patients with epilepsy (or other patients with brain disorders) in order to protect them from injury.http://dx.doi.org/10.1155/2014/459636 |
| spellingShingle | Jing Li Xiantong Zhen Xianzeng Liu Gaoxiang Ouyang Classifying Normal and Abnormal Status Based on Video Recordings of Epileptic Patients The Scientific World Journal |
| title | Classifying Normal and Abnormal Status Based on Video Recordings of Epileptic Patients |
| title_full | Classifying Normal and Abnormal Status Based on Video Recordings of Epileptic Patients |
| title_fullStr | Classifying Normal and Abnormal Status Based on Video Recordings of Epileptic Patients |
| title_full_unstemmed | Classifying Normal and Abnormal Status Based on Video Recordings of Epileptic Patients |
| title_short | Classifying Normal and Abnormal Status Based on Video Recordings of Epileptic Patients |
| title_sort | classifying normal and abnormal status based on video recordings of epileptic patients |
| url | http://dx.doi.org/10.1155/2014/459636 |
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