One typical application of a robotic exoskeleton is to automate rehabilitation, where the robot is worn by a stroke patient and provides assistance to help perform repetitive motions and regain motor functions. The deployment of exoskeletons can alleviate the shortage of experienced therapists and would also play a vital role in countries with aging populations. However, the intelligence level of existing exoskeletons is relatively low, wherein a robot cannot adapt to either the online change of a subject’s motion (e.g., the gait pattern) or the variation of his/her body parameters (i.e., a new subject who is going to wear the robot), potentially resulting in conflict between human and robot and possibly even leading to physical damage. As such, the application of a robotic exoskeleton in clinical studies is limited. This article introduces a new bilateral exoskeletal assistive robot for rehabilitation (BEAR-H) in which the main novelty is the integration of multiple intelligent features, such as gait recognition and synchronization, cloud-computing diagnosis, and individualized gait generation. Such an integration helps the robot to better understand the patient’s condition and hence provide effective assistance, by the end achieving smart rehabilitation. BEAR-H is a successfully commercialized product, and its performance has been validated in actual clinical studies with 30 patients, producing experimental results from different aspects that are analyzed and presented.
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