A physiological signal database of children with different special needs for stress recognition

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.

Fig. 1

Becure CatchAPet.

Fig. 2

Becure LeapBall.

Fig. 3

Experimental design.

Fig. 4

Experimental setup. The parents of the children signed written permission for the child’s picture to be included in this publication.

Fig. 5

Examples of data available in the AKTIVES Dataset; (a) Physiological signals recorded with Empatica E4: BVP, EDA, ST (b) 3 sample video frames of a child (c) The facial emotions are detected as neural for the first two columns and sad for the third column with FER library. The faces are cropped for better visualization, and the facial landmarks are generated with the Dlib PyPI library. The children’s parents gave written consent to include her image in this publication.