Rehabilitation robots have become increasingly popular for stroke rehabilitation. However, the high cost of robots hampers their implementation on a large scale. This paper implements the concept of a modular and reconfigurable robot, reducing its cost and size by adopting different therapeutic end effectors for different training movements using a single robot. The challenge is to increase the robot's portability and identify appropriate kinds of modular tools and configurations. Because literature on the effectiveness of this kind of rehabilitation robot is still scarce, this paper presents the design of a portable and reconfigurable rehabilitation robot and describes its use with a group of post-stroke patients for wrist and forearm training. Seven stroke subjects received training using a reconfigurable robot for 30 sessions, lasting 30 min per session. Post-training, statistical analysis showed significant improvement of 3.29 points (16.20%, p = 0.027) on the Fugl-Meyer assessment scale for forearm and wrist components. Significant improvement of active range of motion was detected in both pronation-supination (75.59%, p = 0.018) and wrist flexion-extension (56.12%, p = 0.018) after the training. These preliminary results demonstrate that the developed reconfigurable robot could improve subjects' wrist and forearm movement.

Stroke has now become the leading cause of severe disability. Rehabilitation robots are gradually becoming popular for stroke rehabilitation to improve motor recovery, as robotic technology can assist, enhance, and further quantify rehabilitation training for stroke patients. However, most of the available rehabilitation robots are complex and involve multiple degrees-of-freedom (DOFs) causing it to be very expensive and huge in size. Rehabilitation robots should be useful but also need to be affordable and portable enabling more patients to afford and train independently at home. This paper presents a development of an affordable, portable and compact rehabilitation robot that implements different rehabilitation strategies for stroke patient to train forearm and wrist movement in an enhanced virtual reality environment with haptic feedback.

There is a potential of using iRest, a non-motorized device in predicting MAS score.

Stroke is the leading cause of severe disability worldwide, with up to 15 million of people suffer stroke every year. Survivors of stroke can recover their physical strength, provided they undergo proper rehabilitation. However, most of the rehabilitation centres provide only basic tools as they can rarely afford the expensive and advanced rehabilitation devices. Besides that, training with therapists is limited to few hours per week due to the large number of patients and the stroke patients are generally sent home once they are mobile, although their upper limbs functions are not recovered. Stroke patients need to continue training after stroke to avoid muscle contraction, but due to large number of patients, they are not able to train frequently in the hospital. Therefore, the goal of this project is to develop a low-cost, simple yet compact rehabilitation robot for stroke patient to train both upper and lower limbs reaching movement. Compact Rehabilitation Robot (CR2) is expected to help the stroke patients training reaching movement in an enhanced virtual reality environment with haptic feedback and to provide the stroke patients with a faster track towards recovery.

Rehabilitation robots are gradually becoming popular for stroke rehabilitation to improve motor recovery. By using a robot, the patient may perform the training more frequently on their own, but they must be motivated to do so. Therefore, this project develops a set of rehabilitation training programs with different haptic modalities on Compact Rehabilitation Robot (CR2) -a robot used to train upper and lower limbs reaching movement. The paper present the developed haptic interface, Haptic Sense with five configurable haptic modalities that include sensations of weight, wall, spring, sponge and visual amplification. A combination of several haptic modalities was implemented into virtual reality games, Water Drop -a progressive training game with up to nine levels of difficulties that requires user to move the cup to collect the water drops.