Authors
Alexandra A Portnova-Fahreeva, Momona Yamagami, Adrià Robert-Gonzalez, Jennifer Mankoff, Heather Feldner, Katherine M Steele
Publication date
2024/5/9
Journal
IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publisher
IEEE
Description
Utilization of hand-tracking cameras, such as Leap, for hand rehabilitation and functional assessments is an innovative approach to providing affordable alternatives for people with disabilities. However, prior to deploying these commercially-available tools, a thorough evaluation of their performance for disabled populations is necessary. In this study, we provide an in-depth analysis of the accuracy of Leap’s hand-tracking feature for both individuals with and without upper-body disabilities for common dynamic tasks used in rehabilitation. Leap is compared against motion capture with conventional techniques such as signal correlations, mean absolute errors, and digit segment length estimation. We also propose the use of dimensionality reduction techniques, such as Principal Component Analysis (PCA), to capture the complex, high-dimensional signal spaces of the hand. We found that Leap’s hand-tracking …
Scholar articles
AA Portnova-Fahreeva, M Yamagami… - IEEE Transactions on Neural Systems and …, 2024