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The push forward in rehabilitation; validation of a machine learning method for detection of wheelchair propulsion type

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The push forward in rehabilitation; validation of a machine learning method for detection of wheelchair propulsion type

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Samenvatting

Within rehabilitation, there is a great need for a simple method to monitor wheelchair use, especially whether it is active or passive. For this purpose, an existing measurement technique was
extended with a method for detecting self- or attendant-pushed wheelchair propulsion. The aim of this study was to validate this new detection method by comparison with manual annotation of wheelchair use. Twenty-four amputation and stroke patients completed a semi-structured course of active and passive wheelchair use. Based on a machine learning approach, a method was developed that detected the type of movement. The machine learning method was trained based on the data of a single-wheel sensor as well as a setup using an additional sensor on the frame. The method showed high accuracy (F1 = 0.886, frame and wheel sensor) even if only a single wheel sensor was used (F1 = 0.827). The developed and validated measurement method is ideally suited to easily determine wheelchair use and the corresponding activity level of patients in rehabilitation.

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OrganisatieDe Haagse Hogeschool
AfdelingFaculteit Gezondheid, Voeding & Sport
LectoraatLectoraat Technologie voor Inclusief Bewegen en Sport
Gepubliceerd inSensors MDPI, Vol. 24, Uitgave: 2, Pagina's: 1-12
Datum2024-01-19
TypeArtikel
DOI10.3390/s24020657
TaalEngels

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