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Article

Reliability of IMU-Based Gait Assessment in Clinical Stroke Rehabilitation

1
Research Group Lifestyle and Health, Utrecht University of Applied Sciences, 3584 CS Utrecht, The Netherlands
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Faculty of Human Movement Sciences, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
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Physiotherapy Department Neurology, Rehabilitation Center de Parkgraaf, 3526 KJ Utrecht, The Netherlands
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Physiotherapy Department Neurology, De Hoogstraat Revalidatie, 3583 TM Utrecht, The Netherlands
*
Author to whom correspondence should be addressed.
Current address: Heidelberglaan 7, 3584 CS Utrecht, The Netherlands.
Academic Editor: Chi Hwan Lee
Sensors 2022, 22(3), 908; https://doi.org/10.3390/s22030908
Received: 17 December 2021 / Revised: 16 January 2022 / Accepted: 19 January 2022 / Published: 25 January 2022
(This article belongs to the Special Issue Use of Smart Wearable Sensors and AI Methods in Providing P4 Medicine)
Background: Gait is often impaired in people after stroke, restricting personal independence and affecting quality of life. During stroke rehabilitation, walking capacity is conventionally assessed by measuring walking distance and speed. Gait features, such as asymmetry and variability, are not routinely determined, but may provide more specific insights into the patient’s walking capacity. Inertial measurement units offer a feasible and promising tool to determine these gait features. Objective: We examined the test–retest reliability of inertial measurement units-based gait features measured in a two-minute walking assessment in people after stroke and while in clinical rehabilitation. Method: Thirty-one people after stroke performed two assessments with a test–retest interval of 24 h. Each assessment consisted of a two-minute walking test on a 14-m walking path. Participants were equipped with three inertial measurement units, placed at both feet and at the low back. In total, 166 gait features were calculated for each assessment, consisting of spatio-temporal (56), frequency (26), complexity (63), and asymmetry (14) features. The reliability was determined using the intraclass correlation coefficient. Additionally, the minimal detectable change and the relative minimal detectable change were computed. Results: Overall, 107 gait features had good–excellent reliability, consisting of 50 spatio-temporal, 8 frequency, 36 complexity, and 13 symmetry features. The relative minimal detectable change of these features ranged between 0.5 and 1.5 standard deviations. Conclusion: Gait can reliably be assessed in people after stroke in clinical stroke rehabilitation using three inertial measurement units. View Full-Text
Keywords: cerebral vascular accident; sensors; walking; recovery; accelerometer; gait quality; neurological disorder; functional gait assessment cerebral vascular accident; sensors; walking; recovery; accelerometer; gait quality; neurological disorder; functional gait assessment
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MDPI and ACS Style

Felius, R.A.W.; Geerars, M.; Bruijn, S.M.; van Dieën, J.H.; Wouda, N.C.; Punt, M. Reliability of IMU-Based Gait Assessment in Clinical Stroke Rehabilitation. Sensors 2022, 22, 908. https://doi.org/10.3390/s22030908

AMA Style

Felius RAW, Geerars M, Bruijn SM, van Dieën JH, Wouda NC, Punt M. Reliability of IMU-Based Gait Assessment in Clinical Stroke Rehabilitation. Sensors. 2022; 22(3):908. https://doi.org/10.3390/s22030908

Chicago/Turabian Style

Felius, Richard A. W., Marieke Geerars, Sjoerd M. Bruijn, Jaap H. van Dieën, Natasja C. Wouda, and Michiel Punt. 2022. "Reliability of IMU-Based Gait Assessment in Clinical Stroke Rehabilitation" Sensors 22, no. 3: 908. https://doi.org/10.3390/s22030908

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