Adaptive control for shape memory alloy actuated systems with applications to human-robot interaction.

Introduction: Shape memory alloy (SMA) actuators are attractive options for robotic applications due to their salient features. So far, achieving precise control of SMA actuators and applying them to human-robot interaction scenarios remains a challenge. Methods: This paper proposes a novel approach to deal with the control problem of a SMA actuator. Departing from conventional mechanism models, we attempt to describe this nonlinear plant using a gray-box model, in which only the input current and the output displacement are measured. The control scheme consists of the model parameters updating and the control law calculation. The adaptation algorithm is founded on the multi-innovation concept and incorporates a dead-zone weighted factor, aiming to concurrently reduce computational complexities and enhance robustness properties. The control law is based on a PI controller, the gains of which are designed by the pole assignment technique. Theoretical analysis proves that the closed-loop performance can be ensured under mild conditions. Results: The experiments are first conducted through the Beckhoff controller. The comparative results suggest that the proposed adaptive PI control strategy exhibits broad applicability, particularly under load variations. Subsequently, the SMA actuator is designed and incorporated into the hand rehabilitation robot. System position tracking experiments and passive rehabilitation training experiments for various gestures are then conducted. The experimental outcomes demonstrate that the hand rehabilitation robot, utilizing the SMA actuator, achieves higher position tracking accuracy and a more stable system under the adaptive control strategy proposed in this paper. Simultaneously, it successfully accommodates hand rehabilitation movements for multiple gestures. Discussion: The adaptive controller proposed in this paper takes into account both the computational complexity of the model and the accuracy of the control results, Experimental results not only demonstrate the practicality and reliability of the controller but also attest to its potential application in human-machine interaction within the field of neural rehabilitation.

Design and analysis of a compatible exoskeleton rehabilitation robot system based on upper limb movement mechanism.

Rehabilitation robots are used to promote structural and functional recovery of the nervous system with repetitive, task-oriented training and have been gradually applied to clinical rehabilitation training. This paper proposes an upper limb exoskeleton rehabilitation robot system that could realize shoulder-elbow-wrist joint rehabilitation training. Firstly, a motion equivalent model was established based on the upper limb movement mechanism, the robot mechanism configuration was designed, and the optimization algorithm and spatial mechanism theory were used to optimize and analyze the structural parameters and human-machine compatibility of the robot, which will guide the design of the robot's model. Then, the robot kinematics were solved, and its maximum motion range, dexterity distribution, and daily motion trajectory were simulated. Finally, a system prototype was built to test the maximum range of robot-assisted human upper limb training by laser tracker, while the pressure of human-machine interaction during training was captured and analyzed by flexible sensors. The results show that the proposed rehabilitation robot could nearly completely cover the range of motion of upper limb joints and meet the needs of trajectory training, and the linear velocity dexterity and angular velocity dexterity in the motion space are maximum 0.55 and 0.89, and the human-machine interaction pressures during the training process are all less than 10 kPa. Besides, this paper also conducted a system evaluation based on the fuzzy comprehensive evaluation model, and the evaluation result was 0.39, with an excellent evaluation grade, it indirectly indicates that the robot's overall performance was good.

Effects of an exoskeleton rehabilitation robot on the lower limb motor function of children with spastic cerebral palsy / 中华物理医学与康复杂志

Objective:To observe any effect of using the KidGo exoskeleton rehabilitation robot on the lower limb motor function of children with spastic cerebral palsy.Methods:Thirty children with spastic cerebral palsy were sorted at random into a control group and a robotics group, each of 15. Both groups received conventional rehabilitation 5 days a week for 12 weeks, but the robotics group also spent 30 minutes daily training with the KidGo exoskeleton robot. Before and after the intervention, the lower limb muscle tone and strength, gross motor function, balance, and functional independence of both groups were assessed using surface electromyography, a handheld muscle strength tester, the gross motor function measure, the Berg Balance Scale, and the Wee-functional independence measure.Results:After the intervention great improvements in average lower limb muscle tone and strength, gross motor function, balance, and functional independence were observed in both groups, but the improvements in the robotics group were significantly greater, on average.Conclusion:Supplementing conventional rehabilitation with training using the KidGo exoskeleton rehabilitation robot can better improve muscle tone, strength, gross motor functioning, balance, and the functional independence of children with spastic cerebral palsy.

Research of intent recognition in rehabilitation robots: a systematic review.

PURPOSE: Rehabilitation robots with intent recognition are helping people with dysfunction to enjoy better lives. Many rehabilitation robots with intent recognition have been developed by academic institutions and commercial companies. However, there is no systematic summary about the application of intent recognition in the field of rehabilitation robots. Therefore, the purpose of this paper is to summarize the application of intent recognition in rehabilitation robots, analyze the current status of their research, and provide cutting-edge research directions for colleagues. MATERIALS AND METHODS: Literature searches were conducted on Web of Science, IEEE Xplore, ScienceDirect, SpringerLink, and Medline. Search terms included "rehabilitation robot", "intent recognition", "exoskeleton", "prosthesis", "surface electromyography (sEMG)" and "electroencephalogram (EEG)". References listed in relevant literature were further screened according to inclusion and exclusion criteria. RESULTS: In this field, most studies have recognized movement intent by kinematic, sEMG, and EEG signals. However, in practical studies, the development of intent recognition in rehabilitation robots is limited by the hysteresis of kinematic signals and the weak anti-interference ability of sEMG and EEG signals. CONCLUSIONS: Intent recognition has achieved a lot in the field of rehabilitation robotics but the key factors limiting its development are still timeliness and accuracy.In the future, intent recognition strategy with multi-sensor information fusion may be a good solution.

As a technology, intent recognition can become a part of rehabilitation, assist patients to complete daily life activities, and improve their quality of life.Rehabilitation training equipment for treatment usually adopts a relatively stable prediction method, which aims to stimulate the enthusiasm of users to participate in training.Functionally enhanced rehabilitation aids have high requirements for the timeliness of movement intent recognition, and its purpose is to assist patients to complete activities of daily life.

Nonholonomic Virtual Constraints for Control of Powered Prostheses Across Walking Speeds.

This paper presents a method to design a nonholonomic virtual constraint (NHVC) controller that produces multiple distinct stance-phase trajectories for corresponding walking speeds. NHVCs encode velocity-dependent joint trajectories via momenta conjugate to the unactuated degree(s)-of-freedom of the system. We recently introduced a method for designing NHVCs that allow for stable bipedal robotic walking across variable terrain slopes. This work extends the notion of NHVCs for application to variable-cadence powered prostheses. Using the segmental conjugate momentum for the prosthesis, an optimization problem is used to design a single stance-phase NHVC for three distinct walking speed trajectories (slow, normal, and fast). This stance-phase controller is implemented with a holonomic swing phase controller on a powered knee-ankle prosthesis, and experiments are conducted with an able-bodied user walking in steady and non-steady velocity conditions. The control scheme is capable of representing 1) multiple, task-dependent reference trajectories, and 2) walking gait variance due to both temporal and kinematic changes in user motion.

Real time control and fabrication of a soft robotic glove by two parallel sensors with MBD approach.

Soft robotic gloves were designed to aid the rehabilitation process with hand pathologies and coordination of gripping exercises. The main issue in soft robotic actuators is to design a control strategy to overcome deformation in grasping exercises. In this paper, a new soft robotic actuator is developed to be protected against swell and deformation. This soft robotic glove is equipped with two sensors; these sensors make the robotic glove more intelligent. In the hardware, it was used two sensors in the new closed-loop method which include an air pressure sensor in the figure tip and a flex sensor to measure finger flexion rate. Two closed-loop control system is developed to regulate inlet air pressure and regulate the angle of the fingers for the soft robotic actuator. A Model-Based Design (MBD) method is presented as a very cost-effective, favorable, and robust method. PID programming on an embedded controller is applied by MBD approach. The soft actuator process contains a molded wooden chamber and fiber reinforcement. Experimental results show that the proposed soft robotic has a soft gripping mechanism, accurate gripping against various objects during daily activities.

Mobile Robot-Based Gait Training after Total Hip Arthroplasty (THA) Improves Walking in Biomechanical Gait Analysis.

There are multiple attempts to decrease costs in the healthcare system while maintaining a high treatment quality. Digital therapies receive increasing attention in clinical practice, mainly relating to home-based exercises supported by mobile devices, eventually in combination with wearable sensors. The aim of this study was to determine if patients following total hip arthroplasty (THA) could benefit from gait training on crutches conducted by a mobile robot in a clinical setting. METHOD: This clinical trial was conducted with 30 patients following total hip arthroplasty. Fifteen patients received the conventional physiotherapy program in the clinic (including 5 min of gait training supported by a physiotherapist). The intervention group of 15 patients passed the same standard physiotherapy program, but the 5-min gait training supported by a physiotherapist was replaced by 2 × 5 min of gait training conducted by the robot. Length of stay of the patients was set to five days. Biomechanical gait parameters of the patients were assessed pre-surgery and upon patient discharge. RESULTS: While before surgery no significant difference in gait parameters was existent, patients from the intervention group showed a significant higher absolute walking speed (0.83 vs. 0.65 m/s, p = 0.029), higher relative walking speed (0.2 vs. 0.16 m/s, p = 0.043) or shorter relative cycle time (3.35 vs. 3.68 s, p = 0.041) than the patients from the control group. CONCLUSION: The significant higher walking speed of patients indicates that such robot-based gait training on crutches may shorten length of stay (LOS) in acute clinics. However, the number of patients involved was rather small, thus calling for further studies.

Safety Assessment of Rehabilitation Robots: A Review Identifying Safety Skills and Current Knowledge Gaps.

The assessment of rehabilitation robot safety is a vital aspect of the development process, which is often experienced as difficult. There are gaps in best practices and knowledge to ensure safe usage of rehabilitation robots. Currently, safety is commonly assessed by monitoring adverse events occurrence. The aim of this article is to explore how safety of rehabilitation robots can be assessed early in the development phase, before they are used with patients. We are suggesting a uniform approach for safety validation of robots closely interacting with humans, based on safety skills and validation protocols. Safety skills are an abstract representation of the ability of a robot to reduce a specific risk or deal with a specific hazard. They can be implemented in various ways, depending on the application requirements, which enables the use of a single safety skill across a wide range of applications and domains. Safety validation protocols have been developed that correspond to these skills and consider domain-specific conditions. This gives robot users and developers concise testing procedures to prove the mechanical safety of their robotic system, even when the applications are in domains with a lack of standards and best practices such as the healthcare domain. Based on knowledge about adverse events occurring in rehabilitation robot use, we identified multi-directional excessive forces on the soft tissue level and musculoskeletal level as most relevant hazards for rehabilitation robots and related them to four safety skills, providing a concrete starting point for safety assessment of rehabilitation robots. We further identified a number of gaps which need to be addressed in the future to pave the way for more comprehensive guidelines for rehabilitation robot safety assessments. Predominantly, besides new developments of safety by design features, there is a strong need for reliable measurement methods as well as acceptable limit values for human-robot interaction forces both on skin and joint level.

Multidirectional Overground Robotic Training Leads to Improvements in Balance in Older Adults.

For the rapidly growing aging demographic worldwide, robotic training methods could be impactful towards improving balance critical for everyday life. Here, we investigated the hypothesis that non-bodyweight supportive (nBWS) overground robotic balance training would lead to improvements in balance performance and balance confidence in older adults. Sixteen healthy older participants (69.7 ± 6.7 years old) were trained while donning a harness from a distinctive NaviGAITor robotic system. A control group of 11 healthy participants (68.7 ± 5.0 years old) underwent the same training but without the robotic system. Training included 6 weeks of standing and walking tasks while modifying: (1) sensory information (i.e., with and without vision (eyes-open/closed), with more and fewer support surface cues (hard or foam surfaces)) and (2) base-of-support (wide, tandem and single-leg standing exercises). Prior to and post-training, balance ability and balance confidence were assessed via the balance error scoring system (BESS) and the Activities specific Balance Confidence (ABC) scale, respectively. Encouragingly, results showed that balance ability improved (i.e., BESS errors significantly decreased), particularly in the nBWS group, across nearly all test conditions. This result serves as an indication that robotic training has an impact on improving balance for healthy aging individuals.

Passive Exercise Adaptation for Ankle Rehabilitation Based on Learning Control Framework.

Ankle injuries are among the most common injuries in sport and daily life. However, for their recovery, it is important for patients to perform rehabilitation exercises. These exercises are usually done with a therapist's guidance to help strengthen the patient's ankle joint and restore its range of motion. However, in order to share the load with therapists so that they can offer assistance to more patients, and to provide an efficient and safe way for patients to perform ankle rehabilitation exercises, we propose a framework that integrates learning techniques with a 3-PRS parallel robot, acting together as an ankle rehabilitation device. In this paper, we propose to use passive rehabilitation exercises for dorsiflexion/plantar flexion and inversion/eversion ankle movements. The therapist is needed in the first stage to design the exercise with the patient by teaching the robot intuitively through learning from demonstration. We then propose a learning control scheme based on dynamic movement primitives and iterative learning control, which takes the designed exercise trajectory as a demonstration (an input) together with the recorded forces in order to reproduce the exercise with the patient for a number of repetitions defined by the therapist. During the execution, our approach monitors the sensed forces and adapts the trajectory by adding the necessary offsets to the original trajectory to reduce its range without modifying the original trajectory and subsequently reducing the measured forces. After a predefined number of repetitions, the algorithm restores the range gradually, until the patient is able to perform the originally designed exercise. We validate the proposed framework with both real experiments and simulation using a Simulink model of the rehabilitation parallel robot that has been developed in our lab.

[Bibliometric analysis on international cooperation of rehabilitation robots in China from 2000 to 2019].

Rapid development is undergoing in the field of rehabilitation robots, and more countries (regions) are participating in international cooperation and becoming academic contributors. Here in this study, the bibliometric method is used to determine the dynamics and developments of international cooperation in China. The publication data are indexed in Web of Science with search term of rehabilitation robot from 2000 to 2019. Compared with other countries (regions), publication with international co-authors and institutes participating in international cooperation are studied by assessment of indicators such as the cooperation degree, cooperation frequency, and the frequency of citations. The results show that in the past two decades, international scientific cooperation has shown a positive tendency in China, and participating in international collaboration could improve China's impact on the global rehabilitation robot. The United States, England and Japan are the top three countries in number of cooperation with China. Our findings provide valuable information for researchers to better understand China's international scientific collaboration in rehabilitation robot.

Inertial-Robotic Motion Tracking in End-Effector-Based Rehabilitation Robots.

End-effector-based robotic systems provide easy-to-set-up motion support in rehabilitation of stroke and spinal-cord-injured patients. However, measurement information is obtained only about the motion of the limb segments to which the systems are attached and not about the adjacent limb segments. We demonstrate in one particular experimental setup that this limitation can be overcome by augmenting an end-effector-based robot with a wearable inertial sensor. Most existing inertial motion tracking approaches rely on a homogeneous magnetic field and thus fail in indoor environments and near ferromagnetic materials and electronic devices. In contrast, we propose a magnetometer-free sensor fusion method. It uses a quaternion-based algorithm to track the heading of a limb segment in real time by combining the gyroscope and accelerometer readings with position measurements of one point along that segment. We apply this method to an upper-limb rehabilitation robotics use case in which the orientation and position of the forearm and elbow are known, and the orientation and position of the upper arm and shoulder are estimated by the proposed method using an inertial sensor worn on the upper arm. Experimental data from five healthy subjects who performed 282 proper executions of a typical rehabilitation motion and 163 executions with compensation motion are evaluated. Using a camera-based system as a ground truth, we demonstrate that the shoulder position and the elbow angle are tracked with median errors around 4 cm and 4°, respectively; and that undesirable compensatory shoulder movements, which were defined as shoulder displacements greater ±10 cm for more than 20% of a motion cycle, are detected and classified 100% correctly across all 445 performed motions. The results indicate that wearable inertial sensors and end-effector-based robots can be combined to provide means for effective rehabilitation therapy with likewise detailed and accurate motion tracking for performance assessment, real-time biofeedback and feedback control of robotic and neuroprosthetic motion support.

Bibliometric analysis on international cooperation of rehabilitation robots in China from 2000 to 2019 / 生物医学工程学杂志

Rapid development is undergoing in the field of rehabilitation robots, and more countries (regions) are participating in international cooperation and becoming academic contributors. Here in this study, the bibliometric method is used to determine the dynamics and developments of international cooperation in China. The publication data are indexed in Web of Science with search term of rehabilitation robot from 2000 to 2019. Compared with other countries (regions), publication with international co-authors and institutes participating in international cooperation are studied by assessment of indicators such as the cooperation degree, cooperation frequency, and the frequency of citations. The results show that in the past two decades, international scientific cooperation has shown a positive tendency in China, and participating in international collaboration could improve China's impact on the global rehabilitation robot. The United States, England and Japan are the top three countries in number of cooperation with China. Our findings provide valuable information for researchers to better understand China's international scientific collaboration in rehabilitation robot.

Design of an isokinetic knee dynamometer for evaluation of functional electrical stimulation strategies.

BACKGROUND: The limitations of functional electrical stimulation (FES) cycling directly affect the health benefits acquired from this technology and prevents its' full potential to be realised. Experiments should be done on a test bed which can isolate and focus only on one muscle group, namely the quadriceps. The aim of this work was to design and develop an isokinetic robotic leg extension/flexion dynamometer which can mimic knee joint motion during actual cycling to be used for evaluation of novel functional electrical stimulation strategies. Although the main motivation for development of the dynamometer was for application in FES studies, it has the potential to be used for various different muscle physiology studies. METHODS: A feedback control system with integrated electrical stimulation for isokinetic knee joint torque measurement has been developed and tested for safety and functionality. The leg extension/flexion device was modified and equipped with a DC motor drive system to imitate isokinetic knee joint motion during cycling when the hip joint remains fixed. Real-time bi-directional effective torque on the lever arm was measured by a magnetostrictive torque sensor and a load cell. Closed-loop motor control system was also designed to mimic the cyclical motion at desired angular velocity. RESULTS: A functional model of the robotic dynamometer was developed and evaluated. The dynamometer is capable of simulating the knee angle during cycling at a cadence of up to 70 rpm with range of motion of 72∘. The magnetostrictive torque sensor can measure torque values up to 75 Nm. The lever arm can be adjusted and the target knee angle was controlled with RMSE tracking error of less than 2.1∘ in tests with and without a test person, and with and without muscle stimulation. CONCLUSIONS: The isokinetic knee joint torque measurement system was designed and validated in this work, and subsequently used to develop and evaluate novel muscle activation strategies. This is important for fundamental research on effective stimulation patterns and novel activation strategies. This will, in turn, enhance the efficiency of FES cycling exercise and has the potential to improve the health-beneficial effects.

Program Design of Motor Imagery with Regular Rhythm / 中国康复理论与实践

Objective:To propose a motor imagery paradigm with regular rhythm to improve the accuracy of classification in brain-computer interface based on motor imagery. Methods:Ten untrained healthy subjects were asked to image the movement guided by the picture accompanied with regular rhythm. The common spatial pattern feature extraction algorithm and Fisher classifier were used for classification, and compared with the traditional paradigm and the motor imagery paradigm accompanying with irregular rhythm. Results:More desynchronization was found as motor imagery with regular rhythm, while the classification accuracy improved. Conclusion:Motor imagery with regular rhythm gives a new idea for active rehabilitation training based on brain-computer interface.

Program Design of Motor Imagery with Regular Rhythm / 中国康复理论与实践

Objective:To propose a motor imagery paradigm with regular rhythm to improve the accuracy of classification in brain-computer interface based on motor imagery. Methods:Ten untrained healthy subjects were asked to image the movement guided by the picture accompanied with regular rhythm. The common spatial pattern feature extraction algorithm and Fisher classifier were used for classification, and compared with the traditional paradigm and the motor imagery paradigm accompanying with irregular rhythm. Results:More desynchronization was found as motor imagery with regular rhythm, while the classification accuracy improved. Conclusion:Motor imagery with regular rhythm gives a new idea for active rehabilitation training based on brain-computer interface.

Robot-assisted training can improve the bladder and intestinal functions of paraplegic patients / 中华物理医学与康复杂志

Objective To explore the clinical effect of training assisted by a lower limb rehabilitation robot on the bladder and intestinal function of paraplegic spinal cord injury survivors. Methods Thirty-eight paraplegic patients with spinal cord injury were divided according to their admission order into an experimental group ( n=19) and a control group (n=19). Both groups were given conventional rehabilitation training, while the experimental group was additionally provided with robot-assisted lower limb training in three stages:adaptation, training and con-solidation. It lasted 30 minutes daily, 5 days per week for 12 weeks. Before and after the training, an urodynamics examination system was used to evaluate the maximum urine flow, bladder capacity, residual urine volume, bladder pressure and detrusor pressure. Colon transit time, mean rectal pressure and intestinal function were measured using the colon transit test, a mean rectal pressure test, and the Functional Independence Measure ( FIM) scale respective-ly. Results The average bladder volume, maximum urine flow rate, average urine flow rate, detrusor pressure, bladder compliance, average rectal pressure and intestinal FIM score of the robot training group after training were all significantly better than before the training, as were the average residual urine volume and colon transit time. After the training, the average bladder volume, maximum urine flow rate, average urine flow rate, detrusor pressure, bladder compliance and average rectal pressure of the robot training group were all significantly higher than those of the control group, while the average residual urine volume and colon transit time were significantly smaller. Then, 32％ of the patients in the experimental group achieved no less than 6 points for their average FIM score, significantly higher than in the control group. Conclusion Robot-assisted lower limb training combined with comprehensive rehabilitation training can effectively improve the bladder and intestinal function of paraplegic patients after a spinal cord injury.

Stroke Rehabilitation: Therapy Robots and Assistive Devices.

Motor impairments after stroke are often persistent and disabling, and women are less likely to recover and show poorer functional outcomes. To regain motor function after stroke, rehabilitation robots are increasingly integrated into clinics. The devices fall into two main classes: robots developed to train lost motor function after stroke (therapy devices) and robots designed to compensate for lost skills (i.e., assistive devices). The article provides an overview of therapeutic options with robots for motor rehabilitation after stroke.

The effect of a novel gait retraining device on lower limb kinematics and muscle activation in healthy adults.

The Re-Link Trainer (RLT) is a modified walking frame with a linkage system designed to apply a non-individualized kinematic constraint to normalize gait trajectory of the left limb. The premise behind the RLT is that a user's lower limb is constrained into a physiologically normal gait pattern, ideally generating symmetry across gait cycle parameters and kinematics. This pilot study investigated adaptations in the natural gait pattern of healthy adults when using the RLT compared to normal overground walking. Bilateral lower limb kinematic and electromyography data were collected while participants walked overground at a self-selected speed, followed by walking in the RLT. A series of 2-way analyses of variance examined between-limb and between-condition differences. Peak hip extension and knee flexion were reduced bilaterally when walking in the RLT. Left peak hip extension occurred earlier in the gait cycle when using the RLT, but later for the right limb. Peak hip flexion was significantly increased and occurred earlier for the constrained limb, while peak plantarflexion was significantly reduced. Peak knee flexion and plantarflexion in the right limb occurred later when using the RLT. Significant bilateral reductions in peak electromyography amplitude were evident when walking in the RLT, along with a significant shift in when peak muscle activity was occurring. These findings suggest that the RLT does impose a significant constraint, but generates asymmetries in lower limb kinematics and muscle activity patterns. The large interindividual variation suggests users may utilize differing motor strategies to adapt their gait pattern to the imposed constraint.

[Human-robot global Simulink modeling and analysis for an end-effector upper limb rehabilitation robot].

Robot rehabilitation has been a primary therapy method for the urgent rehabilitation demands of paralyzed patients after a stroke. The parameters in rehabilitation training such as the range of the training, which should be adjustable according to each participant's functional ability, are the key factors influencing the effectiveness of rehabilitation therapy. Therapists design rehabilitation projects based on the semiquantitative functional assessment scales and their experience. But these therapies based on therapists' experience cannot be implemented in robot rehabilitation therapy. This paper modeled the global human-robot by Simulink in order to analyze the relationship between the parameters in robot rehabilitation therapy and the patients' movement functional abilities. We compared the shoulder and elbow angles calculated by simulation with the angles recorded by motion capture system while the healthy subjects completed the simulated action. Results showed there was a remarkable correlation between the simulation data and the experiment data, which verified the validity of the human-robot global Simulink model. Besides, the relationship between the circle radius in the drawing tasks in robot rehabilitation training and the active movement degrees of shoulder as well as elbow was also matched by a linear, which also had a remarkable fitting coefficient. The matched linear can be a quantitative reference for the robot rehabilitation training parameters.