Improvement in hand function to promote functional recovery is one of the major goals of stroke rehabilitation. This paper introduces a newly developed exoskeleton for hand rehabilitation with a user-centered design concept, which integrates the requirements of practical use, mechanical structure and control system. The paper also evaluated the function with two prototypes in a local hospital. Results of functional evaluation showed that significant improvements were found in ARAT (P=0.014), WMFT (P=0.020) and FMA_WH (P=0.021). Increase in the mean values of FMA_SE was observed but without significant difference (P=0.071). The improvement in ARAT score reflects the motor recovery in hand and finger functions. The increased FMA scores suggest there is motor improvement in the whole upper limb, and especially in the hand after the training. The product met patients’ requirements and has practical significance. It is portable, cost effective, easy to use and supports multiple control modes to adapt to different rehabilitation phases.
via Design and development of a portable exoskeleton for hand rehabilitation – IEEE Journals & Magazine
In this study, we have been developing a rehabilitation system that combining a motor and sensory function recovery device and a measuring device for a hand sensory. These devices are purposely developed for paralyzed patients. The rehabilitation system was named HSRS (Hand Sensory Rehabilitation system) and it’s consists of a training device hand sensory function, a computer to control the device, and an external monitor displays an obtained data from sensors. The training device is able to applycontinuous mechanical stimulation to the hand of a user by grasping the device probe. On the monitor, the self-made Graphical User Interface (GUI) is displayed. An operator instructs the user to match the target value to the measured value in the training. When the user operates the switches, and the device measures the point that contacted with the probe. We did two experiments by using these devices. One is stimulus evaluation experiment. In this experiment, three frequencies (30 [Hz], 60[Hz], 100[Hz]) were given to the human hand and we verified which frequency was most effective. Using a slide caliper and the device to measure sensory function, we evaluated the difference in sensory degree of each healthy subject between before and after using the training device. As a result, we found 60[Hz] is the most effective frequency. In the second experiment, we let a subject follow a target value of GUI. In this experiment, we examined the relation between the sensory function and the motor function and investigated the best evaluation parameter when training the paralyzed patient. As a result, we didn’t get difference in the results when comparing in sports experience. However, we got a particularly big difference of the magnitude of the residual during accelerated and deceleration time of the gripping with other items. Moreover, when comparing those who are good and not good sensory in sensory function measurement experiments, there was a tendency that the subjects with not good sensory have the bigger difference with the target value. We confirmed the utility of the measuring devise and the relationship between motor and sensory function.
via Hand Sensory Rehabilitation System Which Incorporated Visual and Tactile Feedback – IEEE Conference Publication
Rehabilitation is an important process to restore muscle strength and joint’s range of motion. This paper proposes a biomechatronic design of a robotic arm that is able to mimic the natural movement of the human shoulder, elbow and wrist joint. In a preliminary experiment, a subject was asked to perform four different arm movements using the developed robotic arm for a period of two weeks. The experimental results were recorded and can be plotted into graphical results using Matlab. Based on the results, the robotic arm shows encouraging effect by increasing the performance of rehabilitation process. This is proven when the result in degree value are accurate when being compared with the flexion of both shoulder and elbow joints. This project can give advantages on research if the input parameter needed in the flexion of elbow and wrist.
According to the United Nations (UN), by 2030 the number of people over 60 years will increase by 56 per cent, from 901 million to more than 1.4 billion worldwide . As the number of older persons is expected to grow, it is imperative that government and private health care providers prepare adequate and modern facilities that can provide quality services for the needs of older persons especially in rehabilitation centers. Implementation of robotic technology in rehabilitation process is a modern method and definitely can contribute in this policy and capable in promoting early recovery and motor learning . Furthermore, systematic application of robotic technology can produce significant clinical results in motor recovery of post-traumatic central nervous system injury by assisting in physical exercise based on voluntary movement in rehabilitation .
via Biomechatronics design of a robotic arm for rehabilitation – IEEE Conference Publication
Upper limb (UL) hemiparesis is frequently a disabling consequence of stroke. The ability to improve UL functioning is associated with motor relearning and experience dependent neuroplasticity. Interventions such as non-invasive brain stimulation (NIBS) and task-practice in virtual environments (VEs) can influence motor relearning as well as adaptive plasticity. However, the effectiveness of a combination of NIBS and task-practice in VEs on UL motor improvement has not been systematically examined. The objective of this review was to examine the evidence regarding the effectiveness of combining NIBS with task-practice in VEs on UL motor impairment and activity levels. A systematic review of the published literature was conducted using standard methodology. Study quality was assessed using the PEDro scale and Down’s and Black checklist. Four studies examining the effects of a combination of NIBS (involving transcranial direct current stimulation; tDCS and repetitive transcranial magnetic stimulation; rTMS) were retrieved. Of these, three studies were randomized controlled trials (RCTs) and one was a cross-sectional study. There was 1a level evidence that the combination of NIBS and task-practice in a VE was beneficial in the sub-acute stage. A combination of training in a VE with rTMS as well as tDCS was beneficial for motor improvements in the UL in sub-acute stage of stroke (1b level). The combination was not found to be superior compared to task practice in VEs alone in the chronic stage (1b level). The results suggest that people with stroke may be capable of improving levels of motor impairment and activity in the sub-acute stage if their rehabilitation program involves a combination on NIBS and VE training. Emergent questions regarding the use of more sensitive outcomes, different types of stimulation parameters, locations and training environments still need to be addressed.
Source: Virtual reality and non-invasive brain stimulation in stroke: How effective is their combination for upper limb motor improvement? – IEEE Xplore Document
Chronic wrist impairment is frequent following stroke and negatively impacts everyday life. Rehabilitation of the dysfunctional limb is possible but requires extensive training and motivation. Wearable training devices might offer new opportunities for rehabilitation. However, few devices are available to train wrist extension even though this movement is highly relevant for many upper limb activities of daily living. As a proof of concept, we developed the eWrist, a wearable one degree-of-freedom powered exoskeleton which supports wrist extension training. Conceptually one might think of an electric bike which provides mechanical support only when the rider moves the pedals, i.e. it enhances motor activity but does not replace it. Stroke patients may not have the ability to produce overt movements, but they might still be able to produce weak muscle activation that can be measured via surface electromyography (sEMG). By combining force and sEMG-based control in an assist-as-needed support strategy, we aim at providing a training device which enhances activity of the wrist extensor muscles in the context of daily life activities, thereby, driving cortical reorganization and recovery. Preliminary results show that the integration of sEMG signals in the control strategy allow for adjustable assistance with respect to a proxy measurement of corticomotor drive.
Source: The eWrist — A wearable wrist exoskeleton with sEMG-based force control for stroke rehabilitation – IEEE Xplore Document