Enhanced compensation control of pneumatic muscle actuator with high-order modified dynamic model.

Dynamic behaviour of the pneumatic muscle actuator (PMA) is conventionally modelled as a pressure-based first-order equation under discrete loads, which cannot exactly describe its dynamic features. Considering PMA's nonlinear, time-varying and hysteresis characteristics, we propose a novel high-order modified dynamic model of PMA based on its physical properties and working principle, with coefficients being identified under external dynamic loads. To tackle PMA's nonlinear hysteresis problem in high-frequency movements, a global fast terminal sliding mode controller with the modified model-based radial basis function (RBF) neural network disturbance compensator (RBF-GFTSMC) is designed. Comparison experimental studies are carried on a designed PMA platform that can provide continuously changing loads. Results show that the RBF-GFTSMC has superior trajectory tracking performance and disturbance compensation capability under wide-ranged frequencies and external loads, which can be potentially used to achieve precise control of PMA-actuated robots.

Bearing-Only Formation Control With Prespecified Convergence Time.

This article considers the bearing-only formation control problem, where the control of each agent only relies on relative bearings of their neighbors. A new control law is proposed to achieve target formations in finite time. Different from the existing results, the control law is based on a time-varying scaling gain. Hence, the convergence time can be arbitrarily chosen by users, and the derivative of the control input is continuous. Furthermore, sufficient conditions are given to guarantee almost global convergence and interagent collision avoidance. Then, a leader-follower control structure is proposed to achieve global convergence. By exploring the properties of the bearing Laplacian matrix, the collision avoidance and smooth control input are preserved. A multirobot hardware platform is designed to validate the theoretical results. Both simulation and experimental results demonstrate the effectiveness of our design.

Path Planning and Impedance Control of a Soft Modular Exoskeleton for Coordinated Upper Limb Rehabilitation.

The coordinated rehabilitation of the upper limb is important for the recovery of the daily living abilities of stroke patients. However, the guidance of the joint coordination model is generally lacking in the current robot-assisted rehabilitation. Modular robots with soft joints can assist patients to perform coordinated training with safety and compliance. In this study, a novel coordinated path planning and impedance control method is proposed for the modular exoskeleton elbow-wrist rehabilitation robot driven by pneumatic artificial muscles (PAMs). A convolutional neural network-long short-term memory (CNN-LSTM) model is established to describe the coordination relationship of the upper limb joints, so as to generate adaptive trajectories conformed to the coordination laws. Guided by the planned trajectory, an impedance adjustment strategy is proposed to realize active training within a virtual coordinated tunnel to achieve the robot-assisted upper limb coordinated training. The experimental results showed that the CNN-LSTM hybrid neural network can effectively quantify the coordinated relationship between the upper limb joints, and the impedance control method ensures that the robotic assistance path is always in the virtual coordination tunnel, which can improve the movement coordination of the patient and enhance the rehabilitation effectiveness.

Automated robot-assisted assessment for wrist active ranges of motion.

The measurement of wrist active range of motion (ROM) is essential for determining the progress of hand functional recovery, which can provide insight into quantitative improvements and enable effective monitoring during hand rehabilitation. Compared with manual methods, which depend on the experience of the therapist, the proposed robot-assisted assessment technique can measure active ROM of human wrists. The robot with a reconfigurable handle design allows for multiple wrist motions. Experiments were conducted with 11 human subjects to measure ROMs of human wrist flexion/extension and radial/ulnar deviation. Reliability analysis was conducted by calculating the intra-class correlation coefficients (ICC), standard error of measurement (SEM) and SEM%. Results showed high reliability (ICC2,1 ≥ 0.89, SEM ≤ 2.36°, SEM% ≤ 6.81%). Future will focus on adaptive joint self-alignment design between human users and robots to further improve its assessment accuracy.

Interactive Compliance Control of a Wrist Rehabilitation Device (WReD) with Enhanced Training Safety.

Interaction control plays an important role in rehabilitation devices to ensure training safety and efficacy. Compliance adaptation of interaction is vital for enabling robot movements to better suit the patient's requirements as human joint characteristics vary. This paper proposes an interactive compliance control scheme on a wrist rehabilitation device (WReD) for enhanced training safety and efficacy. This control system consists of a low-level trajectory tracking loop and a high-level admittance loop. Experiments were conducted with zero load and human interaction, respectively. Satisfactory trajectory tracking responses were obtained, with the normalized root mean square deviation (NRMSD) values being 1.08% with zero load and the NRMSD values no greater than 1.4% with real-time disturbance and interaction from human users. Results demonstrate that such an interactive compliance control method can adaptively adjust the range of training motions and encourage active engagement from human users simultaneously. These findings suggest that the proposed control method of the WReD has great potentials for clinical applications due to enhanced training safety and efficacy. Future work will focus on evaluating its efficacy on a large sample of participants.

Reviewing Clinical Effectiveness of Active Training Strategies of Platform-Based Ankle Rehabilitation Robots.

Objective: This review aims to provide a systematical investigation of clinical effectiveness of active training strategies applied in platform-based ankle robots. Method: English-language studies published from Jan 1980 to Aug 2017 were searched from four databases using key words of "Ankle∗" AND "Robot∗" AND "Effect∗ OR Improv∗ OR Increas∗." Following an initial screening, three rounds of discrimination were successively conducted based on the title, the abstract, and the full paper. Result: A total of 21 studies were selected with 311 patients involved; of them, 13 studies applied a single group while another eight studies used different groups for comparison to verify the therapeutic effect. Virtual-reality (VR) game training was applied in 19 studies, while two studies used proprioceptive neuromuscular facilitation (PNF) training. Conclusion: Active training techniques delivered by platform ankle rehabilitation robots have been demonstrated with great potential for clinical applications. Training strategies are mostly combined with one another by considering rehabilitation schemes and motion ability of ankle joints. VR game environment has been commonly used with active ankle training. Bioelectrical signals integrated with VR game training can implement intelligent identification of movement intention and assessment. These further provide the foundation for advanced interactive training strategies that can lead to enhanced training safety and confidence for patients and better treatment efficacy.

Automated objective robot-assisted assessment of wrist passive ranges of motion.

The measurement of wrist passive ranges of motion (ROMs) can provide insight into improvements and allow for effective monitoring during a rehabilitation program. Compared with conventional methods, this study proposed a new robotic assessment technique for measuring passive ROMs of the wrist. The robotic system has a reconfigurable handle structure that allows for multi-dimensional applications of wrist motions. The assessment reliability of this robotic system was analysed on 11 subjects for measuring wrist extension/flexion and radial/ulnar deviation. Preliminary data demonstrated its potential with intraclass correlation coefficient (ICC2,1) all greater than 0.857 and standard error of measurement (SEM) less than 3.38°. Future work will focus on the standardization of the assessment protocol of this robotic system for assessment purposes, paving the way for its clinical application.

Tele-rehabilitation using in-house wearable ankle rehabilitation robot.

This article explores wide-ranging potential of the wearable ankle robot for in-house rehabilitation. The presented robot has been conceptualized following a brief analysis of the existing technologies, systems, and solutions for in-house physical ankle rehabilitation. Configuration design analysis and component selection for ankle robot have been discussed as part of the conceptual design. The complexities of human robot interaction are closely encountered while maneuvering a rehabilitation robot. We present a fuzzy logic-based controller to perform the required robot-assisted ankle rehabilitation treatment. Designs of visual haptic interfaces have also been discussed, which will make the treatment interesting, and the subject will be motivated to exert more and regain lost functions rapidly. The complex nature of web-based communication between user and remotely sitting physiotherapy staff has also been discussed. A high-level software architecture appended with robot ensures user-friendly operations. This software is made up of three important components: patient-related database, graphical user interface (GUI), and a library of exercises creating virtual reality-specifically developed for ankle rehabilitation.

Disturbance-Estimated Adaptive Backstepping Sliding Mode Control of a Pneumatic Muscles-Driven Ankle Rehabilitation Robot.

A rehabilitation robot plays an important role in relieving the therapists' burden and helping patients with ankle injuries to perform more accurate and effective rehabilitation training. However, a majority of current ankle rehabilitation robots are rigid and have drawbacks in terms of complex structure, poor flexibility and lack of safety. Taking advantages of pneumatic muscles' good flexibility and light weight, we developed a novel two degrees of freedom (2-DOF) parallel compliant ankle rehabilitation robot actuated by pneumatic muscles (PMs). To solve the PM's nonlinear characteristics during operation and to tackle the human-robot uncertainties in rehabilitation, an adaptive backstepping sliding mode control (ABS-SMC) method is proposed in this paper. The human-robot external disturbance can be estimated by an observer, who is then used to adjust the robot output to accommodate external changes. The system stability is guaranteed by the Lyapunov stability theorem. Experimental results on the compliant ankle rehabilitation robot show that the proposed ABS-SMC is able to estimate the external disturbance online and adjust the control output in real time during operation, resulting in a higher trajectory tracking accuracy and better response performance especially in dynamic conditions.

Hierarchical Compliance Control of a Soft Ankle Rehabilitation Robot Actuated by Pneumatic Muscles.

Traditional compliance control of a rehabilitation robot is implemented in task space by using impedance or admittance control algorithms. The soft robot actuated by pneumatic muscle actuators (PMAs) is becoming prominent for patients as it enables the compliance being adjusted in each active link, which, however, has not been reported in the literature. This paper proposes a new compliance control method of a soft ankle rehabilitation robot that is driven by four PMAs configured in parallel to enable three degrees of freedom movement of the ankle joint. A new hierarchical compliance control structure, including a low-level compliance adjustment controller in joint space and a high-level admittance controller in task space, is designed. An adaptive compliance control paradigm is further developed by taking into account patient's active contribution and movement ability during a previous period of time, in order to provide robot assistance only when it is necessarily required. Experiments on healthy and impaired human subjects were conducted to verify the adaptive hierarchical compliance control scheme. The results show that the robot hierarchical compliance can be online adjusted according to the participant's assessment. The robot reduces its assistance output when participants contribute more and vice versa, thus providing a potentially feasible solution to the patient-in-loop cooperative training strategy.

Design and Interaction Control of a New Bilateral Upper-Limb Rehabilitation Device.

This paper proposed a bilateral upper-limb rehabilitation device (BULReD) with two degrees of freedom (DOFs). The BULReD is portable for both hospital and home environment, easy to use for therapists and patients, and safer with respect to upper-limb robotic exoskeletons. It was implemented to be able to conduct both passive and interactive training, based on system kinematics and dynamics, as well as the identification of real-time movement intention of human users. Preliminary results demonstrate the potential of the BULReD for clinical applications, with satisfactory position and interaction force tracking performance. Future work will focus on the clinical evaluation of the BULReD on a large sample of poststroke patients.

A Robot-Driven Computational Model for Estimating Passive Ankle Torque With Subject-Specific Adaptation.

BACKGROUND: Robot-assisted ankle assessment could potentially be conducted using sensor-based and model-based methods. Existing ankle rehabilitation robots usually use torquemeters and multiaxis load cells for measuring joint dynamics. These measurements are accurate, but the contribution as a result of muscles and ligaments is not taken into account. Some computational ankle models have been developed to evaluate ligament strain and joint torque. These models do not include muscles and, thus, are not suitable for an overall ankle assessment in robot-assisted therapy. METHODS: This study proposed a computational ankle model for use in robot-assisted therapy with three rotational degrees of freedom, 12 muscles, and seven ligaments. This model is driven by robotics, uses three independent position variables as inputs, and outputs an overall ankle assessment. Subject-specific adaptations by geometric and strength scaling were also made to allow for a universal model. RESULTS: This model was evaluated using published results and experimental data from 11 participants. Results show a high accuracy in the evaluation of ligament neutral length and passive joint torque. The subject-specific adaptation performance is high, with each normalized root-mean-square deviation value less than 10%. CONCLUSION: This model could be used for ankle assessment, especially in evaluating passive ankle torque, for a specific individual. The characteristic that is unique to this model is the use of three independent position variables that can be measured in real time as inputs, which makes it advantageous over other models when combined with robot-assisted therapy.

Review on design and control aspects of ankle rehabilitation robots.

Ankle rehabilitation robots can play an important role in improving outcomes of the rehabilitation treatment by assisting therapists and patients in number of ways. Consequently, few robot designs have been proposed by researchers which fall under either of the two categories, namely, wearable robots or platform-based robots. This paper presents a review of both kinds of ankle robots along with a brief analysis of their design, actuation and control approaches. While reviewing these designs it was observed that most of them are undesirably inspired by industrial robot designs. Taking note of the design concerns of current ankle robots, few improvements in the ankle robot designs have also been suggested. Conventional position control or force control approaches, being used in the existing ankle robots, have been reviewed. Apparently, opportunities of improvement also exist in the actuation as well as control of ankle robots. Subsequently, a discussion on most recent research in the development of novel actuators and advanced controllers based on appropriate physical and cognitive human-robot interaction has also been included in this review. Implications for Rehabilitation Ankle joint functions are restricted/impaired as a consequence of stroke or injury during sports or otherwise. Robots can help in reinstating functions faster and can also work as tool for recording rehabilitation data useful for further analysis. Evolution of ankle robots with respect to their design and control aspects has been discussed in the present paper and a novel design with futuristic control approach has been proposed.

Adaptive impedance control of a robotic orthosis for gait rehabilitation.

Intervention of robotic devices in the field of physical gait therapy can help in providing repetitive, systematic, and economically viable training sessions. Interactive or assist-as-needed (AAN) gait training encourages patient voluntary participation in the robotic gait training process which may aid in rapid motor function recovery. In this paper, a lightweight robotic gait training orthosis with two actuated and four passive degrees of freedom (DOFs) is proposed. The actuated DOFs were powered by pneumatic muscle actuators. An AAN gait training paradigm based on adaptive impedance control was developed to provide interactive robotic gait training. The proposed adaptive impedance control scheme adapts the robotic assistance according to the disability level and voluntary participation of human subjects. The robotic orthosis was operated in two gait training modes, namely, inactive mode and active mode, to evaluate the performance of the proposed control scheme. The adaptive impedance control scheme was evaluated on ten neurologically intact subjects. The experimental results demonstrate that an increase in voluntary participation of human subjects resulted in a decrease of the robotic assistance and vice versa. Further clinical evaluations with neurologically impaired subjects are required to establish the therapeutic efficacy of the adaptive-impedance-control-based AAN gait training strategy.

Effect of cadence regulation on muscle activation patterns during robot assisted gait: a dynamic simulation study.

Cadence or stride frequency is an important parameter being controlled in gait training of neurologically impaired subjects. The aim of this study was to examine the effects of cadence variation on muscle activation patterns during robot assisted unimpaired gait using dynamic simulations. A twodimensional (2-D) musculoskeletal model of human gait was developed considering eight major muscle groups along with existing ground contact force (GCF) model. A 2-D model of a robotic orthosis was also developed which provides actuation to the hip, knee and ankle joints in the sagittal plane to guide subjects limbs on reference trajectories. A custom inverse dynamics algorithm was used along with a quadratic minimization algorithm to obtain a feasible set of muscle activation patterns. Predicted patterns of muscle activations during slow, natural and fast cadence were compared and the mean muscle activations were found to be increasing with an increase in cadence. The proposed dynamic simulation provide important insight into the muscle activation variations with change in cadence during robot assisted gait and provide the basis for investigating the influence of cadence regulation on neuromuscular parameters of interest during robot assisted gait.

Bone-muscle interaction of the fractured femur.

The interaction forces of a fractured femur among the bone, muscle, and other soft tissues are not well understood. Only a small number of in vivo measurements have been made and with many limitations. Mathematical modeling is a useful alternative, overcoming limitations and allowing investigation of hypothetical simulated reductions. We aimed to develop a model to help understand best practices in fracture reduction and to form a base to develop new technologies and procedures. The simulation environment allows muscle forces and moments to deform a fractured femur, and the behavior of forces during reduction can be found. Visual and numerical output of forces and moments during simulated reduction procedures are provided. The output can be probed throughout the reduction procedure down to the individual muscle's contribution. This is achieved by construction of an anatomically correct three-dimensional mathematical model of the lower extremity and muscles. Parameters are fully customizable and can be used to investigate simple, oblique, and some comminuted fractures. Results were compared with published in vivo measurements and were of the same magnitude. A simple midshaft fracture had a maximum resulting force of 428 N, whereas traction from the hip reached a maximum value of 893 N at 60 mm of displacement. Monte Carlo analysis revealed that the deforming force was most sensitive to the muscles' rest lengths. The developed model provides greater understanding and detail than in vivo measurements have to date. It allows new treatment procedures to be developed and importantly to assess the outcome.