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Accuracy of Sensor-Based Measurement of Clinically Relevant Motor Activities in Daily Life of Children With Mobility Impairments. | LitMetric

Accuracy of Sensor-Based Measurement of Clinically Relevant Motor Activities in Daily Life of Children With Mobility Impairments.

Arch Phys Med Rehabil

Swiss Children's Rehab, University Children's Hospital Zurich, Affoltern am Albis, Switzerland; Children's Research Center, University Children's Hospital Zurich, University of Zurich, Zurich, Switzerland. Electronic address:

Published: January 2024

Objective: This study aimed to determine the accuracy of 3 sensor configurations and corresponding algorithms deriving clinically relevant outcomes of everyday life motor activities in children undergoing rehabilitation. These outcomes were identified in 2 preceding studies assessing the needs of pediatric rehabilitation. The first algorithm estimates the duration of lying, sitting, and standing positions and the number of sit-to-stand transitions with data from a trunk and a thigh sensor. The second algorithm detects active and passive wheeling periods with data from a wrist and a wheelchair sensor. The third algorithm detects free and assisted walking periods and estimates the covered altitude change during stair climbing with data from a single ankle sensor and a sensor placed on walking aids.

Design: The participants performed a semi-structured activity circuit while wearing inertial sensors on both wrists, the sternum, and the thigh and shank of the less-affected side. The circuit included watching a movie, playing, cycling, drinking, and moving around between facilities. Video recordings, which 2 independent researchers labeled, served as reference criteria to determine the algorithms' performance.

Setting: In-patient rehabilitation center.

Participants: Thirty-one children and adolescents with mobility impairments who were able to walk or use a manual wheelchair for household distances (N=31).

Interventions: Not applicable.

Main Outcome Measure(s): The algorithms' activity classification accuracies.

Results: The activity classification accuracy was 97% for the posture detection algorithm, 96% for the wheeling detection algorithm, and 93% for the walking detection algorithm.

Conclusion(s): The 3 sensor configurations and corresponding algorithms presented in this study revealed accurate measurements of everyday life motor activities in children with mobility impairments. To follow-up on this promising results, the sensor systems needs to be tested in long-term measurements outside the clinic before using the system to determine the children's motor performance in their habitual environment for clinical and scientific purposes.

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Source
http://dx.doi.org/10.1016/j.apmr.2023.05.015DOI Listing

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