Human action recognition recorder for assistive robot

The objective of the project is to help elderly or disabled people maintain a healthy mental and physical life by using intelligent robotic systems. My contribution focused on developing a human action recognition method based on 3D skeleton for the Temi assistive robot. I worked directly with the Temi robot platform and developed an Android application that integrates multiple capabilities. The app performs human pose estimation, recognizes basic human actions from the 3D skeleton data, and automatically records the time spent for each action. The system can operate in real-time for immediate feedback and monitoring, or save the data for post-processing analysis. This flexibility enables continuous monitoring and assessment of daily activities, providing valuable data for healthcare professionals and caregivers to track the physical activity patterns of elderly or disabled users.