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Up to now, with the increasing of the elderly population, more and more patients are suffering from hemiplegia. The need for hemiplegic rehabilitation is increasing quickly. As traditional rehabilitation, each patient must be treated by therapist, one by one. However, because of the different levels of therapists, the rehabilitation cannot be performed as the as the same. Normally, the rehabilitation status diagnosing is still be performed by therapists with the subjective experience. It caused the inhomogeneity on rehabilitation evaluation. It also sometimes causes negative influence on the rehabilitation effect. To solve these problems, many researches focusing on assessing the status of the hemiplegic patients quantitatively are proposed rehabilitation evaluation systems. Rehabilitation motion detection is the basis of the evaluation system, and it requires the participation of therapist. In this paper, a method is presented to detect lower limb motion of hemiplegic patients based on inertial sensor technology. The gesture quaternion of lower limb can be obtained through LPMS. With the matrix and Euler angle changing algorithm, combining with the simplified lower limb motion model, the rotation angle of joint can be computed. Finally, the curve of rotation angle of knee is established.1 © 2016 IEEE.

Up to now, with the increasing of the elderly population, more and more patients are suffering from hemiplegia. The need for hemiplegic rehabilitation is increasing quickly. As traditional rehabilitation, each patient must be treated by therapist, one by one. However, because of the different levels of therapists, the rehabilitation cannot be performed as the as the same. Normally, the rehabilitation status diagnosing is still be performed by therapists with the subjective experience. It caused the inhomogeneity on rehabilitation evaluation. It also sometimes causes negative influence on the rehabilitation effect. To solve these problems, many researches focusing on assessing the status of the hemiplegic patients quantitatively are proposed rehabilitation evaluation systems. Rehabilitation motion detection is the basis of the evaluation system, and it requires the participation of therapist. In this paper, a method is presented to detect lower limb motion of hemiplegic patients based on inertial sensor technology. The gesture quaternion of lower limb can be obtained through LPMS. With the matrix and Euler angle changing algorithm, combining with the simplified lower limb motion model, the rotation angle of joint can be computed. Finally, the curve of rotation angle of knee is established. © 2016 IEEE.

With the aging population problem getting more and more aggravated, the number of hemiplegia patients increases rapidly, which results in the increasing requirement of rehabilitation training for regaining the body movement function. Taking advantages of rehabilitation robots makes the rehabilitation training more scientific and efficient compared to traditional rehabilitation measures such as manual training. By now, many types of rehabilitation robots have been proposed by researchers. However, from the view of the physiological structure, many of them can't well fit the motion characteristics. Ankle plays an important role in standing, walking and so on. As the motion of these robots is different from the motion characteristics of ankles, it would make an undesired influence on the training effect. Rehabilitation robots have many structures, and they are mainly serial mechanism and parallel mechanism. However, serial mechanism is inconvenient to package. In this paper, a new type of parallel mechanism with five degrees of freedom was proposed. Compared to serial mechanism, parallel mechanism is convenient to package and it has larger motion area. It enables ankles to rotate around the rotary center of the ankle. With the screw theory, the degree of freedom was calculated. To verify the working space of the mechanism, the working space simulation was carried out by Matlab. Finally, the quantity and position of motors are determined. © 2016 IEEE.

With the aggravation of ageing society, the number of hemiplegic patients has increased rapidly. As a result, the requirement of rehabilitation training has made a huge increase. In order to help hemiplegic patients to get a better rehabilitation and help occupational therapists to reduce working pressure, series of rehabilitation training robot has been developed. Although the rehabilitation robot has been improved greatly for meeting various requirements, most of rehabilitation robots still just focus on rehabilitation training of single joint and neglect the recovery of damaged nervous system. In order to offer patients comprehensive rehabilitation training and help recovering nervous system, a new MKW series rehabilitation robots are designed to realize wrist and hand independent and cooperative training in our team. As the MKW-I is not convenient for use and its sensors' accuracy would be heavily influenced by environment. Therefore, MKW-II is designed for better rehabilitation effectiveness. For these reasons, we propose the MKW-II, which can perfectly solve these problems. The improvement of mechanism structure and improvement of related sensors will be introduced detailly in this paper. © 2016 IEEE.