This paper presents the ongoing development of the Intelligent Health Promotion Service System, a joint Taiwanese-Czech project focused on remote rehabilitation solutions. The system combines a multi-sensor smart orthosis with serious game integration for patient motivation. Our primary targets are aging populations with sarcopenia and potentially dementia, undergoing long-term home rehabilitation. Methodology: We focus on three key areas: Camera-based motion capture and analysis: We utilize a single 2D camera for movement capture, enabling a versatile and cost-effective solution. Machine learning models trained by physiotherapist evaluations are used for automated assessment, comparable to human raters. Reconditioning for bedridden patients: This solution provides passive reconditioning for ICU patients with limited mobility. It allows for rehabilitation in existing hospital beds, minimizing disruption to treatment routines. Smart somatosensory wearable assistive device (SSWAD): This device incorporates wireless surface electromyography (sEMG) with exergames to enhance user engagement and track rehabilitation progress. Usability studies show high user acceptance (average SUS score: 77.70) for SSWAD, particularly among female participants with prior rehabilitation experience. Conclusion: The Intelligent Health Promotion Service System offers a promising approach for remote rehabilitation, promoting patient motivation and improving accessibility, particularly for vulnerable populations.

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Intelligent Health Promotion Service System: A Project for Remote Rehabilitation

  • Lenka Lhotska,
  • Jaromir Dolezal,
  • Jindrich Adolf,
  • Josef Černohorsky,
  • Ales Richter,
  • Zdenek Pliva,
  • Pavel Sedlak,
  • Yang-Cheng Lin,
  • Wei-Chih Lien,
  • Poh Thong Tan,
  • Bo Liu

摘要

This paper presents the ongoing development of the Intelligent Health Promotion Service System, a joint Taiwanese-Czech project focused on remote rehabilitation solutions. The system combines a multi-sensor smart orthosis with serious game integration for patient motivation. Our primary targets are aging populations with sarcopenia and potentially dementia, undergoing long-term home rehabilitation. Methodology: We focus on three key areas: Camera-based motion capture and analysis: We utilize a single 2D camera for movement capture, enabling a versatile and cost-effective solution. Machine learning models trained by physiotherapist evaluations are used for automated assessment, comparable to human raters. Reconditioning for bedridden patients: This solution provides passive reconditioning for ICU patients with limited mobility. It allows for rehabilitation in existing hospital beds, minimizing disruption to treatment routines. Smart somatosensory wearable assistive device (SSWAD): This device incorporates wireless surface electromyography (sEMG) with exergames to enhance user engagement and track rehabilitation progress. Usability studies show high user acceptance (average SUS score: 77.70) for SSWAD, particularly among female participants with prior rehabilitation experience. Conclusion: The Intelligent Health Promotion Service System offers a promising approach for remote rehabilitation, promoting patient motivation and improving accessibility, particularly for vulnerable populations.