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Autonomous Stroke Rehabilitation with Microsoft Kinect
KTH, School of Computer Science and Communication (CSC).
2014 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The aim of the work is to design and prototype an autonomous stroke rehabilitation system using the Microsoft Kinect camera that allows patients to undergo their rehab therapy from home without the constant need of specialized staff involvement in the rehab process. The rehab system tracks and computes a set of measurable indicators that reflect the rehab progress.

Today, patients that have suffered a stroke usually have to visit specialized centers to perform the rehabilitation program. This proves to be hard for the patients with motion disorders, especially in the northern parts of Sweden with large distances to the closest specialized center.

A prototype rehabilitation system for stroke patients has been designed and built. The system is autonomous and does not need constant staff involvement in the rehab process. The system tracks a set of rehabilitation indicators that reflect the patient rehabilitation progress (joint range of motion, reaction time, precision of motion, energy expenditure and training time). The system is constantly monitoring the patient to make sure the exercises are done correctly.

Attention has been paid at making the system more engaging and fun by adding some gamification features like providing real time feedback while exercising and by computing the training statistics with personal best indicators and progress meant to increase patient engagement and motivation. At last but not at least, the system has a multimodal interface including audio feedback that makes usage much more intuitive and simple. The system was designed and implemented and tested on regular users. The results prove that the system is able to achieve good results in automating the rehabilitation process and providing

Place, publisher, year, edition, pages
National Category
Computer and Information Science
URN: urn:nbn:se:kth:diva-153659OAI: diva2:753068
Available from: 2014-11-24 Created: 2014-10-07 Last updated: 2014-11-24Bibliographically approved

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