The thesis presents targeted sensor-based devices and methods for the training and assessment of upper extremity. These systems are all passive (non-actuated) thus intrinsically safe for (semi) independent use. An isometric assessment system is first presented, which uses a handle fixed on a force/torque sensor to investigate the force signal parameters and their relation to functional disability scales. The results from multiple sclerosis and healthy populations establish relation of isometric control and strength measures, its dependence on direction and how they are related to functional scales. The dissertation then introduces the novel platform MIMATE, Multimodal Interactive Motor Assessment and Training Environment, which is a wireless embedded platform for designing systems for training and assessing sensorimotor behaviour. MIMATE's potential for designing clinically useful neurorehabilitation systems was demonstrated in a rehabilitation technology course. Based on MIMATE, intelligent objects (IObjects) are presented, which can measure position and force during training and assessing of manipulation tasks relevant to activities of daily living. A preliminary study with an IObject exhibits potential metrics and techniques that can be used to assess motor performance during fine manipulation tasks. The IObjects are part of the SITAR system, which is a novel sensor-based platform based on a force sensitive touchscreen and IObjects. It is used for training and assessment of sensorimotor deficits by focusing on meaningful functional tasks. Pilot assessment study with SITAR indicated a significant difference in performance of stroke and healthy populations during different sensorimotor tasks. Finally the thesis presents LOBSTER, a low cost, portable, bimanual self-trainer for exercising hand opening/closing, wrist flexion/extension or pronation/supination. The major novelty of the system relies on exploiting the movement of the unaffected limb to train the affected limb, making it safe for independent use. Study with LOBSTER will determine its usability for home based use.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:656478 |
| Date | January 2013 |
| Creators | Hussain, Asif |
| Contributors | Burdet, Etienne |
| Publisher | Imperial College London |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/10044/1/24685 |
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