The push forward in rehabilitation; validation of a machine learning method for detection of wheelchair propulsion type
The push forward in rehabilitation; validation of a machine learning method for detection of wheelchair propulsion type
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.
Organisatie | De Haagse Hogeschool |
Afdeling | Faculteit Gezondheid, Voeding & Sport |
Lectoraat | Lectoraat Technologie voor Inclusief Bewegen en Sport |
Gepubliceerd in | Sensors MDPI, Vol. 24, Uitgave: 2, Pagina's: 1-12 |
Datum | 2024-01-19 |
Type | Artikel |
DOI | 10.3390/s24020657 |
Taal | Engels |