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Journal Article

Citation

Angelini L, Carpinella I, Cattaneo D, Ferrarin M, Gervasoni E, Sharrack B, Paling D, Nair KPS, MazzĂ  C. Sensors (Basel) 2020; 20(1): s20010079.

Affiliation

Insigneo Institute for in silico Medicine, University of Sheffield, Sheffield S1 3JD, UK.

Copyright

(Copyright © 2020, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/s20010079

PMID

31877760

Abstract

Inertial measurement units (IMUs) allow accurate quantification of gait impairment of people with multiple sclerosis (pwMS). Nonetheless, it is not clear how IMU-based metrics might be influenced by pragmatic aspects associated with clinical translation of this approach, such as data collection settings and gait protocols. In this study, we hypothesised that these aspects do not significantly alter those characteristics of gait that are more related to quality and energetic efficiency and are quantifiable via acceleration related metrics, such as intensity, smoothness, stability, symmetry, and regularity. To test this hypothesis, we compared 33 IMU-based metrics extracted from data, retrospectively collected by two independent centres on two matched cohorts of pwMS. As a worst-case scenario, a walking test was performed in the two centres at a different speed along corridors of different lengths, using different IMU systems, which were also positioned differently. The results showed that the majority of the temporal metrics (9 out of 12) exhibited significant between-centre differences. Conversely, the between-centre differences in the gait quality metrics were small and comparable to those associated with a test-retest analysis under equivalent conditions. Therefore, the gait quality metrics are promising candidates for reliable multi-centric studies aiming at assessing rehabilitation interventions within a routine clinical context.


Language: en

Keywords

accelerometry; autocorrelation; gait metrics; harmonic ratio; multiple sclerosis; sampling frequency; six-minute walk; test-retest reliability; wearable sensors

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