ArticleHand therapy2022
A system for automated acquisition of digital flexion using a 3-D camera and custom gantry.
Article in Hand therapy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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0 citing papers in PubMed, 1 citations in OpenAlex.
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Authors and funding
5 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Introduction: Automated measurement of digital range of motion (ROM) may improve the accuracy of reporting and increase clinical efficiency. We hypothesize that a 3-D camera on a custom gantry will produce ROM measurements similar to those obtained with a manual goniometer. Methods: A 3-D camera mounted on a custom gantry, was mechanized to rotate 200° around a platform. The video was processed to segment each digit and calculate joint angles in people with no history of any hand conditions or surgery to validate the system. A second-generation prototype was then assessed in people with different hand conditions. Metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joint flexion were measured repeatedly with a goniometer and the automated system. The average difference between manual and automatic measurements was calculated along with intraclass correlation coefficients (ICC). Results: In the initial validation, 1,488 manual and 1,488 automated joint measurements were obtained and the measurement algorithm was refined. In people with hand conditions, 688 manual and 688 automated joint measurements were compared. Average acquisition time was 7 s per hand, with an additional 2-3 s required for data processing. ICC between manual and automated data in the clinical study ranged from 0.65 to 0.85 for the MCP joints, and 0.22 to 0.66 for PIP joints. Discussion: The automated system resulted in rapid data acquisition, with reliability varying by type of joint and location. It has the potential to improve efficiency in the collection of physical exam findings. Further developments of the system are needed to measure thumb and distal phalangeal motions.
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