Hand Rehabilitation System Research Articles

A Glove-Based Virtual Hand Rehabilitation System for Patients With Post-Traumatic Hand Injuries.

Recent studies have shown that virtual gamified therapy can be a potential adjunct to conventional orthopedic rehabilitation. However, the off-the-shelf gaming consoles used for virtual rehabilitation pose several practical challenges in deploying them in clinical settings. In this article, we present the design of a portable glove-based virtual hand rehabilitation system (RehabRelive Glove) that can be used at both clinics and homes for physiotherapy. We also evaluate the system's efficacy on patients with post-traumatic hand injuries. Thirty patients were randomly categorized into groups A (virtual rehabilitation) and B (conventional physiotherapy). Both groups received fifteen 25-minute sessions of respective therapy over three weeks. The wrist and finger joints' range of motion (ROM) and grip strength were measured every seven sessions to compare the efficacy. Group A showed about 1.5 times greater improvement in flexion/extension ROM of the wrist compared to Group B. While both groups improved finger ROM and grip strength with time, no significant difference was observed between the groups. The results suggest that the proposed virtual rehabilitation system effectively enables patients with hand injuries to recover ROM faster.

Hybrid Brain-Computer Interface Controlled Soft Robotic Glove for Stroke Rehabilitation.

Soft robotic glove controlled by a brain-computer interface (BCI) have demonstrated effectiveness in hand rehabilitation for stroke patients. Current systems rely on static visual representations for patients to perform motor imagination (MI) tasks, resulting in lower BCI performance. Therefore, this study innovatively used MI and high-frequency steady-state visual evoked potential (SSVEP) to construct a friendly and natural hybrid BCI paradigm. Specifically, the stimulation interface sequentially presented decomposed action pictures of the left and right hands gripping a ball, with the pictures flashing at specific stimulation frequencies (left: 34 Hz, right: 35 Hz). Integrating soft robotic glove as feedback, we established a comprehensive "peripheral - central - peripheral" hand rehabilitation system to facilitate the hand rehabilitation of patients. Filter bank common spatial pattern (FBCSP) and filter bank canonical correlation analysis (FBCCA) algorithms were used to identify MI and SSVEP signals, respectively. Additionally, we proposed a novel fusion algorithm to decide the final output of the system. The feasibility of the proposed system was validated through online experiments involving 12 healthy subjects and 9 stroke patients, achieving accuracy rates of 95.83 ± 6.83% and 63.33 ± 10.38, respectively. The accuracy of MI and SSVEP in 12 healthy subjects reached 81.67 ± 15.63% and 95.14 ± 7.47%, both lower than the accuracy after fusion, these results confirmed the effectiveness of the proposed algorithm. The accuracy rate was more than 50% in both healthy subjects and patients, confirming the effectiveness of the proposed system.

Conformal, stretchable, breathable, wireless epidermal surface electromyography sensor system for hand gesture recognition and rehabilitation of stroke hand function

Surface electromyography (sEMG) plays a significant role in the everyday practice of clinic hand function rehabilitation. The materials and design of current typical clinic sEMG electrodes are rigid Ag/AgCl or flexible polyimide (PI) film, which cannot provide a stable interface between electrodes and skin for adequate long-term high-quality data. Thus, conformal, soft, breathable, wireless epidermal sEMG sensor systems have broad potential relevance to clinic rehabilitation settings. Herein, we demonstrate a stretchable epidermal sEMG sensor array system with optimized materials and structure strategies for hand gesture recognition and hand function rehabilitation. The optimized serpentine structures with marvelous stretchability and improved fill ratio, provide lower impedance and high-quality sEMG signals. Moreover, the easy-to-use airhole method further ensures stable and long-term contact with the skin for recording. In addition, integrated with a customized flexible wireless data acquisition system, the capability for real-time 8-channel sEMG monitoring is developed, and taking together with the CNN-based algorithm, the system can automatically and reliably realize the 7 kinds of hand gestures with an accuracy of 81.02%. Moreover, the low-cost yet high-performance epidermal sEMG sensor system demonstrated its conceptual feasibility in quantitatively evaluation of stroke patient’s hand and facilitating human-robot collaboration in hand rehabilitation by proof-of-the-concept clinical testing.

BCI–VR-Based Hand Soft Rehabilitation System with Its Applications in Hand Rehabilitation After Stroke

The recovery of hand motor function can effectively improve the living standard of stroke patients and relieve their psychological anxiety. Traditional physical rehabilitation training is unable to target the cause of motor function loss; therefore, the rehabilitation effect is not ideal. The objective of this study is to propose a hand rehabilitation system combining brain–computer interface (BCI), soft hand rehabilitation glove and virtual reality (VR), and explore its effectiveness on hand movement disorders in stroke patients. The corresponding comparison experiments conducted on 11 stroke patients demonstrated that the proposed BCI-based hand rehabilitation system can not only mobilize more cerebral cortex to participate in the process of hand motor rehabilitation, but also enhance the muscle strength, muscle tension, and improve the hand motor dysfunction of stroke patients.

Development of immersive virtual reality-based hand rehabilitation system using a gesture-controlled rhythm game with vibrotactile feedback: an fNIRS pilot study.

Recently, virtual reality (VR) has been widely utilized with rehabilitation to promote user engagement, which has been shown to induce brain plasticity. In this study, we developed a VR-based hand rehabilitation system consisting of a personalized gesture-controlled rhythm game with vibrotactile feedback and investigated the cortical activation pattern induced by our system using functional near-infrared spectroscopy (fNIRS). Our system provides vibrotactile feedback as the user matches their hand gestures to VR targets customized to their pre-recorded hand gestures. Cortical activation was measured via fNIRS during 420 seconds of alternating gameplay and rest in 11 healthy subjects and one stroke survivor. Regions of interest (ROI) were the prefrontal cortex (PFC), the premotor cortex & the supplementary motor area (PMC&SMA), the primary sensorimotor cortex (SM1), and the somatosensory association cortex (SAC). The mean success rate of gesture matching among healthy subjects was 90 % with a standard deviation of 10.7 %, and the success rate of the stroke survivor was 79.6 %. The averaged cortical activation map for the 11 healthy subjects and the individual cortical activation map for the single stroke survivor showed increased hemodynamic responses of oxygenated hemoglobin (HbO) during the VR-based hand rehabilitation compared to the resting condition. Paired t-test analysis demonstrated a significant increase in HbO activation values in 19 out of 51 channels, corresponding to all ROIs except the left PFC and PMC&SMA, which exhibited high subject variability. The experimental results indicate that the proposed system successfully activated brain areas related to motor planning/execution, multisensory integration, and attention.

Proposal for the design and manufacture of a dynamic orthoses prototype for hand rehabilitation

Objetivos The objective of this research is to propose a prototype design of the dynamic orthosis adaptation system for hand rehabilitation. For this, the following methodology was used: the biomechanical and architectural foundations and the functional patterns of the fingers of the hands were previously analyzed, later the test subject was chosen and the corresponding measurements were taken, to finalize the design and manufacture of the prototype. The dynamic orthosis prototype proposed in this research is controlled by servomotors coupled to rings with rigid links, which transmit movement at a certain speed, from the motor axis to the fingers, simulating the biomechanical movements of flexion and extension. The design of this device is focused on users who do not have movement in the phalanges, and thus prevent their muscles from atrophying. The contribution of this research is the development of an economic device that can partially or totally replace the physiological therapies of a patient with problems in the upper limb (hand).

A Novel Soft Robotic Exoskeleton System for Hand Rehabilitation and Assistance Purposes

During the last decade, soft robotic systems, such as actuators and grippers, have been employed in various commercial applications. Due to the need to integrate robotic mechanisms into devices operating alongside humans, soft robotic systems concentrate increased scientific interest in tasks with intense human–robot interaction, especially for human-exoskeleton applications. Human exoskeletons are usually utilized for assistance and rehabilitation of patients with mobility disabilities and neurological disorders. Towards this direction, a fully functional soft robotic hand exoskeleton system was designed and developed, utilizing innovative air-pressurized soft actuators fabricated via additive manufacturing technologies. The CE-certified system consists of a control glove that copies the motion from the healthy hand and passes the fingers configuration to the exoskeleton applied on the affected hand, which consists of a soft exoskeleton glove (SEG) controlled with the assistance of one-axis flex sensors, micro-valves, and a proportional integral derivative (PID) controller. Each finger of the SEG moves independently due to the finger-dedicated motion control system. Furthermore, the real-time monitoring and control of the fabricated SEG are conducted via the developed software. In addition, the efficiency of the exoskeleton system was investigated through an experimental validation procedure with the involvement of healthy participants (control group) and patients, which evaluated the efficiency of the system, including safety, ergonomics, and comfort in its usage.

Data-Driven Predictive Control of Exoskeleton for Hand Rehabilitation with Subspace Identification.

This study proposed a control method, a data-driven predictive control (DDPC), for the hand exoskeleton used for active, passive, and resistive rehabilitation. DDPC is a model-free approach based on past system data. One of the strengths of DDPC is that constraints of states can be added to the controller while performing the controller design. These features of the control algorithm eliminate an essential problem for rehabilitation robots in terms of easy customization and safe repetitive rehabilitation tasks that can be planned within certain constraints. Experiments were carried out with a designed hand rehabilitation system under repetitive and various therapy tasks. Real-time experiment results demonstrate the feasibility and efficiency of the proposed control approach to rehabilitation systems.

What is the feasibility and patient acceptability of a digital system for arm and hand rehabilitation after stroke? A mixed-methods, single-arm feasibility study of the ‘OnTrack’ intervention for hospital and home use

ObjectivesArm weakness is common after stroke; repetitive activity is critical for recovery but people struggle with knowing what to do, volume, and monitoring progress. We studied the feasibility and acceptability...

The Software Interface of a Hybrid FES and Mechatronic Exoskeleton System for Hand Rehabilitation in Stroke People

Abstract This paper introduces novel contributions to the field of hand rehabilitation systems designed for stroke patients. The primary objective is to enhance voluntary movements in the paralyzed upper limbs, with a particular focus on hand functionality. The system, known as MANUTEX, comprises two main components: functional electrical stimulation (FES) implemented through a textile glove with embedded electrodes, connected to a programmable neurostimulator, and a mechatronic exoskeleton resembling a glove, powered by individual linear motors for each finger. These linear motors are controlled by a programmable microcontroller on a central board. MANUTEX delivers mirror therapy, a therapeutic approach requiring a sensory glove attached to the healthy hand. This sensory glove provides reference movements for the hybrid system located on the affected, impaired hand. An application installed on a computer serves as the control interface for the entire system. It reads movement data from the healthy hand and concurrently sends commands to both the FES and mechatronic exoskeleton glove, ensuring a balanced and synchronized therapeutic experience for the patient.

Synergistic Immediate Cortical Activation on Mirror Visual Feedback Combined With a Soft Robotic Bilateral Hand Rehabilitation System: A Functional Near Infrared Spectroscopy Study.

BackgroundMirror visual feedback (MVF) has been widely used in neurological rehabilitation. Due to the potential gain effect of the MVF combination therapy, the related mechanisms still need be further analyzed.MethodsOur self-controlled study recruited 20 healthy subjects (age 22.150 ± 2.661 years) were asked to perform four different visual feedback tasks with simultaneous functional near infrared spectroscopy (fNIRS) monitoring. The right hand of the subjects was set as the active hand (performing active movement), and the left hand was set as the observation hand (static or performing passive movement under soft robotic bilateral hand rehabilitation system). The four VF tasks were designed as RVF Task (real visual feedback task), MVF task (mirror visual feedback task), BRM task (bilateral robotic movement task), and MVF + BRM task (Mirror visual feedback combined with bilateral robotic movement task).ResultsThe beta value of the right pre-motor cortex (PMC) of MVF task was significantly higher than the RVF task (RVF task: -0.015 ± 0.029, MVF task: 0.011 ± 0.033, P = 0.033). The beta value right primary sensorimotor cortex (SM1) in MVF + BRM task was significantly higher than MVF task (MVF task: 0.006 ± 0.040, MVF + BRM task: 0.037 ± 0.036, P = 0.016).ConclusionOur study used the synchronous fNIRS to compare the immediate hemodynamics cortical activation of four visual feedback tasks in healthy subjects. The results showed the synergistic gain effect on cortical activation from MVF combined with a soft robotic bilateral hand rehabilitation system for the first time, which could be used to guide the clinical application and the future studies.

Psychological and Psychophysiological Responses to Challenge Variations for Virtual Hand Training in Game-based Smart Rehabilitation System

Background: Maintaining motivation is one of the most important characteristics of rehabilitation strategies for successful treatment. Understanding the underlying mechanism of mental state is helpful for developing new therapeutic methods based on virtual reality and serious game technologies. Objective: The present study aims to develop a cost-benefit game-based hand rehabilitation system and assess the influence on the psychological state of subjects when they interact with a virtual reality environment in different task difficulty levels. Methods: First, we introduced a low-cost smart hand rehabilitation system based on the Leap Motion tracker; then, the experimental study was performed with 20 healthy participants. Their mental states were evoked using interaction with two separate games in four different difficulty levels. Three measures from the SAM self-reported test described as a psychological response to this condition, and also four features were extracted from Photoplethysmogram signal in order to quantify psychophysiological responses of Autonomic Nervous System. Results: Comparison of the different difficulty levels revealed significant changes in arousal and dominance correspond to under challenging and over the challenging condition, respectively. The results of psychophysiological feature analysis showed significant differences only for the standard deviation of intervals between consecutive heartbeats. Conclusion: The developed system is a low-cost smart solution that can be useful for upper limb neurological rehabilitation. Regulating difficulty parameters of the implemented game can be used to influence the motivation of users through rehabilitation procedures. It seems Photoplethysmogram is an appropriate psychophysiological indicator of mental states, but further studies are required.

Multi-point surface FES hand rehabilitation system for stroke patients based on eye movement control

Recently, the number of stroke patients has increased greatly. Most of them suffer from hand motor impairment, which creates the need for effective rehabilitation systems. Functional electrical stimulation (FES) is a neurorehabilitation method based on brain plasticity, which is widely accepted because it is non-invasive and convenient. However, it is still a challenge to achieve fine finger control by using surface FES. Here, we use multi-point surface FES to achieve individual finger motion. Besides, simple FES does not engage the subjects' attention, and an optimal stimulation position is difficult to identify. Hence, we try to integrate FES with sensory control by presenting a multi-point FES system based on eye movement control. By programming the electrodes display interface and establishing communication with the FES device and the eye tracker, subjects can change stimulation points via their eye movements. Experiments were performed to test the validity and safety of the proposed system. Feedback data was obtained using a 3D motion capture device. The results indicate that achieving individual finger motion is possible and stimulation points can be changed via eye movements. The system is practical and can be used in hand motor training for stroke patients to shorten the rehabilitation period.

Smart Skin: Vision-Based Soft Pressure Sensing System for In-Home Hand Rehabilitation.

We introduce a novel in-home hand rehabilitation system for monitoring hand motions and assessing grip forces of stroke patients. The overall system is composed of a sensing device and a computer vision system. The sensing device is a lightweight cylindrical object for easy grip and manipulation, which is covered by a passive sensing layer called “Smart Skin.” The Smart Skin is fabricated using soft silicone elastomer, which contains embedded microchannels partially filled with colored fluid. When the Smart Skin is compressed by grip forces, the colored fluid rises and fills in the top surface display area. Then, the computer vision system captures the image of the display area through a red–green–blue camera, detects the length change of the liquid through image processing, and eventually maps the liquid length to the calibrated force for estimating the gripping force. The passive sensing mechanism of the proposed Smart Skin device works in conjunction with a single camera setup, making the system simple and easy to use, while also requiring minimum maintenance effort. Our system, on one hand, aims to support home-based rehabilitation therapy with minimal or no supervision by recording the training process and the force data, which can be automatically conveyed to physical therapists. In contrast, the therapists can also remotely instruct the patients with their training prescriptions through online videos. This study first describes the design, fabrication, and calibration of the Smart Skin, and the algorithm for image processing, and then presents experimental results from the integrated system. The Smart Skin prototype shows a relatively linear relationship between the applied force and the length change of the liquid in the range of 0–35 N. The computer vision system shows the estimation error <4% and a relatively high stability in estimation under different hand motions.

A compact valveless pressure control source for soft rehabilitation glove.

Soft pneumatic robots have shown great promises in hand rehabilitation systems as alternatives to conventional rigid systems. However, their application is limited to clinical rehabilitation programs due to their dependency on large-sized compressors as air suppliers. This disadvantage triggered the search for compact portable pneumatic sources. A compact valveless pneumatic source to control the bending angle of a soft actuator is proposed in this paper. The source incorporates two series of serially connected commercially available microcompressors to provide additional pressure and flowrate in two directions. In the proposed design, an inner-loop controller, controls the output characteristics of the source while an outer-loop controller handles the trajectory tracking of the angular position. Experimental results show that the source is capable of providing up to 160kPa of output. The controller is able to track up to 2rad/sec sinusoidal trajectory with a maximum 0.066rad root-mean-square error. Experimental measurements showed satisfactory results in the maximum ratings and tracking errors whilst relatively low average power was consumed by eliminating control valves.

Attention Enhancement for Exoskeleton-Assisted Hand Rehabilitation Using Fingertip Haptic Stimulation.

Active enrollment in rehabilitation training yields better treatment outcomes. This paper introduces an exoskeleton-assisted hand rehabilitation system. It is the first attempt to combine fingertip cutaneous haptic stimulation with exoskeleton-assisted hand rehabilitation for training participation enhancement. For the first time, soft material 3D printing techniques are adopted to make soft pneumatic fingertip haptic feedback actuators to achieve cheaper and faster iterations of prototype designs with consistent quality. The fingertip haptic stimulation is synchronized with the motion of our hand exoskeleton. The contact force of the fingertips resulted from a virtual interaction with a glass of water was based on data collected from normal hand motions to grasp a glass of water. System characterization experiments were conducted and exoskeleton-assisted hand motion with and without the fingertip cutaneous haptic stimulation were compared in an experiment involving healthy human subjects. Users’ attention levels were monitored in the motion control process using a Brainlink EEG-recording device and software. The results of characterization experiments show that our created haptic actuators are lightweight (6.8 ± 0.23 g each with a PLA fixture and Velcro) and their performance is consistent and stable with small hysteresis. The user study experimental results show that participants had significantly higher attention levels with additional haptic stimulations compared to when only the exoskeleton was deployed; heavier stimulated grasping weight (a 300 g glass) was associated with significantly higher attention levels of the participants compared to when lighter stimulated grasping weight (a 150 g glass) was applied. We conclude that haptic stimulations increase the involvement level of human subjects during exoskeleton-assisted hand exercises. Potentially, the proposed exoskeleton-assisted hand rehabilitation with fingertip stimulation may better attract user’s attention during treatment.

A Hand Motor Skills Rehabilitation for the Injured Implemented on a Social Robot

In this work, we introduce HaReS, a hand rehabilitation system. Our proposal integrates a series of exercises, jointly developed with a foundation for those with motor and cognitive injuries, that are aimed at improving the skills of patients and the adherence to the rehabilitation plan. Our system takes advantage of a low-cost hand-tracking device to provide a quantitative analysis of the performance of the patient. It also integrates a low-cost surface electromyography (sEMG) sensor in order to provide insight about which muscles are being activated while completing the exercises. It is also modular and can be deployed on a social robot. We tested our proposal in two different facilities for rehabilitation with high success. The therapists and patients felt more motivation while using HaReS, which improved the adherence to the rehabilitation plan. In addition, the therapists were able to provide services to more patients than when they used their traditional methodology.

Plug-and-Train Robot (PLUTO) for Hand Rehabilitation: Design and Preliminary Evaluation

Hand neurorehabilitation involves training movements at the forearm, wrist, fingers, and thumb joints. Assisted training of all these joints requires either one complex multiple degree-of-freedom (DOF) robot or a set of simple robots with one or two DOF. Neither of these is economic or clinically viable. This paper addresses this problem with the PLUg and train rObot (PLUTO)- a single DOF robot that can train multiple joints one at a time. PLUTO has a single actuator with a set of passive attachments/mechanisms that can be easily attached/detached to train for wrist flexion-extension, wrist ulnar-radial deviation, forearm pronation-supination, and gross hand opening-closing. The robot can provide training in active and assisted regimes. PLUTO is linked to performance adaptive computer games to provide feedback to the patients and motivate them during training. As the first step towards clinical validation, the device usability was evaluated by 45 potential stakeholders/end-users of the device, including 15 patients, 15 caregivers, and 15 clinicians with standardized questionnaires: System Usability Scale (SUS) and User Experience Questionnaire (UEQ). Patients and caregivers were administered the questionnaire after a two-session training with the robot. Clinicians, on the other hand, had a single session demo, after which feedback was obtained. The total SUS score obtained from patients, clinicians, and caregivers was 73.3 ± 14.6 (n = 45), indicating good usability. The UEQ score was rated positively in all subscales by both patients and clinicians, indicating that the features of PLUTO match their expectations. The positive response from the preliminary testing and the feedback from the stakeholders indicate that with additional passive mechanisms, assessment features, and optimized ergonomics, PLUTO will be a versatile, affordable, and useful system for hand rehabilitation.

RobHand: A Hand Exoskeleton With Real-Time EMG-Driven Embedded Control. Quantifying Hand Gesture Recognition Delays for Bilateral Rehabilitation

Assisted bilateral rehabilitation has been proven to help patients improve their paretic limb ability and promote motor recovery, especially in upper limbs, after suffering a cerebrovascular accident (ACV). Robotic-assisted bilateral rehabilitation based on sEMG-driven control has been previously addressed in other studies to improve hand mobility; however, low-cost embedded solutions for the real-time bio-cooperative control of robotic rehabilitation platforms are lacking. This paper presents the RobHand (Robot for Hand Rehabilitation) system, which is an exoskeleton that supports EMG-driven assisted bilateral by using a custom-made low-cost EMG real-time embedded solution. A threshold non-pattern recognition EMG-driven control for RobHand has been developed, and it detects hand gestures of the healthy hand and replicates the gesture on the exoskeleton placed on the paretic hand. A preliminary study with ten healthy subjects is conducted to evaluate the performance in reliability, tracking accuracy and response time of the proposed EMG-driven control strategy using the EMG real-time embedded solution, and the findings could be extrapolated to stroke patients. A systematic review has been carried out to compare the results of the study, which present a 97% of overall accuracy for the detection of hand gestures and indicate the adequate time responsiveness of the system.

A new hand rehabilitation system based on the cable-driven mechanism and dielectric elastomer actuator

Abstract. The increasing number of patients with hand disabilities after strokes or peripheral nerve injuries necessitates the continuous development of rehabilitation system devices to accelerate muscle recovery and to help patients regain the motor functions of their hands. This paper introduces the design of a hand rehabilitation system for patients who have a solitary impairment of their hand extension. The system was designed to be portable, simple, and cheap. Using a system based on a cable-driven mechanism instead of traditional rigid links reduces the degrees of freedom of the finger to one. The dielectric elastomer actuator was designed and fabricated as a smart actuator for the system, which supports the low cost of the system. A kinematic analysis of the cable-driven mechanism has been done. Parameters of the actuator were optimized to reach the required output. In order to characterize the performance of the actuator, a uniaxial tension test, isotonic test, and isometric test have been implemented.