Markerless Behavior Monitoring System for Diagnosis Support of Developmental Disorder Symptoms in Children
- Resource Type
- Conference
- Authors
- Putra, Prasetia Utama; Shima, Keisuke; Hotchi, Sayaka; Shirnatani, Koji
- Source
- 2021 21st International Conference on Control, Automation and Systems (ICCAS) Control, Automation and Systems (ICCAS), 2021 21st International Conference on. :1784-1787 Oct, 2021
- Subject
- Aerospace
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Automation
Computational modeling
Toy manufacturing industry
Petri nets
Feature extraction
Cameras
Control systems
Autism Spectrum Disorder
Behavior Monitoring
Petri-Net
- Language
- ISSN
- 2642-3901
This study presents a markerless behavior evaluation system employing multiple RGB cameras and Kinect V2 sensors to assists clinicians in identifying disorder symptoms in children. The system utilizes OpenPTrack with Kinect sensors to track children's and toys' positions and records their activity using RGB cameras. Children's activity was estimated by computing the distance between them and the toys. Children's behavior was modeled with a Petri net, and four features were extracted from the model. We conducted preliminary experiments with four typical and three ASD disorder children. The experimental results demonstrated that the frequency of changing activity and playing alone was more informative than the others to distinguish ASD children from the typical ones.