Journal of experimental orthopaedics · 2025
Validity of a wireless instrumented insole (WalkinSense system) for measuring gait metrics.
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Eckelt Melanie, Fayad Jennifer, Backes Anne, Schurmans Gaëlle, Garcia Frederic, Grimm Bernd, Serchi Valeria, Meyer Tobias, Solignac Thomas, Mouton Caroline, Seil Romain, Malisoux Laurent
Аннотация
PURPOSE: Gait analysis has become a valuable tool in assessing abnormal gait patterns and quantifying improvements resulting from interventions, particularly in the rehabilitation of orthopaedic patients. Wearables can measure gait metrics in daily life settings, but they must first be validated before being applied in such contexts. This study aims to assess the validity of a wireless instrumented insole (WalkinSense).
METHODS: Recordings of 104 healthy participants were obtained at various speed and slope conditions (3 km/h, 4.5 km/h [-3°, -6°, +3° and +6°], 6 km/h and 9 km/h). Spatiotemporal and kinematic variables were collected simultaneously with an instrumented treadmill, a three-dimensional motion capture system and with the WalkinSense system. Mean bias between the systems was assessed using separate Bland-Altman analyses for each metric and condition. Mean error and limits of agreement (absolute and percentage) were calculated and the agreement was statistically quantified using a priori set thresholds (excellent <5%, good <10%, acceptable <15% and poor >15%). MAPE scores and a two-way mixed model intraclass correlation coefficient (ICC) for consistency were also calculated.
RESULTS: All spatiotemporal variables (except double support time) showed good or excellent agreement, MAPE scores lower than 5% and ICC values > 0.88 in the walking speeds. Data collected with the WalkinSense system showed acceptable or good agreement for the spatiotemporal variables in running. Kinematic variables showed only poor agreements across all speeds and slopes.
CONCLUSION: These findings suggest that the WalkinSense system may be useful to quantify spatiotemporal variables with good to excellent accuracy across various walking speeds. However, based on the results of this study indicate that the WalkinSense system is not suitable for measuring kinematic variables without substantial improvements.
LEVEL OF EVIDENCE: Level II, diagnostic studies.
METHODS: Recordings of 104 healthy participants were obtained at various speed and slope conditions (3 km/h, 4.5 km/h [-3°, -6°, +3° and +6°], 6 km/h and 9 km/h). Spatiotemporal and kinematic variables were collected simultaneously with an instrumented treadmill, a three-dimensional motion capture system and with the WalkinSense system. Mean bias between the systems was assessed using separate Bland-Altman analyses for each metric and condition. Mean error and limits of agreement (absolute and percentage) were calculated and the agreement was statistically quantified using a priori set thresholds (excellent <5%, good <10%, acceptable <15% and poor >15%). MAPE scores and a two-way mixed model intraclass correlation coefficient (ICC) for consistency were also calculated.
RESULTS: All spatiotemporal variables (except double support time) showed good or excellent agreement, MAPE scores lower than 5% and ICC values > 0.88 in the walking speeds. Data collected with the WalkinSense system showed acceptable or good agreement for the spatiotemporal variables in running. Kinematic variables showed only poor agreements across all speeds and slopes.
CONCLUSION: These findings suggest that the WalkinSense system may be useful to quantify spatiotemporal variables with good to excellent accuracy across various walking speeds. However, based on the results of this study indicate that the WalkinSense system is not suitable for measuring kinematic variables without substantial improvements.
LEVEL OF EVIDENCE: Level II, diagnostic studies.