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Active Learning Program for Stroke (ALPS) was designed, and testing was done on patients for a while and was found successful in extending cognitive strategies. [66] Socially assistive robotics (SAR) SAR was tested, and kinematic and temporal features related to fatigue were determined. The test was done for a sit-to-stand test and concluded that three kinematic features had a relation with fatigue. [71] Support vector machine (SVM) The feasibility of SVM for the identification of the locomotion from sEMG signals produced by the muscles for rehabilitation robotics was calculated.

Application of virtual reality, SVMs, etc. still requires innovative thinking and ingenuity. Robots with multiple degrees of freedom and robotic-assisted therapy have constantly been a subject of research. The readers interested in pursuing this field could consider the above topics for their study.

1.4 Conclusion

This chapter presents a review of the progress of rehabilitation robotics. Robots have found application in neurology, cognitive science, stroke, biomechanical, machine interface, assistive, motion detection, limb injury, etc. They have been used to aid surgeries and therapies, to take care of neurological disorders of patients, assisting patients for movement, etc. Adaptive robotics has been developed catering to patient needs and abilities. Moreover, the application of robots in orthotics, prosthetics, and neuro-rehabilitation has been intriguing. This chapter also presents the scenario of rehabilitation robotics in Europe and the northern part of America. The scope of research lies in the exploration of virtual reality, neural networks, and SVM, and application to robotics. The use of sensing technology in the rehabilitation robots with various degrees of freedom is also worthy of attention. The readers are encouraged to pursue this line of research.

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