Automatic range of motion measurement via smartphone images for telemedicine examination of the hand.

Sci Prog

Department of Microsurgery, Orthopaedic Trauma and Hand Surgery, The First Affiliated Hospital, 71068Sun Yat-sen University, Guangzhou, China.

Published: February 2023

AI Article Synopsis

  • Telemedicine has become essential for hand surgery evaluations during COVID-19, but traditional physical exams are difficult to perform remotely, particularly in measuring hand range of motion (ROM).
  • The study involved 28 healthy volunteers using an automatic measurement method based on hand gestures analyzed through Google MediaPipe Hands, comparing results with manual goniometry to establish accuracy.
  • Results showed that the automatic method had a mean difference of -2.21° in angle and a measure of distance within acceptable ranges, indicating it's a reliable alternative for ROM assessment in telemedicine settings.

Article Abstract

Background: Telemedicine support virtual consultations and evaluations in hand surgery for patients in remote areas during the COVID-19 era. However, traditional physical examination is challenging in telemedicine and it is inconvenient to manually measure the hand range of motion (ROM) from images or videos. Here, we propose an automatic method using the hand pose estimation technique, aiming to measure the hand ROM from smartphone images.

Methods: Twenty-eight healthy volunteers participated in the study. An eight-hand gestures measurement protocol and the Google MediaPipe Hands were used to analyze images and calculate the ROM automatically. Manual goniometry was also performed according to the guideline of the American Medical Association. The correlation between the automatic and manual methods was analyzed by the intraclass correlation coefficient and Pearson correlation coefficient. The clinical acceptance was testified using Bland-Altman plots.

Results: A total of 32 parameters of each hand were measured by both methods, and 1792 measurement results were compared. The mean difference between automatic and manual methods is -2.21 ± 9.29° in the angle measurement and 0.48 ± 0.48 cm in the distance measurement. The intraclass correlation coefficient of 75% of parameters was higher than 0.75, the Pearson correlation coefficient of 84% of parameters was over 0.6, and 40.6% of parameters reached well-accepted clinical agreements.

Conclusions: The proposed method provides a helpful protocol for automatic hand ROM measurement based on smartphone images and the MediaPipe Hands pose estimation technique. The automatic measurement is acceptable and comparable with existing methods, showing a possible application in the telemedicine examination of hand surgery.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10450288PMC
http://dx.doi.org/10.1177/00368504231152740DOI Listing

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