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Artificial intelligence

Artificial Intelligence-Powered Computer Vision for Hand Evaluation Shows High Reliability

Strategic Insights

— 2 min read

Researchers at Mayo Clinic have made a significant breakthrough in the field of artificial intelligence (AI) and computer vision, demonstrating the potential of AI-powered computer vision for evaluating hand function. According to a study published in Plastic and Reconstructive Surgery, Global Open, the researchers used a proprietary program, H.AI.ND, to analyze videos of hand movements and compared the results with manually derived measurements. The study found that AI-generated angle outputs showed high reliability in assessing hand function in both static and dynamic movements.

Key Takeaways:

  • The study aimed to evaluate the efficacy of computer vision for assessing peripheral motor function and range of motion of the hand for future clinic and telemedicine purposes.
  • Five healthy volunteer subjects were filmed performing hand examinations, and the videos were processed using the H.AI.ND program to generate temporal and spatial data for joint angle analysis.
  • The median joint angles determined by AI were compared with manually derived counterparts, and the measurements were compared at a population level using Wilcoxon signed rank tests and at the individual video level using interclass correlation analyses.
  • The study concluded that goniometric analysis through computer vision applications may provide an easy and reliable alternative for hand evaluation in the normal population for both static and dynamic function.
  • The researchers recommended further study to evaluate this program's potential role for diagnostic assessment in the diseased population before and after surgical investigation.
  • The study involved researchers from the Mayo Clinic's *Division of Plastic and Reconstructive Surgery, Mayo Clinic, Rochester, MN, United States.
  • Additional authors for this research include MD Mehmet F. Tunaboylu, MD Andrew F. Emanuels, MD Steven L. Moran.

Statistics:

  • 5 healthy volunteer subjects were involved in the study, with 10 hands total being filmed performing hand examinations.
  • The videos were processed using the H.AI.ND program based on the MediaPipe API (Google, v0.9.2.1).
  • The study compared the AI-generated angle outputs with manually determined measurements for 3 clinical positions, including compound appositional movement.
  • The measurements were compared at a population level using Wilcoxon signed rank tests and at the individual video level using interclass correlation analyses.

Sources:

  • NewsRx. Mayo Clinic Researchers Describe Findings in Artificial Intelligence (From Theory to Practice: Moving Toward Artificial Intelligence-powered Computer Vision Applications for Peripheral Motor Nerve Assessment of the Hand). Telemedicine Week. May 13, 2025; p 568.
  • Plastic and Reconstructive Surgery, Global Open. From Theory to Practice: Moving Toward Artificial Intelligence-powered Computer Vision Applications for Peripheral Motor Nerve Assessment of the Hand. 2025,13(4):e6674. (http://www.prsgo.com)

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