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.
Recent technological developments regarding wearable soft-robotic devices extend beyond the current application of rehabilitation robotics and enable unobtrusive support of the arms and hands during daily activities. In this light, the HandinMind (HiM) system was developed, comprising a soft-robotic, grip supporting glove with an added computer gaming environment. The present study aims to gain first insight into the feasibility of clinical application of the HiM system and its potential impact. In order to do so, both the direct influence of the HiM system on hand function as assistive device and its therapeutic potential, of either assistive or therapeutic use, were explored. A pilot randomized clinical trial was combined with a cross-sectional measurement (comparing performance with and without glove) at baseline in 5 chronic stroke patients, to investigate both the direct assistive and potential therapeutic effects of the HiM system. Extended use of the soft-robotic glove as assistive device at home or with dedicated gaming exercises in a clinical setting was applicable and feasible. A positive assistive effect of the soft-robotic glove was proposed for pinch strength and functional task performance ‘lifting full cans’ in most of the five participants. A potential therapeutic impact was suggested with predominantly improved hand strength in both participants with assistive use, and faster functional task performance in both participants with therapeutic application.
The occurrence of strokes has been progressively increasing. Upper limb recovery after stroke is more difficult than lower limb. One of the rapidly expanding technologies in post-stroke rehabilitation is robot-aided therapy. The advantage of robots is that they are able to deliver highly repetitive therapeutic tasks with minimal supervision of a therapist. However, from the literature, the focus of robotic design in stroke rehabilitation has been technology-driven. Clinical and therapeutic requirements were not seriously considered in the design of rehabilitation robots. The purpose of this study was twofold: (1) demonstrate the missing elements of current robot-aided therapy; (2) identify design factors and opportunities of rehabilitation robots (in upper-limb training after stroke). In this study, we performed a literature review on articles relevant to rehabilitation robots in upper-limb training after stroke. We identified the design foci of current rehabilitation robots for upper limb stroke recovery. Using the therapeutic framework for stroke rehabilitation in occupational therapy, we highlighted design factors and opportunities of rehabilitation robots. The outcomes of this study benefit the robotics design community in the design of rehabilitation robots.
A robot is defined as a machine programmable to perform and modify tasks in response to changes in the environment . The benefits of robots are noticeable in productivity, safety, and in saving time and money. The advancement of robot technologies in the past decade caused the wide adoption of robots in our lives and in the society. For instance, in education, robots were implemented in undergraduate courses to teach core artificial intelligence concepts, e.g., algorithms for searching tree data structures . In agriculture, robotic milking systems (being able to reduce labor/operational costs) were installed to replace conventional milking that gave cows the freedom to be milked throughout the day . In healthcare, service robots were implemented to provide functional assistance for the elderly in home environments, e.g., bringing medication for the emergency and picking up heavy objects low on the ground .
Rehabilitation robots have become increasingly popular for stroke rehabilitation. However, the high cost of robots hampers their implementation on a large scale. This study 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 minutes 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 (FMA-FW). Significant improvement of active range of motion (AROM) 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.
Hemianopia leads to severe impairment of spatial orientation and mobility. In cases without macular sparing an additional reading disorder occurs. Persistent visual deficits require rehabilitation. The goal is to compensate for the deficits to regain independence and to maintain the patient’s quality of life. Spontaneous adaptive mechanisms, such as shifting the field defect towards the hemianopic side by eye movements or eccentric fixation, are beneficial, but often insufficient. They can be enhanced by training, e.g., saccadic training to utilize the full field of gaze in order to improve mobility and by special training methods to improve reading performance. At present only compensatory interventions are evidence-based.
In the rehabilitation training and assessment of upper limbs, the conventional kinematic model treats the arm as a serial manipulator and maps the rotations in the joint space to movements in the Cartesian space. While this model brings simplicity and convenience, and thus has been overwhelming used, its accuracy is limited, especially for the distal parts of the upper limb that execute dexterous movements.
In this paper, a novel kinematic model of the arm has been proposed, which has been inspired by the biomechanical analysis of the forearm and wrist anatomy. One additional parameter is introduced into the conventional arm model, and then both the forward and inverse kinematic models of five parameters are derived for the motion of upper arm medial/lateral rotation, elbow flexion/extension, forearm pronation/supination, wrist flexion/extension and ulnar/radial deviation. Then, experiments with an advanced haptic interface have been designed and performed to examine the presented arm kinematic model. Data analysis revealed that accuracy and robustness can be significantly improved with the new model.
This extended arm kinematic model will help device development, movement training and assessment of upper limb rehabilitation.
Finger recovery is much harder than other parts on the upper limbs, because finger recovery movement has several key problems need to overcome, including high precision of movement, high control resolution requirements, variable data with different person, as well as the fuzzy signal during the movement. In order to overcome the difficulties, a new scheme of finger recovery is presented in the paper based on symmetric rehabilitation. In the paralyzed hand side, a mechanical exoskeleton hand is designed and simulated to provide skeletal traction, while in the regular hand side, the curve magnitude of every joint during movement is detected. Then the hand motion is analyzed and recognized using Multi-class SVM. Many candidates were chosen to perform the experiment, and the data produced by the candidates were divided the training parts and recognition parts. Experiments shows that the Multi-class SVM is effective and practical for classification and recognition, and could be helpful in the finger recovery process.
This paper describes the design of a FES system automatically controlled in a closed loop using a Microsoft Kinect sensor, for assisting both cylindrical grasping and hand opening. The feasibility of the system was evaluated in real-time in stroke patients with hand function deficits. A hand function exercise was designed in which the subjects performed an arm and hand exercise in sitting position. The subject had to grasp one of two differently sized cylindrical objects and move it forward or backwards in the sagittal plane. This exercise was performed with each cylinder with and without FES support. Results showed that the stroke patients were able to perform up to 29% more successful grasps when they were assisted by FES. Moreover, the hand grasp-and-hold and hold-and-release durations were shorter for the smaller of the two cylinders. FES was appropriately timed in more than 95% of all trials indicating successful closed loop FES control. Future studies should incorporate options for assisting forward reaching in order to target a larger group of stroke patients.
This study investigates the effect of combining both mirror therapy with Electrical Stimulation (ES) on improvement of the function of lower extremity compared to conventional therapy. 18 stroke survivors (sub acute stage) were recruited, 9 of them were randomly assigned to receive conventional treatment and another 9 started the mirror therapy combined with ES treatment. Duration of each session in both interventions was 50 minutes, done 4 times per week over two weeks. After 2 weeks, subjects took one week rest before switching they type of treatment; those started with conventional therapy continued with mirror therapy combined with ES, and vice versa. The duration of this phase was 2 weeks with same schedule as the 1st one. Ankle dorsi-flexion range of motion, lower extremity sensory-motor function, and walking duration were measured at baseline, after 1st 2 weeks, and immediately after the last two weeks, and 4 weeks after end of training (retention test). Repeated Measures ANCOVA was done to compare outcome measures scores in both groups and between all testing days, and paired T-test was used measure the difference between groups. Significant increase in all outcome measures was found after the (MT+ES) training, which is higher than conventional therapy training (p<;0.0001). In conclusion, the results suggest that combination of mirror therapy and ES is more effective than conventional therapy in improving lower limb motor function after stroke.
Stroke is a sudden loss of the blood supply to brain tissues where a focal neurological disturbance of brain function rapidly develops. The symptoms of stroke last more than 24 hours and depend on the area of the brain that has been affected. Lower-extremity motor function after stroke is often impaired, causing restrictions in function, gait, and postural performance . Because ankle is one of the most important joints in gait, especially related to dorsiflexion movement , the gait performance is highly diminished as a result of ankle movement impairment . Recovery is most prominent within the first three to six months after stroke. Thus, implementation of intensive therapy within this duration post stroke can lead to faster improvement in activities . Conventional treatment approaches (like Brunnstrom’s approach or Bobath’s approach) for hemiplegic patients have been used for many years, even though they are not always evidence-based and their neurophysiologic background is poorly investigated. On the other hand, several promising rehabilitation approaches have been recently developed addressing the motor recovery and balance of lower extremity in stroke; such as virtual reality, mental imagery, robotic interactive therapy, electrical stimulation, and mirror therapy .
Stroke patients usually have difficulties to conduct rehabilitation training themselves, due to no rehabilitation evaluation in time and dependence on doctors. In order to solve this problem, this paper proposes a motion rehabilitation and evaluation system based on the Kinect gesture measuring technology combining VR technology as well as traditional method of stroke rehabilitation. Real-time rehabilitation motion feedback is achieved by using Kinect motion capturing, customized skeleton modeling, and virtual characters constructed in Unity3D. The jitter problem of virtual characters following motion using Kinect is solved. Fidelity and interactivity of virtual rehabilitation training is improved. Our experiment validated the feasibility of this system preliminarily.
With an ageing population problem increasingly prominent, the number of hemiplegia patients is growing caused by stroke, which has a high morbidity and high mortality rate . Stroke can lead to the dysfunction of the brain central nervous, often characterized by language, cognitive or motor dysfunction , . The medical rehabilitation mechanism of stroke is based on neural plasticity theory and the theory of mirror neurons .