Status
Ongoing
Year
2026
Team
Hao Wang, Wenshuo Wu, Yuxuan Wang, Ziyun Lin
Collaborators
Department of Nursing, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Civil Affairs Bureau of Nansha District, Guangzhou

Overview

This project aims to construct a multimodal Activities of Daily Living dataset for older adults to support behavioral analysis, digital human modeling, and the development of assistive technologies. First, we will develop an easy-to-use digital ADL assessment system for collecting high-quality motion data in hospitals and nursing homes. Second, through the analysis of full-body gross movements, the project will establish reference tables of motion characteristics and comfort evaluation systems for older adults. These findings will inform the development of age-specific digital human models and support the optimization of age-friendly spatial design. Finally, by integrating ergonomic sensors, the project will enable the analysis of fine movements, biomechanics, and intention recognition. The resulting dataset, models, and evaluation methods will facilitate the training of assistive robots and promote the development of assistive technologies, ultimately improving the quality of life of older adults.

Methods

  • Multimodal motion capture: markerless, optical, and IMU-based MoCap
  • Multimodal data fusion and synchronization
  • Motion feature extraction and statistical analysis
  • Human motion retargeting and digital human modeling
  • Kinematic and dynamic assessment