학술논문

Design and Implementation of Platform for Collecting Physiological and Psychological Data for Mood Status Inference
Document Type
Conference
Source
2021 International Conference on System Science and Engineering (ICSSE) System Science and Engineering (ICSSE), 2021 International Conference on. :427-432 Aug, 2021
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Mood
Hospitals
Tools
Depression
Physiology
Electroencephalography
Heart rate variability
Mood state inference
EEG
HRV
Psychological
Physiological
Language
ISSN
2325-0925
Abstract
The assessment of mental state is an important issue for diagnosing whether people getting depressed or not. The general assessment tool is to use the Hamilton Depression Rating Scale (HAM-D). In general, psychiatrist utilizes Monthly Mood Chart (MMC) to collect and infer the mental state during the treatment for assessing whether the symptoms relieved or not. But, the MMC is a kind of psychology data. Recently, there is research has developed to evaluate individual emotional and mental state in the way of fusion of psychology and physiology. Therefore, how to effectively and conveniently collect patient's psychological and physiological data to integrate them together has become an important issue. In this paper, we design and implement a platform for collecting data and inferring mental state; the data includes patients' physiological and psychological data, such as Electroencephalography (EEG), Heart Rate Variability (HRV), and MMC. The platform can automatically infer emotional state and provide it to psychiatrists for assessment. This platform is cooperating with psychiatrists in two hospitals and would like to obtain approval. It can be used for the diagnosis of future mental illnesses.