A Physiotherapy Video Matching Method Supporting Arbitrary Camera Placement Via Angle-Of-Limb-Based Posture Structures
Jiunn-Wu Lin, Yao-Sheng Chou, Yun Pin Huang, Min-Hsiung Hung, Ming-Hung Kao, Jia Ji, Lin-Yi Jiang, Pi Wei Chen
Abstract
The “Hospital at Home” initiative transforms medical service automation through modern technologies. This paper revisits remote physiotherapy, allowing convalescents to record exercises using mobile devices from arbitrary angles. To address this, we propose a physiotherapy video matching method that accurately aligns movements from unconstrained viewpoints. The task is formulated as an optimization problem and solved using a modular pipeline. We introduce the Angle-of-Limb-based Posture Structure (ALPS) and the Camera-Angle-Free (CAFE) transformation to counter camera-angle differences. We also develop the Three-phase ALPS Matching Algorithm (TALMA) for matching movements between mentor and convalescent videos. Real-world experiments show our method outperforms existing solutions in both precision and practicality, with a time deviation of less than 0.07 seconds from expert annotations. The prototype and datasets are publicly available at: https://github.com/NCKU-CIoTlab/TALMA-on-ALPS/.