Implementation of a deep learning model for emotion evaluation based on LSTM psychological and physiological data

Yen Wei Ting, Yun Jie Zhang, Kuo Hsuan Chung, Yue Shan Chang

研究成果: 書貢獻/報告類型會議貢獻

摘要

Evaluating mental status is an important issue that diagnosing depression. Hamilton Depression Rating Scale (HAM-D) is a common method to diagnosis depression. Generally, psychiatrists collect Monthly Mood Chart (MMC) to infer mental status of patients during treatments. However, the processes waste a lot of time. Therefore, our target is to find a method that can evaluate mental status faster. We'd used the constructed platform[15] to collect physiological and psychological data. We'd collected 91 data including 42 remission data and 49 non-remission data. We'd used Electroencephalography(EEG) to train LSTM model, and then got 70% accuracy. This model can automatically infer mood status that helping psychiatrists evaluating. This system had coordinated with two hospitals to refer mood status in the future.
原文英語
主出版物標題2021 International Automatic Control Conference, CACS 2021
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781665444125
DOIs
出版狀態已發佈 - 2021
事件2021 International Automatic Control Conference, CACS 2021 - Chiayi, 臺灣
持續時間: 11月 3 202111月 6 2021

出版系列

名字2021 International Automatic Control Conference, CACS 2021

會議

會議2021 International Automatic Control Conference, CACS 2021
國家/地區臺灣
城市Chiayi
期間11/3/2111/6/21

ASJC Scopus subject areas

  • 人工智慧
  • 航空工程
  • 汽車工程
  • 控制與系統工程
  • 控制和優化

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