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As the global population of elderly and disabled individuals continues to grow, innovative solutions are urgently needed to improve their safety, mobility, independence, and well-being, while reducing caregiving burdens and enhancing healthcare outcomes. This paper presents a telemonitoring and telerehabilitation platform that demonstrates the transformative potential of Human-AI collaboration to address these critical needs. The paper focuses on the platform’s architectural and technological design to tackle the unique challenges faced by these vulnerable groups, emphasizing AI’s role in decision support, personalized care, and rehabilitation. The platform comprises four key components: a wearable Raman Spectroscopy system for non-invasive blood glucose monitoring, fall detection systems using video analytics, deep learning, and radio frequency signals for rapid caregiver alerts, bimanual rehabilitation technologies to aid physical therapy and improve recovery, and a cloud-based system for managing and analyzing health and rehabilitation data to provide valuable insights and facilitate personalized care.

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Human-AI Collaboration in Health and Wellness: A Case of Telemonitoring and Telerehabilitation Platform for Disabled, Elderly, and Post-Stroke Care

  • 会议论文

  • 发表日期：

    2025年

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  • Chutiporn Anutariya,
  • Parkpoom Wisedsri,
  • Chaklam Silpasuwanchai,
  • Mongkol Ekpanyapong,
  • Attaphongse Taparugssanagorn,
  • S. D. A. P. Senadeera,
  • Roongtiwa Vachalathiti,
  • Sunee Bovonsunthonchai

摘要

As the global population of elderly and disabled individuals continues to grow, innovative solutions are urgently needed to improve their safety, mobility, independence, and well-being, while reducing caregiving burdens and enhancing healthcare outcomes. This paper presents a telemonitoring and telerehabilitation platform that demonstrates the transformative potential of Human-AI collaboration to address these critical needs. The paper focuses on the platform’s architectural and technological design to tackle the unique challenges faced by these vulnerable groups, emphasizing AI’s role in decision support, personalized care, and rehabilitation. The platform comprises four key components: a wearable Raman Spectroscopy system for non-invasive blood glucose monitoring, fall detection systems using video analytics, deep learning, and radio frequency signals for rapid caregiver alerts, bimanual rehabilitation technologies to aid physical therapy and improve recovery, and a cloud-based system for managing and analyzing health and rehabilitation data to provide valuable insights and facilitate personalized care.