SHENZHEN SAYES MEDICAL TECHNOLOGY CO., LTD.;SOUTH CHINA UNIVERSITY OF TECHNOLOGY
发明人:
Rongqian Yang,Xiuwen Chen,Ruixue Lv,Chuanxu Song
申请号：
US15109815
公开号：
US20170238858A1
申请日:
2015.10.29
申请国别(地区):
US
年份:
2017
代理人:
摘要：
The present invention discloses a depression assessment system based on physiological information, comprising an information acquisition module, a signal processing module, a parameters calculation module, a feature selection module, a machine learning module and an output result module. The present invention further discloses a depression assessment method based on various physiological information, comprising the following steps: 1, processing electrocardiogram (ECG) signal and one or more of photoplethysmography (PPG) signal, electroencephalogram (EEG) signal, galvanic skin response (GSR)signal, electrogastrography (EGG) signal, electromyogram (EMG) signal, electrooculogram (EOG) signal, polysomnogram (PSG) signal and temperature signal, and calculating signal parameters； 2, normalizing the obtained signal parameters, and performing the feature selection on parameters set formed by the normalized signal parameters to obtain feature parameters set； and 3, performing machine learning by utilizing the obtained feature parameters set, and establishing a depression assessment mathematic model to assess the depression level by utilizing a relationship between the feature parameters set and the depression level. The present invention has the advantage that the subjectivity of the assessment by utilizing the depression rating scale can be avoided.
