Stroke is the leading cause of severe disability worldwide, with up to 15 million of people suffer stroke every year. Survivors of stroke can recover their physical strength, provided they undergo proper rehabilitation. However, most of the rehabilitation centres provide only basic tools as they can rarely afford the expensive and advanced rehabilitation devices. Besides that, training with therapists is limited to few hours per week due to the large number of patients and the stroke patients are generally sent home once they are mobile, although their upper limbs functions are not recovered. Stroke patients need to continue training after stroke to avoid muscle contraction, but due to large number of patients, they are not able to train frequently in the hospital. Therefore, the goal of this project is to develop a low-cost, simple yet compact rehabilitation robot for stroke patient to train both upper and lower limbs reaching movement. Compact Rehabilitation Robot (CR2) is expected to help the stroke patients training reaching movement in an enhanced virtual reality environment with haptic feedback and to provide the stroke patients with a faster track towards recovery.
Stroke is the leading cause of disability. Reaching movement is the most important movement for many daily activities routine. Rehabilitation is to encourage and enhanced recovery process. Conventional rehabilitation is one-to-one intervention where labour intensive and lack of repeatability. In addition, the stroke assessments by physiotherapist are subjective and not independent. Thus, this paper will describe the design and development of non-motorized system for assessing the patients' motor function. This system will be used in the future to find the correlation between conventional assessments scales such Fugl-Mayer Assessment (FMA), Chedoke-McMaster Stroke Assessment Scale (CMSA) and Motor Assessment Scale (MAS) and robotic assessment.
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