AI-driven balance evaluation: a comparative study between blind and non-blind individuals using the mini-BESTest
Milagros Jaén-Vargas, Josué Pagán, Shiyang Li, María Fernanda Trujillo-Guerrero, Niloufar Kazemi, Alessio Sansò, Benito Codina-Casals, Roy Abi Zeid Daou, Jose Javier Serrano Olmedo
TL;DR
This study compares balance in blind and sighted people using a balance test and sensors, finding that one-legged stance best differentiates them.
Contribution
First study to evaluate balance in blind individuals using the mini-BESTest and inertial measurement units.
Findings
One-legged stance activity best differentiates blind and sighted individuals in balance evaluation.
Physiotherapists' evaluations are not fully aligned with test criteria based on acceleration data analysis.
Machine learning models achieved an 85.6% F1-score in predicting mini-BESTest scores in binary classification.
Abstract
There are 2.2 billion visually impaired individuals and 285 million blind people worldwide. The vestibular system plays a fundamental role in the balance of a person related to sight and hearing, and thus blind people require physical therapy to improve their balance. Several clinical tests have been developed to evaluate balance, such as the mini-BESTest. This test has been used to evaluate the balance of people with neurological diseases, but there have been no studies that evaluate the balance of blind individuals before. Furthermore, despite the scoring of these tests being not subjective, the performance of some activities are subject to the physiotherapist’s bias. Tele-rehabilitation is a growing field that aims to provide physical therapy to people with disabilities. Among the technologies used in tele-rehabilitation are inertial measurement units that can be used to monitor the…
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Taxonomy
TopicsBalance, Gait, and Falls Prevention · Diabetic Foot Ulcer Assessment and Management · Stroke Rehabilitation and Recovery