Mikaela L Frechette1, Brett M Meyer2, Lindsey J Tulipani2, Reed D Gurchiek2, Ryan S McGinnis2, Jacob J Sosnoff3. 1. Motor Control Research Lab, Department of Kinesiology and Community Health, University of Illinois Urbana-Champaign, 301 Freer Hall 906 S Goodwin Ave, Urbana, IL, 61801, USA. 2. M-Sense Research Group, Department of Electrical and Biomedical Engineering, University of Vermont, Burlington, VT, 05405, USA. 3. Motor Control Research Lab, Department of Kinesiology and Community Health, University of Illinois Urbana-Champaign, 301 Freer Hall 906 S Goodwin Ave, Urbana, IL, 61801, USA. jsosnoff@illinois.edu.
Abstract
PURPOSE OF REVIEW: Walking impairments are highly prevalent in persons with multiple sclerosis (PwMS) and are associated with reduced quality of life. Walking is traditionally quantified with various measures, including patient self-reports, clinical rating scales, performance measures, and advanced lab-based movement analysis techniques. Yet, the majority of these measures do not fully characterize walking (i.e., gait quality) nor adequately reflect walking in the real world (i.e., community ambulation) and have limited timescale (only measure walking at a single point in time). We discuss the potential of wearable sensors to provide sensitive, objective, and easy-to-use assessment of community ambulation in PwMS. RECENT FINDINGS: Wearable technology has the ability to measure all aspects of gait in PwMS yet is under-studied in comparison with other populations (e.g., older adults). Within the studies focusing on PwMS, half that measure pace collected free-living data, while only one study explored gait variability in free-living conditions. No studies explore gait asymmetry or complexity in free-living conditions. Wearable technology has the ability to provide objective, comprehensive, and sensitive measures of gait in PwMS. Future research should investigate this technology's ability to accurately assess free-living measures of gait quality, specifically gait asymmetry and complexity.
PURPOSE OF REVIEW: Walking impairments are highly prevalent in persons with multiple sclerosis (PwMS) and are associated with reduced quality of life. Walking is traditionally quantified with various measures, including patient self-reports, clinical rating scales, performance measures, and advanced lab-based movement analysis techniques. Yet, the majority of these measures do not fully characterize walking (i.e., gait quality) nor adequately reflect walking in the real world (i.e., community ambulation) and have limited timescale (only measure walking at a single point in time). We discuss the potential of wearable sensors to provide sensitive, objective, and easy-to-use assessment of community ambulation in PwMS. RECENT FINDINGS: Wearable technology has the ability to measure all aspects of gait in PwMS yet is under-studied in comparison with other populations (e.g., older adults). Within the studies focusing on PwMS, half that measure pace collected free-living data, while only one study explored gait variability in free-living conditions. No studies explore gait asymmetry or complexity in free-living conditions. Wearable technology has the ability to provide objective, comprehensive, and sensitive measures of gait in PwMS. Future research should investigate this technology's ability to accurately assess free-living measures of gait quality, specifically gait asymmetry and complexity.
Entities:
Keywords:
Community ambulation; Gait; Gait quality; Multiple sclerosis; Wearable technology
Authors: C L Martin; B A Phillips; T J Kilpatrick; H Butzkueven; N Tubridy; E McDonald; M P Galea Journal: Mult Scler Date: 2006-10 Impact factor: 6.312
Authors: Brett M Meyer; Lindsey J Tulipani; Reed D Gurchiek; Dakota A Allen; Lukas Adamowicz; Dale Larie; Andrew J Solomon; Nick Cheney; Ryan S McGinnis Journal: IEEE J Biomed Health Inform Date: 2021-05-11 Impact factor: 5.772