"My knee hurts constantly," an older patient might tell their doctor. Yet in many cases, diagnostic imaging like X-rays or magnetic resonance imaging (MRI) reveals no clear structural abnormality that matches the reported severity. For clinicians, gauging how deeply chronic pain disrupts a patient's ability to walk, climb stairs, or perform daily activities remains a major challenge.
To bridge this gap, a multi-institutional research consortium has launched an initiative to combine physical movement data, biosignals, and clinical records. The goal is to develop artificial intelligence-driven technology that objectively measures chronic pain in older adults and delivers tailored rehabilitation programs.
The Catholic University of Korea’s Yeouido St. Mary’s Hospital announced on August 24 that Prof. Kim Jong-ho of the Department of Orthopedic Surgery will co-lead the project, which was selected as part of the Korean-style Advanced Research Projects Agency for Health (K-ARPA-H) initiative.
The project is led by Chonnam National University Hospital, bringing together eight collaborating entities: The Catholic University of Korea Industry-Academic Cooperation Foundation, digital health company OrthoCare, the Gwangju Institute of Science and Technology (GIST), the Korea Electronics Technology Institute (KETI), Syntekabio, the Korea Digital Healthcare Promotion Foundation, and the Kyung Hee University Industry-Academic Cooperation Foundation. Supported by 7.5 billion won in total research funding, the consortium will carry out the study over four years and six months. Prof. Kim Jong-ho and Prof. Lee Yun-gyu of Chung-Ang University’s School of Software serve as co-principal investigators.
Adding Real-World Motion Data to Subjective Pain Scores
Because pain is a subjective sensory experience, clinical assessments have long relied on patient self-reporting. However, two individuals reporting the exact same pain score can experience vastly different functional limitations—one may walk and climb stairs with ease, while another struggles to stand up from a chair.
The project focuses on complementing self-reported pain scores with objective, real-world mobility data. Prof. Kim’s team is developing an AI system to evaluate joint movement, muscle strength, physical function, and exercise execution. By cross-analyzing these physical metrics with biosignals, clinical records, and patient-reported pain, the researchers aim to identify quantifiable indicators of pain and functional decline.
The researchers emphasize that "objective evaluation" does not mean AI will unilaterally grade a patient's suffering. Rather, the system pairs self-reported symptoms with observed motion patterns to provide a clearer picture of daily physical impairment.
Smartphones and Digital Biomarkers for At-Home Rehabilitation
The initiative leverages ANAPA, an AI-powered musculoskeletal digital health platform developed by OrthoCare. ANAPA uses smartphone or tablet cameras to record body motion and analyze joint range of motion—such as knee or shoulder extension—without requiring patients to wear external sensors.
Building on this framework, the team plans to track patient mobility beyond hospital settings into home and community environments. The platform will evaluate how effectively patients perform rehabilitation exercises and track longitudinal improvements in joint mobility and physical function. These insights will be integrated with pain classification, underlying disease profiles, and living conditions to generate personalized digital exercise and rehab regimens.
A key milestone will be identifying reliable "digital biomarkers"—quantifiable indicators derived from smartphone-captured movement and biosignal data that reflect real-time shifts in musculoskeletal health. Rather than applying uniform exercise protocols, the resulting management model will dynamically adjust rehab intensity based on individual progress.
"For older adults, imaging tests and periodic clinic visits alone are insufficient to evaluate the full severity of pain and its impact on daily life," said Prof. Kim Jong-ho. "Through this study, we aim to objectively quantify pain and musculoskeletal function, establishing a personalized management system that delivers tailored treatment and rehabilitation."
Prof. Lee Yun-gyu added, "By deploying ANAPA’s AI motion analysis and digital rehab technology, we can continuously track functional changes not only in clinics but also in patients' daily lives. We will refine this technology to establish clinically reliable digital biomarkers that bring tangible relief to older adults suffering from chronic pain."
The project is funded by the Ministry of Health and Welfare and the Korea Health Industry Development Institute’s K-Health Future Promotion Group under the 2026 K-ARPA-H Project (RFP7 VISTA).
