Is a Wearable Sensor-Based Characterisation of Gait Robust Enough to Overcome Differences Between Measurement Protocols? A Multi-Centric Pragmatic Study in Patients with Multiple Sclerosis

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.

Gait Characteristics Harvested during a Smartphone-Based Self-Administered 2-Minute Walk Test in People with Multiple Sclerosis: Test-Retest Reliability and Minimum Detectable Change

“…ICC values for test-retest reliability were similar to those reported in other assessments of gait in PwMS using body-worn IMUs [ 11 , 15 ] and for clinical walking outcome assessments in PwMS [ 36 ]. ICCs for test-retest reliability harvested from HCs were less reliable than from PwMS.…”

“…SEM values reported here are lower for mean stride (0.026 s vs. 0.04 s), step (0.013 s vs. 0.02 s) and stance (0.017 s vs. 0.03 s) times, Table 3 , and comparable to the swing time (0.012 s vs. 0.01 s), Table 3 , reported by Angelini et al [ 11 ]. MDC values reported here are lower for step (0.036 s vs. 0.05 s) time and higher for stride (0.072 s vs. 0.01 s), stance (0.046 s vs. 0.03 s) and swing (0.032 s vs. 0.03 s) time, Table 3 , to those reported by Angelini et al [ 11 ].Except for swing time asymmetry, higher SEM and MDC temporal variability and asymmetry metrics were observed for mean stride, step, stance and swing times when compared to those reported by Angelini et al [ 11 ]. The study by Angelini et al [ 11 ] was however conducted in a controlled clinical setting using a multi-sensor recording set-up.…”

“…Small or low SEM values for gait characteristics indicate that measurements are stable and reproducible over time, thus indicating the precision of the measurement system [ 37 ]. Angelini et al [ 11 ] reported SEM and MDC values for gait characteristics measured in PwMS (n = 26, EDSS = 2–6.5) using three body-worn (both ankles and lumbar spine) IMU-based sensors, during a 6MWT recorded in a clinical setting. SEM values reported here are lower for mean stride (0.026 s vs. 0.04 s), step (0.013 s vs. 0.02 s) and stance (0.017 s vs. 0.03 s) times, Table 3 , and comparable to the swing time (0.012 s vs. 0.01 s), Table 3 , reported by Angelini et al [ 11 ].…”

“…Angelini et al [ 11 ] reported SEM and MDC values for gait characteristics measured in PwMS (n = 26, EDSS = 2–6.5) using three body-worn (both ankles and lumbar spine) IMU-based sensors, during a 6MWT recorded in a clinical setting. SEM values reported here are lower for mean stride (0.026 s vs. 0.04 s), step (0.013 s vs. 0.02 s) and stance (0.017 s vs. 0.03 s) times, Table 3 , and comparable to the swing time (0.012 s vs. 0.01 s), Table 3 , reported by Angelini et al [ 11 ]. MDC values reported here are lower for step (0.036 s vs. 0.05 s) time and higher for stride (0.072 s vs. 0.01 s), stance (0.046 s vs. 0.03 s) and swing (0.032 s vs. 0.03 s) time, Table 3 , to those reported by Angelini et al [ 11 ].Except for swing time asymmetry, higher SEM and MDC temporal variability and asymmetry metrics were observed for mean stride, step, stance and swing times when compared to those reported by Angelini et al [ 11 ].…”

“…An opportunity thus exists as the participant’s gait characteristics remain unexplored. Recent studies have employed body-worn inertial-sensor based systems for the assessment of gait in PwMS, through the measurement of temporal, spatial and/or spatiotemporal gait characteristics, during laboratory-based scripted functional assessments such as the 6MWT [ 9 , 10 , 11 ], T25FW [ 12 , 13 ], TUG [ 13 , 14 , 15 ], a 1-minute walk [ 16 ] and free-living gait [ 16 ]. However these studies suffer from a number of limitations and drawbacks, including the requirement for a multi-sensor body-worn set-up [ 9 , 11 , 12 , 13 , 14 , 15 , 17 ], the test requires assistance from a clinician and/or were laboratory based [ 9 , 11 , 12 , 13 , 14 , 15 , 17 ], were carried out on a small/limited cohort [ 10 , 16 ] or the sensor requires direct attachment to the skin [ 9 , 14 ].…”