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In robot-assisted upper limb rehabilitation, detecting the intentions of hemiplegic patients is essential towards assisting the patients to actively exercise instead of driving passive motions. Many interactive channels, such as voice, EMG and EEG, have been studied to estimate the motion intentions. However, limitations of these techniques, such as high complexity, have constrained their applications...
Virtual Reality (VR) presents a promising future in the field of rehabilitation due to its advantages brought to the training process as is indicated in many articles and researches. In this paper, we describe a novel method in developing a virtual training environment for a 5 degrees of freedom (DOF) upper limb rehabilitation robot which has been designed to help provide assistance for patients who...
We present a novel object detection framework that uses the local shape patches features combining the interclass global features information. A supervised local model learning architecture is proposed: a novel interest point descriptor is proposed and applied to detect the local shape patches, the local shape patches are formed by chains of several connected contour segments. Then the object local...
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