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A physiological signal database of children with different special needs for stress recognition
Buket Coşkun1, Sevket Ay2, Duygun Erol Barkana3
1Yeditepe University, Faculty of Engineering, Department of Electrical and Electronics Engineering, Istanbul, 34755, Turkey. buket.coskun@yeditepe.edu.tr.
Insights
This study introduces the AKTIVES dataset for stress detection and game reaction analysis in children using physiological signals. The data, collected during game therapy, enables evaluation of stress and reaction detection methods.
Area of Science:
- Biomedical Engineering
- Human-Computer Interaction
- Developmental Psychology
Background:
- Evaluating stress and reactions in children during therapy is crucial for personalized interventions.
- Existing methods for analyzing physiological responses in pediatric populations require robust datasets.
- Game therapy offers a naturalistic setting for collecting behavioral and physiological data.
Purpose of the Study:
- To introduce the AKTIVES dataset for stress detection and game reaction analysis.
- To provide a benchmark for evaluating computational methods using physiological and facial signals.
- To facilitate research on children with developmental disabilities and typically developing peers.
Main Methods:
- Collected physiological data (BVP, EDA, ST) and facial expressions from 25 children during game therapy.
- Included children with obstetric brachial plexus injury, dyslexia, intellectual disabilities, and typically developing children.
- Labeled data based on expert consensus from video recordings for stress and reaction detection.
Main Results:
- The AKTIVES dataset comprises high-quality physiological signals validated for technical accuracy.
- Expert labeling demonstrated consistency, ensuring reliable ground truth for stress and reaction.
- The dataset supports the evaluation of methods for detecting stress and reactions in children.
Conclusions:
- The AKTIVES dataset is a valuable resource for advancing stress detection and game reaction analysis in children.
- This dataset will aid in developing and validating computational models for therapeutic applications.
- Future research can leverage AKTIVES to explore individual differences in physiological responses during gameplay.
Abstract:
This study presents a new dataset AKTIVES for evaluating the methods for stress detection and game reaction using physiological signals. We collected data from 25 children with obstetric brachial plexus injury, dyslexia, and intellectual disabilities, and typically developed children during game therapy. A wristband was used to record physiological data (blood volume pulse (BVP), electrodermal activity (EDA), and skin temperature (ST)). Furthermore, the facial expressions of children were recorded. Three experts watched the children's videos, and physiological data is labeled "Stress/No Stress" and "Reaction/No Reaction", according to the videos. The technical validation supported high-quality signals and showed consistency between the experts.
