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Biosignal and survey-based mental health AI model creation tool
- Project
- 18033 Mad@Work
- Type
- Enhancement
- Description
This result is a tool that creates a biosignal stress model and a questionnaire-based stress model needed for a mental health management system to predict stress based on PPG and questionnaires.
- Contact
- Hyunsuk Kim
- hyskim@etri.re.kr
- Research area(s)
- Mental Health Measurement
- Technical features
Users can create Linear Regression, SVM (Support Vector Machine), Decision Tree, Random Forest, Gradient Boosting, and XGBoost models using PPG data. Users can train survey data to create KNN, Decision Tree, Ada Boost, Gradient Boosting, Light GBM, Random Forest, Logistic Regression, and SVM models.
- Integration constraints
Python
- Targeted customer(s)
Mental health management and work stress measurement SW developers and companies
- Conditions for reuse
It can be used after signing a commercial technology transfer agreement. (https://itec.etri.re.kr/itec/main/index.do)
- Confidentiality
- Public
- Publication date
- 10-10-2023
- Involved partners
- ETRI (Electronics and Telecommunications Research Institute) (KOR)