Hand paralysis is one of the most common complications in stroke patients, which severely impacts their daily lives. This paper presents a wearable hand rehabilitation system that supports both mirror therapy and task-oriented therapy. A pair of gloves, i.e., a sensory glove and a motor glove, was designed and fabricated with a soft, flexible material, providing greater comfort and safety than conventional rigid rehabilitation devices. The sensory glove worn on the non-affected hand, which contains the force and flex sensors, is used to measure the gripping force and bending angle of each finger joint for motion detection. The motor glove, driven by micromotors, provides the affected hand with assisted driving-force to perform training tasks. Machine learning is employed to recognize the gestures from the sensory glove and to facilitate the rehabilitation tasks for the affected hand. The proposed system offers 16 kinds of finger gestures with an accuracy of 93.32%, allowing patients to conduct mirror therapy using fine-grained gestures for training a single finger and multiple fingers in coordination. A more sophisticated task-oriented rehabilitation with mirror therapy is also presented, which offers six types of training tasks with an average accuracy of 89.4% in real-time.
via A Wearable Hand Rehabilitation System with Soft Gloves – IEEE Journals & Magazine
Previous studies on robotic rehabilitation have shown that subjects’ active participation and effort involved in rehabilitation training can promote the performance of therapies. In order to improve the voluntary effort of participants during the rehabilitation training, assist-as-needed (AAN) control strategies regulating the robotic assistance according to subjects’ performance and conditions have been developed. Unfortunately, the heterogeneity of patients’ motor function capability in task space is not taken into account during the implementation of these controllers. In this paper, a new scheme called greedy AAN (GAAN) controller is designed for the upper limb rehabilitation training of neurologically impaired subjects. The proposed GAAN control paradigm includes a baseline controller and a Gaussian RBF network that is utilized to model the functional capability of subjects and to provide corresponding a task challenge for them. In order to avoid subjects’ slacking and encourage their active engagement, the weight vectors of RBF networks evaluating subjects’ impairment level are updated based on a greedy strategy that makes the networks progressively learn the maximum forces over time provided by subjects. Simultaneously, a challenge level modification algorithm is employed to adjust the task challenge according to the task performance of subjects. Experiments on 12 subjects with neurological impairment are conducted to validate the performance and feasibility of the GAAN controller. The results show that the proposed GAAN controller has significant potential to promote the subjects’ voluntary engagement during training exercises.
via A Greedy Assist-as-Needed Controller for Upper Limb 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
In this paper, a novel walker robot is proposed for post-stroke gait rehabilitation. It consists of an omni-directional mobile platform which provides high mobility in horizontal motion, a linear motor that moves in vertical direction to support the body weight of a patient and a 6-axis force/torque sensor to measure interaction force/torque between the robot and patient. The proposed novel walker robot improves the mobility of pelvis so it can provide more natural gait patterns in rehabilitation. This paper analytically derives the kinematic and dynamic models of the novel walker robot. Simulation results are given to validate the proposed kinematic and dynamic models.
Stroke is one of the leading causes of death overall the world . According to a report from the American Heart Association, around 8 million population experience stroke onset every year worldwide . It remains many sequalae including a pathological walking pattern. Impaired walking function refrains stroke survivors from not only activities of daily living but also social participation, which causes poststroke depression in stroke survivors . Unfortunately, the depressed mood also negatively influences on the recovery of daily functions –. Moreover, decreased mobility is associated with other diseases such as obesity which leads to comorbidity then raise the possibility to get recurrent strokes , . This might become a vicious circle and form a huge economic burden for governments .
via Modelling and control of a novel walker robot for post-stroke gait rehabilitation – IEEE Conference Publication
The paper suggests a therapeutic device for hemiparesis that combines robot-assisted rehabilitation and mirror therapy. The robot, which consists of a motor, a position sensor, and a torque sensor, is provided not only to the paralyzed wrist, but also to the unaffected wrist to induce a symmetric movement between the joints. As a user rotates his healthy wrist to the direction of either flexion or extension, the motor on the damaged side rotates and reflects the motion of the normal side to the symmetric angular position. To verify performance of the device, five stroke patients joined a clinical experiment to practice a 10-minute mirroring exercise. Subjects on Brunnstrom stage 3 had shown relatively high repulsive torques due to severe spasticity toward their neutral wrist positions with a maximum magnitude of 0.300kgfm, which was reduced to 0.161kgfm after the exercise. Subjects on stage 5 practiced active bilateral exercises using both wrists with a small repulsive torque of 0.052kgfm only at the extreme extensional angle. The range of motion of affected wrist increased as a result of decrease in spasticity. The therapeutic device not only guided a voluntary exercise to loose spasticity and increase ROM of affected wrist, but also helped distinguish patients with different Brunnstrom stages according to the size of repulsive torque and phase difference between the torque and the wrist position.
Source: Robot-assisted mirroring exercise as a physical therapy for hemiparesis rehabilitation – IEEE Conference Publication
Lower extremity function recovery is one of the most important goals in stroke rehabilitation. Many paradigms and technologies have been introduced for the lower limb rehabilitation over the past decades, but their outcomes indicate a need to develop a complementary approach. One attempt to accomplish a better functional recovery is to combine bottom-up and top-down approaches by means of brain-computer interfaces (BCIs). In this study, a BCI-controlled robotic mirror therapy system is proposed for lower limb recovery following stroke. An experimental paradigm including four states is introduced to combine robotic training (bottom-up) and mirror therapy (top-down) approaches. A BCI system is presented to classify the electroencephalography (EEG) evidence. In addition, a probabilistic model is presented to assist patients in transition across the experiment states based on their intent. To demonstrate the feasibility of the system, both offline and online analyses are performed for five healthy subjects. The experiment results show a promising performance for the system, with average accuracy of 94% in offline and 75% in online sessions.
Source: EEG-guided robotic mirror therapy system for lower limb rehabilitation – IEEE Conference Publication
The optimal conditions inducing proper brain activation during performance of rehabilitation robots should be examined to enhance the efficiency of robot rehabilitation based on the concept of brain plasticity. In this study, we attempted to investigate differences in cortical activation according to the speeds of passive wrist movements performed by a rehabilitation robot for stroke patients. 9 stroke patients with right hemiparesis participated in this study. Passive movements of the affected wrist were performed by the rehabilitation robot at three different speeds: 0.25 Hz; slow, 0.5Hz; moderate and 0.75 Hz; fast. We used functional near-infrared spectroscopy to measure the brain activity during the passive movements performed by a robot. Group-average activation map and the relative changes in oxy-hemoglobin (ΔOxyHb) in two regions of interest: the primary sensory-motor cortex (SM1); premotor area (PMA) and region of all channels were measured. In the result of group-averaged activation map, the contralateral SM1, PMA and somatosensory association cortex (SAC) showed the greatest significant activation according to the movements at 0.75 Hz, while there is no significantly activated area at 0.5 Hz. Regarding ΔOxyHb, no significant diiference was observed among three speeds regardless of region. In conclusion, the contralateral SM1, PMA and SAC showed the greatest activation by a fast speed (0.75 Hz) rather than slow (0.25 Hz) and moderate (0. 5 Hz) speed. Our results suggest an optimal speed for execution of the wrist rehabilitation robot. Therefore, we believe that our findings might point to several promising applications for future research regarding useful and empirically-based robot rehabilitation therapy.
Source: A pilot study on the optimal speeds for passive wrist movements by a rehabilitation robot of stroke patients: A functional NIRS study – IEEE Xplore Document
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 .
Source: Design factors and opportunities of rehabilitation robots in upper-limb training after stroke – IEEE Xplore Document
Stroke survivors who experience severe hemipare-sis often cannot completely recover the use of their hand and arm. Many of the rehabilitation devices currently available are designed to increase the functional recovery right after the stroke when, in some cases, biological restoring and plastic reorganization of the central nervous system can take place. However, this is not always the case. Even after extensive therapeutic interventions, the probability of regaining functional use of the impaired hand is low. In this respect, we present a novel robotic system composed of a supernumerary robotic finger and a wearable cutaneous finger interface. The supernumerary finger is used to help grasping objects while the wearable interface provides information about the forces exerted by the robotic finger on the object being held. We carried out two experiments, enrolling 16 healthy subjects and 2 chronic stroke patients. Results showed that using the supernumerary finger greatly improved the grasping capabilities of the subjects. Moreover, providing cutaneous feedback significantly improved the performance of the considered task and was preferred by all subjects.
Source: A soft robotic supernumerary finger and a wearable cutaneous finger interface to compensate the missing grasping capabilities in chronic stroke patients – IEEE Xplore Document