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Analysing and classifying wheelchair movements from motion capture data
KTH, School of Engineering Sciences (SCI).
KTH, School of Engineering Sciences (SCI).
2015 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

This is a project that describes a part of the development of a tool intended for wheelchair users in their learning process of new and important movements in everyday life and in sports. The process began with an investigation, with the help of people with wheelchair experience, of which movements that were considered important and which were considered useful in sports and in everyday life. The project was first focused on improving the technical skills of athletes practicing wheelchair sports. After studies and discussions it however changed focus, to also deal with obstacles in everyday life and to help people using wheelchairs to learn more everyday movements. After practical workshops, a mechanical analysis of the wheelchair was made. Some types of movement patterns, such as balancing on the rear wheels and turning, was considered essential to study and the goal was also to get information about for example the speed and acceleration of the wheelchair. This was to be analysed in real time and then sonified in later steps. We developed a code torecognize and assess these movements, which is the product of the project.

Abstract [sv]

Detta är ett projekt som beskriver en del av utvecklingsprocessen för ett verktyg ämnat för rullstolsåkare i deras inlärningsprocess av nya och viktiga rörelser i vardagen och i sportsammanhang. Processen började med en undersökning, med hjälp av rullstolsburna,av vilka rörelser som ansågs svåra och vilka som ansågs använd bara inom sport och i vardagen. Projektet var först inriktat mot att förbättra tekniken hos idrottsutövare inom rullstolssporter. Efter undersökningar och diskussioner bytte det dock senare bana, till att även handla om hinder i vardagen och att hjälpa rullstolsåkare att lära sig vardagligare rörelser. Efter praktiska workshops gjordes en mekanisk analys av rullstolen. Vissa typer av rörelsemönster, till exempel balansering på bakhjul och sväng, ansågs vara viktiga att studera och målet var även att få information om till exempel rullstolens hastighet och acceleration. Detta skulle analyseras i realtid för att sedan sonifieras i senare steg. Vi utvecklade en kod för att känna igen och bedöma dessa rörelser, vilket är produkten av projektet.

Place, publisher, year, edition, pages
2015. , 29 p.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-167132OAI: oai:DiVA.org:kth-167132DiVA: diva2:813123
Supervisors
Examiners
Available from: 2015-05-21 Created: 2015-05-21 Last updated: 2017-09-19Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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Output format
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