Analysis of the applicability of an artificial intelligence technology to classify hand movements of people with or without limited hand movement, using AI-motion SW: An observational study

Authors:
Open Access
Publisher website
Google Scholar
Abstract
The purpose of this study was to analyze hand movements using artificial intelligence. From September 1, 2020, to December 30, 2020, a total of 200 individuals, including those with limited hand movements and healthy individuals, were included in the study. Photographs were acquired using a smartphone camera to establish a protocol for hand movements, targeting 100 healthy individuals and 100 individuals with limited hand movements due to central nervous system diseases. The protocol for hand motion video recording using a smartphone camera was as follows: During the hand movement, the participant sat on a chair sufficiently high to touch the floor and did not lean against the back. When the participant sat on the chair and placed the forearm on the desk, the elbow joint was bent at 90°, and the arm was placed on the desk to perform hand movements. The participant placed the forearm in a neutral position on the desk. The smartphone camera was positioned 45 cm in front of the palm at the same height as that of the hand, and then a video was recorded. The data collected to determine the hand movements of all subjects were used for artificial intelligence machine learning analyses. An independent t-test was performed to determine the difference between the two groups. Significant differences between the two groups were observed (p < 0.001). The motion analysis through images showed that the analysis of hand motions using artificial intelligence is feasible. The analysis of healthy individuals and those with limited hand movements confirmed that hand movement alone can be used to quickly and accurately predict hand functions.

This publication has 23 references indexed in Scilit: