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ITEA is the Eureka Cluster on software innovation
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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
Email
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)