Next Steps in Wearable Technology and Community Ambulation in Multiple Sclerosis

Overview

Journal Curr Neurol Neurosci Rep

Specialty Neurology

Date 2019 Sep 6

PMID 31485896

Citations 30

Authors

Mikaela L Frechette

Brett M Meyer

Lindsey J Tulipani

Reed D Gurchiek

Ryan S McGinnis

Jacob J Sosnoff

Affiliations

Soon will be listed here.

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.

Citing Articles

Evaluating Cognitive-Motor Interference in Multiple Sclerosis: A Technology-Based Approach.

Podda J, Pedulla L, Brichetto G, Tacchino A Bioengineering (Basel). 2024; 11(3).

PMID: 38534551 PMC: 10968042. DOI: 10.3390/bioengineering11030277.

Progression events defined by home-based assessment of motor function in multiple sclerosis: protocol of a prospective study.

Dorsch E, Rohling H, Zocholl D, Hafermann L, Paul F, Schmitz-Hubsch T Front Neurol. 2023; 14:1258635.

PMID: 37881311 PMC: 10597627. DOI: 10.3389/fneur.2023.1258635.

An observational study to assess validity and reliability of smartphone sensor-based gait and balance assessments in multiple sclerosis: Floodlight GaitLab protocol.

Rinderknecht M, Zanon M, Boonstra T, Angelini L, Stanev D, Chan G Digit Health. 2023; 9:20552076231205284.

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Wearable Sensor Technologies to Assess Motor Functions in People With Multiple Sclerosis: Systematic Scoping Review and Perspective.

Woelfle T, Bourguignon L, Lorscheider J, Kappos L, Naegelin Y, Jutzeler C J Med Internet Res. 2023; 25:e44428.

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Automatic Assessment of the 2-Minute Walk Distance for Remote Monitoring of People with Multiple Sclerosis.

Kontaxis S, Laporta E, Garcia E, Martinis M, Leocani L, Roselli L Sensors (Basel). 2023; 23(13).

PMID: 37447866 PMC: 10346544. DOI: 10.3390/s23136017.

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