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EEG- EMG-Based Interface For Upper Limb Exoskeleton – A Review

Show simple item record De Marzi, Laura Peixoto, Nathalia 2022-05-16T18:31:43Z 2022-05-16T18:31:43Z 2022-05
dc.description.abstract The second most common cause of death in the world is cerebrovascular accident or stroke, and rehabilitation plays an important role to help the survivors of such accidents. Rehabilitation exercises are essential to speed up the process of recovery and regain independence, not only for post stroke cases but, also, for every patient who suffers of other neuromuscular diseases, such as spinal cord injuries or multiple sclerosis. The aging of the population, the increase of accident, and therefore, the increase of quality and quantity of rehabilitation needed, have led to the development of new techniques and assistance methods for recovery. Exoskeleton robotic devices have been developed to help the rehabilitation process, complementing the manual work of therapists. What is needed for an efficient and smooth implementation of this device is an advance interface between the wearable robot and the human. In this paper we have presented and analyzed two possible control input signals for exoskeletons, specifically electromyography (EMG) and electroencephalography (EEG). We’ve delved deeper into these two techniques, studying their advantages and disadvantages. Advantages are for example their inherent intuitiveness and effectiveness. On the other hand there is high inter-subject variability of the EMG, and the non-invasiveness and high temporal resolution but relatively poor spatial resolution of the EEG technique. The purpose of this review is to study and contrast the two main techniques when used as brain machine interface for the control of exoskeletons. en_US
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri *
dc.subject electromyography en_US
dc.subject electroencephalography en_US
dc.subject exoskeleton en_US
dc.title EEG- EMG-Based Interface For Upper Limb Exoskeleton – A Review en_US
dc.type Article en_US

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