Power wheelchair driving analysis for people with motor disabilities using ANN classification.
The present paper aims primarily to analyze the driving skills of patients with different pathologies using artificial neural networks. The evaluation of these patients' abilities to drive an electric wheelchair or power wheelchair shows that this battery-operated device can be dangerous for them wh...
| Publicado en: | Disability & Rehabilitation: Assistive Technology Vol. 20; no. 7; pp. 2290 - 2298 |
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| Autores principales: | , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Oct2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=188362608&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 188362608 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 17483107 1X04 jtl: Disability & Rehabilitation: Assistive Technology issn: 17483107 maglogo: Y pubinfo: dt: Oct2025 vid: 20 iid: 7 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 188362608 184858190 188362608 188362608 10.1080/17483107.2025.2499189 188362608 ppf: 2290 ppct: 8 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Power wheelchair driving analysis for people with motor disabilities using ANN classification. aug: au: Zatla, Hicham Tolbi, Bilal Bouriachi, Fares affil: IRECOM Laboratory, University of Sidi Bel-Abbes, Sidi Bel-Abbes, Algeria sug: subj: Wheelchairs, Powered Evaluation Persons with Disabilities Motor Skills Disorders Neural Networks (Computer) Learning Methods Machine Learning Algorithms Utilization Simulations Funding Source France Human Experimental Studies Power Sources Clinical Assessment Tools Cerebral Palsy Rehabilitation Male Female Child Adolescence Young Adult Analysis of Variance T-Tests Descriptive Statistics Child: 6-12 years Adolescent: 13-18 years Male Female ab: The present paper aims primarily to analyze the driving skills of patients with different pathologies using artificial neural networks. The evaluation of these patients' abilities to drive an electric wheelchair or power wheelchair shows that this battery-operated device can be dangerous for them when they present severe motor deficiencies. It is for this reason that it was deemed necessary to use a Power Wheelchair (PW) driving simulator in order to analyze, in an objective manner, their driving abilities. Consequently, an experimental study was carried out using the driving simulator at the Center for the Physical Medicine and Rehabilitation of Children (Centre de Médecine Physique et de Réadaptation pour Enfants) in Flavigny-sur-Moselle in France. The error between the reference trajectories and the patient's calculated trajectories which was used as input for classification allowed obtaining the model for analyzing the driver's skills. This model was then used for identifying the familiarized and novice users. The evolution of the above-mentioned error turned out to be an important indicator for improving the quality of the patient's driving skills during the learning phase. IMPLICATION FOR REHABILITATION: The analysis of driving the Power Wheelchair for people with disabilities is conducted in this research. Using the artificial intelligence, we can conclude about the ability of these persons to drive the PW. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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