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Title

A personalized approach to improve walking detection in real-life settings: application to children with cerebral palsy

Authors
Paraschiv-Ionescu, Anisoara
Gerber, Corinna N
Newman, Christopher J
Aminian, Kamiar
Published in Sensors. 2019, vol. 19, no. 23
Abstract Although many methods have been developed to detect walking by using body-worn inertial sensors, their performances decline when gait patterns become abnormal, as seen in children with cerebral palsy (CP). The aim of this study was to evaluate if fine-tuning an existing walking bouts (WB) detection algorithm by various thresholds, customized at the individual or group level, could improve WB detection in children with CP and typical development (TD). Twenty children (10 CP, 10 TD) wore 4 inertial sensors on their lower limbs during laboratory and out-laboratory assessments. Features extracted from the gyroscope signals recorded in the laboratory were used to tune thresholds of an existing walking detection algorithm for each participant (individual-based personalization: Indiv) or for each group (population-based customization: Pop). Out-of-laboratory recordings were analyzed for WB detection with three versions of the algorithm (i.e., original fixed thresholds and adapted thresholds based on the Indiv and Pop methods), and the results were compared against video reference data. The clinical impact was assessed by quantifying the effect of WB detection error on the estimated walking speed distribution. The two customized Indiv and Pop methods both improved WB detection (higher, sensitivity, accuracy and precision), with the individual-based personalization showing the best results. Comparison of walking speed distribution obtained with the best of the two methods showed a significant difference for 8 out of 20 participants. The personalized Indiv method excluded non-walking activities that were initially wrongly interpreted as extremely slow walking with the initial method using fixed thresholds. Customized methods, particularly individual-based personalization, appear more efficient to detect WB in daily-life settings.
Keywords cerebral palsygait detectioninertial sensorspersonalizationwalking bout
Identifiers
PMID: 31816854
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Structures
Research group Laboratoire de cinésiologie (943)
Project
Autre: 2015/Fondation Leenaards/ none/Science for Smile Foundation
Citation
(ISO format)
CARCREFF, Léna et al. A personalized approach to improve walking detection in real-life settings: application to children with cerebral palsy. In: Sensors, 2019, vol. 19, n° 23. doi: 10.3390/s19235316 https://archive-ouverte.unige.ch/unige:128302

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Deposited on : 2020-01-07

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