Study of the Sine-SSA-BP Model in Classification of Cognitive Impairment by Eye Movement Features for Patients with Epilepsy | |
Wei, Xiaojie1,2; Zhang, Huangyemin1,2; Wen, Shirui3; Zhu, Guangpu1,2![]() ![]() | |
2023-10-20 | |
会议名称 | 4th International Symposium on Artificial Intelligence for Medicine Science, ISAIMS 2023 |
会议录名称 | Proceedings of 2023 4th International Symposium on Artificial Intelligence for Medicine Science, ISAIMS 2023 |
页码 | 585-590 |
会议日期 | 2023-10-20 |
会议地点 | Hybrid, Chengdu, China |
出版者 | Association for Computing Machinery |
产权排序 | 1 |
摘要 | Most studies reported that patients with epilepsy could suffer from attention dysfunction and other social cognitive impairment but there were few studies on automatic detection for patients with epilepsy of cognitive impairment based on eye-tracking technology. The current study aimed to explore objective and nontraumatic method of assisting in the detection of patients with epilepsy of cognitive impairment. Thirty-seven patients with epilepsy of cognitive impairment and twenty-nine healthy controls performed the Attention Network Test (ANT) based on eye-tracking technology. The random forest algorithm combined with the principal component analysis was applied to extract the main eye-tracking features, and then the back propagation neural network model was carried out to identify patients with epilepsy of cognitive impairment. To improve the accuracy of the classification model, the sparrow search algorithm (SSA) with Sine chaotic mapping was used to optimize the initial weight and threshold of the back propagation (BP) network. The results showed that compared with the BP network accuracy of 60.00% and the BP network optimized by the SSA accuracy of 90.45%, the BP network optimized by SSA with Sine chaotic mapping had the higher classification accuracy of 96.67%. It proved that Sine-SSA-BP based on eye-tracking features can facilitate early detection for patients with epilepsy of cognitive impairment. © 2023 ACM. |
关键词 | Epilepsy Cognitive impairment Eye-tracking Sine chaotic mapping Sparrow search algorithm Back propagation neural network |
作者部门 | 光谱成像技术研究室 |
DOI | 10.1145/3644116.3644213 |
收录类别 | EI |
ISBN号 | 9798400708138 |
语种 | 英语 |
EI入藏号 | 20241715970308 |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/97435 |
专题 | 光谱成像技术研究室 |
通讯作者 | Wang, Quan; Feng, Li |
作者单位 | 1.Key Laboratory of Spectral Imaging Technology, Xi'an Institute of Optics and Precision Mechanics of Chinese Academy of Sciences, Xi'an, China; 2.University of Chinese Academy of Sciences, Beijing, China; 3.Department of Neurology, Xiangya Hospital, Central South University, Changsha, China |
推荐引用方式 GB/T 7714 | Wei, Xiaojie,Zhang, Huangyemin,Wen, Shirui,et al. Study of the Sine-SSA-BP Model in Classification of Cognitive Impairment by Eye Movement Features for Patients with Epilepsy[C]:Association for Computing Machinery,2023:585-590. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Study of the Sine-SS(542KB) | 会议论文 | 限制开放 | CC BY-NC-SA | 请求全文 |
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