Use of Wearable Sensor Technology in Gait, Balance, and Range of Motion Analysis
Source abstract
Abstract
More than 8.6 million people suffer from neurological disorders that affect their gait and balance. Physical therapists provide interventions to improve patient’s functional outcomes, yet balance and gait are often evaluated in a subjective and observational manner. The use of quantitative methods allows for assessment and tracking of patient progress during and after rehabilitation or for early diagnosis of movement disorders. This paper surveys the state-of-the-art in wearable sensor technology in gait, balance, and range of motion research. It serves as a point of reference for future research, describing current solutions and challenges in the field. A two-level taxonomy of rehabilitation assessment is introduced with evaluation metrics and common algorithms utilized in wearable sensor systems.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Balance, Gait, and Falls Prevention · Muscle activation and electromyography studies · Stroke Rehabilitation and Recovery
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Computer Science and Engineering, University of South Florida, 4202 E Fowler Ave, Tampa, FL 33620, USA
School of Physical Therapy & Rehabilitation Sciences, University of South Florida, 12901 Bruce B. Downs Blvd., MDC 77, Tampa, FL 33612, USA
References (100+)
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