BUILDING A CLOSED-LOOP FOR CHILD EMOTIONAL INTERVENTION: INTEGRATING OPTICAL SENSING, MOTION CAPTURE, AND MULTIMODAL ANALYSIS

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Authors: Xiaoqing Wang
Cited by: 0

Abstract

Aiming at the core pain points in emotional management intervention for children aged 4-12, namely "intrusive physiological data collection, insufficient motion capture accuracy, and disconnection between motion and physiology," this paper relies on a multimodal interactive somatosensory emotional management platform. It integrates optical quantum non-contact sensing, ToF high-precision motion capture, and multimodal motion analysis as three independent technical dimensions to construct a five-element data source system of "physiology-motion-analysis-environment-quantum wave" and optimize the closed-loop of "dimension identification-digital human action-social application." Optical quantum non-contact sensing enables non-invasive collection of heart rate variability (HRV) and electrodermal activity (EDA) with a sampling frequency of 10Hz and data transmission delay below 10ms, increasing the success rate of physiological data collection for special needs children from 60% to 95%. ToF high-precision motion capture, utilizing a 13-megapixel depth camera and self-developed algorithms, supports real-time tracking of 342 human skeletal points with motion accuracy of 0.1mm and response delay under 25ms. Multimodal motion analysis independently processes optical quantum physiological data and ToF motion data through spatiotemporal alignment, feature fusion, and correlation modeling to establish a mapping between motion features, physiological responses, and emotional states, achieving an analysis accuracy of at least 92% and addressing the research gap in motion-physiology integration. Practical application involving 1,500 children across 12 cities in East, North, and South China demonstrates that the collaboration of these three technical dimensions increases the accuracy of children's emotional recognition to 90% (80% for children with autism), improves intervention effectiveness by 29 percentage points, and achieves a skill transfer rate of 80%. This study provides a comprehensive pathway of "non-intrusive collection, high-precision capture, scientific analysis, and full-scene application" for children's emotional management.

Fields of Study & Subjects

Emotion and Mood Recognition Non-Invasive Vital Sign Monitoring Child and Adolescent Psychosocial and Emotional Development

Publication details

Journal / source
Trends in Social Sciences and Humanities Research
Volume
4
Issue
1
Pages
67–79
Publication date
6 March 2026
Language
EN