Wearable Rehabilitation Robot Research Articles

Trajectory tracking control of wearable upper limb rehabilitation robot based on Laguerre model predictive control

Wearable rehabilitation robots have become an important auxiliary tool in rehabilitation therapy, providing effective rehabilitation training and helping to recover damaged muscles and joints. In response to the difficulty of traditional control methods in solving various constraints in the trajectory tracking process of the Upper Limb Rehabilitation Robot (ULRR), this study uses model predictive control to study the trajectory tracking problem of the upper limb rehabilitation robot. Firstly, based on the Lagrangian dynamic model of wearable rehabilitation robots, an extended state space model with pseudo linearization of the system was established. Given the performance indicators and various constraints of the system, a corresponding model predictive controller is designed based on the Laguerre model to ensure system performance while greatly reducing the computational complexity of predictive control. Secondly, the stability of the model predictive controller is demonstrated, and a disturbance observer is introduced into the controller to achieve compensation for slow-varying perturbations; a joint space sliding mode variable is also introduced to achieve simultaneous tracking of the joint’s desired position and desired velocity. Finally, taking a planar two bar robot as an example, comparative simulation verification was conducted on unconstrained joint trajectory tracking and constrained joint trajectory tracking. The simulation results show that the model predictive controller can achieve simultaneous tracking of joint expected trajectory and expected speed while meeting various constraints. It has good effects in improving patient motion control ability and reducing patient fatigue, providing new research ideas and methods for the field of rehabilitation therapy.

Dynamic Modelling and Optimal Sliding Mode Control of the Wearable Rehabilitative Bipedal Cable Robot with 7 Degrees of Freedom

Although robot-assisted physiotherapy has gained increasing attention in recent years, the use of wearable rehabilitation robots for lower limbs has shown reduced efficiency due to additional equipment and motors located at the center of the joint, increasing complexity and load on disabled patients. This paper proposes a novel rehabilitation approach by eliminating motors and equipment from the center of joints and placing them on a fixed platform using cable-based power transmission. A proposed model of a 14 cable-driven bipedal robot with 7 degrees of freedom has been used to model a lower limb rehabilitation robot corresponding to it. The dynamic equations of the robot are derived using the Euler-Lagrange method. The sliding mode control technique is utilized to offer accurate control for tracking desired trajectories, ensuring smoothness despite disturbances, and reducing tracking errors. This approach is employed to help prevent patients from falling and support them in maintaining balance during rehabilitative exercises. To ensure that cables exert positive tension, the sliding mode controller was combined with quadratic programming optimization, minimizing path error while constraining the controller input torque to be non-negative. The performance of the proposed controller was assessed by considering several control gains resulting in K = 10 identified as the most effective one. The feasibility of this approach to rehabilitation is demonstrated by the numerical results in MATLAB simulation, which show that the RMSE amount of the right and left hip and thigh angles are 0.29, 0.37, 0.31, and 0.44, respectively which verified an improved rehabilitation process. Also, the correlation coefficient between the Adams and MATLAB simulation results for motor torque was found to be 0.98, indicating a high degree of correlation between the two simulation results.

Paediatric ankle rehabilitation system based on twisted and coiled polymer actuators

Rehabilitation is crucial for children with physical disabilities arising from various conditions. Traditional exoskeletons, reliant on electric motors and rigid components, making them cumbersome, heavy, and unsuitable for use outside clinical facilities. To overcome these, researchers are turning to soft wearable rehabilitation robots (SWRRs) with artificial muscles based on smart materials like twisted and coiled polymer actuators (TCPs). TCPs offer enhanced compliance, adaptability, comfort, safety, and reduced weight—critical for paediatric use. Despite facing challenges like low operating frequencies and high temperatures, TCPs are explored as potential artificial muscles for SWRRs, due to their advantages on the force they can generate, the strain and a linear behaviour. This study details a proof of concept for a paediatric rehabilitation system for ankles based on TCPs, including the actuator characterization, mechanical design, control strategy, and human-computer-interface (HCI). The resulting device achieved a 1.4 Nm torque, a 10° range of motion in dorsiflexion within 5 s, and integrated electromyographic HCI. This research marks a promising step towards innovative, soft wearable rehabilitation solutions for children with physical disabilities.

Soft Artificial Muscle Based on Pre-Detwinned Shape Memory Alloy Spring Actuator Achieving High Passive Assistive Torque for Wearable Robot.

For designing the assistive wearable rehabilitation robots, it is challenging to design the robot as energy efficient because the actuators have to be capable of overcoming human loads such as gravity of the body and spastic torque continuously during the assistance. To address these challenges, we propose a novel design of soft artificial muscle that utilizes shape memory alloy (SMA) spring actuators with pre-detwinning process. The SMA spring was fabricated through a process called pre-detwinning, which enhances the linearity of the SMA spring in martensite phase and unpowered restoring force, which is called passive force. The fabricated SMA spring can contract >60%. Finally, the soft wearable robot that can assist not only the gravitational torque exerted on the elbow by passive force, but also the elbow movements with active force was designed with a soft artificial muscle. A soft artificial muscle consists of the bundles of pre-detwinned SMA springs integrated with the stretchable coolant vessel. The stiffness of the muscle was measured as 1125 N/m in martensite phase and 1732 N/m in austenite phase. In addition, the muscle showed great actuation frequency performances, the bandwidth of which was measured as 0.5 Hz. The proposed wearable mechanism can fully compensate the gravitational torque for all the angles in passive mode. In addition, the proposed mechanism can produce high torque up to 3.5 Nm and movements in active mode.

Finger joint aligned flat tube folding structure for robotic glove design

Pneumatic soft actuators have been widely considered the safest actuation technology for use in wearable rehabilitation robots. For soft robotic gloves, researchers commonly put soft extending or bending actuators on dorsal fingers to assist hand flexion. In this research, we propose a novel pre-folded flat tube actuator (PFTA) to assist finger flex into a pre-set bending angle or contact force. The PFTA has three folds, aligned with each of the finger joint. Different from other soft actuators, the PFTA exerts bending torque directly on each finger joint without large actuator deformation. The PFTA made of heat shrink flat tube has a small profile, with low cost, easy fabrication, and high safety. When actuated, the PFTA has the tendency to unfold as well, we call this effect as unfolding flat tube actuation. This effect is characterized by a range of bending angles and input air pressures in which four distinct response regimes were observed. They are defined as shearing, collapsing, creasing, and flattening regimes. Similarly, experimental characterization of PFTAs is also conducted to evaluate the level of joint flexion assistance based on which design guidelines for robotic gloves are recommended. Finally, we build PFTAs on a soft wearable glove and demonstrate their capability in assisting the grasping operations of various object shapes.

Improved performance in temperature and speed of TCP artificial muscles for soft wearables robots by length modification

Artificial muscles provide a unique solution for wearable rehabilitation robots (WRRs) because they are compliant, compact, and lightweight. Twisted and coiled polymer actuators (TCPs) are artificial muscles from thermally activated polymer fibres. They present high power density, linearity, stress and strain compared to other artificial muscles. Nevertheless, as TCPs require heat to start, their main barrier for widespread use in WRRs are their slow reaction times and the high temperatures they reach. Previous studies have analysed different parameters, like fibre material, fibre diameter, and various cooling systems, to improve TCP frequency response and working temperature. Nevertheless, the length of the actuator has not been explored as a possible parameter to enhance the actuation performance in this regard. This work focuses on studying the behaviour of TCPs with different lengths and how the performance in frequency response and temperature can be improved using the length as a primary parameter, as they are critical for wearable robots. First, a characterisation of the TCPs was performed. Then, a method to improve frequency response, based on offsets on long actuators was implemented and validated using a chirp signal. The experimental results show that the mechanical characteristics are similar regardless of the actuator’s length. They reached a strain of 10% with a power of 0.16 W cm−1. However, the electrothermal properties changed as the power needed to increase temperature was higher when the actuator was enlarged. Therefore, an improvement in the required temperature was found, able to reduce the temperature with the same frequency response. Regarding the technique to enhance the speed of the actuator, it was possible to increase the frequency by 0.0006 Hz for each mm applied as an offset. Hence, the frequency response for the same displacement was increased linearly as the actuator was elongated.

Gait training with a wearable powered robot during stroke rehabilitation: a randomized parallel-group trial

BackgroundWe have developed a wearable rehabilitation robot, “curara®,” and examined its immediate effect in patients with spinocerebellar degeneration and stroke, but its rehabilitative effect has not been clarified. The purpose of this study was to examine the effect of this device on gait training in stroke patients.MethodsForty stroke patients were enrolled in this study. The participants were divided randomly into two groups (groups A and B). The participants assigned to group A received RAGT with curara® type 4, whereas those in group B received conventional therapist-assisted gait training. The clinical trial period was 15 days. The participants performed 10 sessions of gait training (5 times per week) each lasting 30 ± 5 min per day. The 10-m walking time (10mWT), and 6-minute walking distance (6MWD) were evaluated as the main outcomes. Timed up and go and Berg Balance Scale (BBS) were also examined. Gait parameters (stride duration and length, standard deviation of stride duration and length, cadence, ratio of the stance/swing phases, minimum/maximum knee joint angle, and minimum/maximum hip joint angle) were measured using a RehaGait®. The items other than BBS were measured on days 0, 7, and 14, whereas BBS was measured on days 0 and 14. The improvement rate was calculated as the difference of values between days 14 and 0 divided by the value on day 0. The improvement rates of the 10mWT and 6MWD were set as the main outcomes.ResultsThe data of 35 participants were analyzed. There was no significant difference in the main outcomes between both groups at the end of gait training. As for intragroup changes, gait speed, stride length, stride duration, and cadence were improved significantly between days 0 and 14 in each group. When examining the interaction effect between the day of measurement and group, stride duration (p = 0.006) and cadence (p = 0.012) were more significantly improved in group A than in group B.ConclusionsThis novel wearable powered robot may have the potential to improve gait speed of individuals in stroke rehabilitation.Trial registrationJapan Registry of Clinical Trials (jRCTs032180163). Registered on February 22, 2019; https://jrct.niph.go.jp/en-latest-detail/jRCTs032180163.UMIN Clinical Trials Registry (UMIN000034237)Registered on September 22, 2018; https://center6.umin.ac.jp/cgi-open-bin/icdr/ctr_view.cgi?recptno=R000038939.

Soft Wearable Rehabilitation Robots with Artificial Muscles based on Smart Materials: A Review

Wearables robots have gained attention for the rehabilitation of people with physical disabilities. However, the current technology relies on heavy and bulky actuation components, making it hard to use outside clinical settings. Artificial muscles based on smart materials are trending for soft wearable rehabilitation robots as they present advantages of compliance, are lightweight, and do not require external components. Nevertheless, they present challenges that remain unresolved, preventing widespread adoption. This work reviews the current state of soft wearable rehabilitation robots with artificial muscles based on smart materials (AMSMs). A literature search is conducted utilizing Web of Science and Scopus. Based on the inclusion–exclusion criteria, 15 devices are found using four different smart materials. This study attempts to provide an insight into the distinct biomechanical requirements, the use of smart materials, their limitations, their designs, and possible future research directions, which can provide helpful guidance on the implementation and development of advanced soft wearable rehabilitation robots with AMSMs.

Robot-assisted assessment of the effects of self-aligning mechanism on the wrist passive range of motion

Axis alignment between human and robot has been a research hotspot in wearable rehabilitation robots and has a significant effects on full natural ranges of motion (ROM) during robot-assisted training exercises. Self-alignment mechanism (SAM) has been extensively applied on the rehabilitation robots to adaptively compensate the axis misalignment between human anatomic and robot mechanical joints. However, the effects of the SAM on the wrist ROM have not been definitely assessed. In this study, we implemented a SAM on a wrist rehabilitation device (WReD II), and the SAM was specially designed to be locked or unlocked to achieve self-alignment function or not according to demands. To assess the effects of SAM on the wrist passive ROM of extension/flexion (E/F), passive training experiments involving 8 healthy participants were conducted by locking or unlocking the SAM respectively. Surface Electromyography (sEMG) was applied to monitor muscle activity during experiments. During the experiments, the wrist passive ROM were measured by applying the robot-assisted assessment technique. Preliminary results show that the means of the passive ROM have a maximum increase of 19.78° in the case with SAM unlocked when compared to the case with SAM locked. Statistical results indicated high test-retest reliability of the passive ROM measurements with intraclass correlation coefficient ICC (2,1) more than 0.82, and standard error of measurement (SEM) less than 3.2°. These findings suggest that the implement of SAM on the rehabilitation robots has great potentials due to its feasibility and reliability to obtain larger natural passive ROM.

Kineto-Static Analysis and Design Optimization of a 3-DOF Wrist Rehabilitation Parallel Robot with Consideration of the Effect of the Human Limb

When designing rehabilitation robots, there remains the challenge of ensuring the comfort and safety of users, especially for wearable rehabilitation robots that interact with human limbs. In this paper, we present a kineto-static analysis of the 3-RPS parallel wrist rehabilitation robot, taking into account the soft characteristics of the human limb and its kinematic mobility. First, the human upper-limb model was made to estimate the interaction force and moment through inverse kinematic analysis. Second, a static analysis was conducted to obtain the force and moment acting on the human limb, which is directly related to the user’s comfort and safety. Then, the design parameters of the 3-RPS robot were obtained by generic optimization through kineto-static analysis. Finally, the influence of the parasitic motion of the 3-RPS robot and the initial offset between the wrist center and the robot moving platform were discussed. Through the analysis results, we provide effective solutions to ensure the safety and comfort of the user.

Health Index Monitoring of Sports Injury Rehabilitation Training Based on Wearable Sensors.

In order to design the perception system of the lower limb wearable rehabilitation robot, this study established the kinematics theoretical model of human lower limb and conducted the kinematics analysis of human body. By using the dynamic attitude analysis system, combined with the human body mark points, the position data of human body mark points in the process of standing up, sitting up, walking, stepping up, and squatting were collected. Combined with the movement mechanism of human lower limbs, the characteristics of human motion state transition are analyzed, and the perceptual algorithm for judging human motion intention is studied, so as to determine the wearer's current posture, standing intention while sitting, walking intention while standing, moving intention, and stopping intention during walking. The results show that the angle of the hip joint changes regularly between 0° and 37° and the angle of the knee joint changes regularly between 0° and 70°during the standing process, which is consistent with the angle change trajectory collected by the dynamic attitude analysis system. The angle trajectories of the hip and knee joints measured by the absolute angle sensor are the same as those obtained by the dynamic attitude analysis system. 1.5 rad and 0.3 rad were selected as reasonable and effective thresholds for determining sitting and standing states.

Experimental Investigation for Two Links Wearable Rehabilitation Robot Dynamic According to Real Body Movement and Generate the Stability of the Trajectory Tracking by Classical PID Controller

Experimental Investigation for Two Links Wearable Rehabilitation Robot Dynamic According to Real Body Movement and Generate the Stability of the Trajectory Tracking by Classical PID Controller

Intelligent wearable rehabilitation robot control system based on mobile communication network

A large number of disabled people are caused by major diseases and accidents. Because disabled patients cannot exercise freely on their own, in order to prevent muscle atrophy, the most effective treatment is to exercise the patients’ limbs. Therefore, it is necessary to choose a more suitable rehabilitation training method to replace the traditional artificial rehabilitation training method, and the use of intelligent wearable rehabilitation robots to treat hemiplegia patients is particularly important for the rehabilitation treatment of hemiplegia patients. Rehabilitation robots can promote the development of medical technology and medical equipment, and have important practical significance for patients to overcome disease and recover health and build a harmonious family. This paper mainly studies the EMG research of the control system of intelligent wearable rehabilitation robot based on mobile communication network. This paper studies the way of stimulating signals and the processing of signal feedback in the process of electromyographic stimulation of rehabilitation robots to improve the rehabilitation effect of robots after stimulation; explores the problem of using biofeedback and fuzzy control rules to control patients for rehabilitation training, which urges patients actively participate in rehabilitation treatment, effectively guide the recovery of patients’ self-consciousness, and build a variety of training modes for rehabilitation robots to enhance the robot’s ability to adapt to different groups of people. In the experiments of this paper, the time window for data processing is 256ms, and the delay is also 256ms. It can be seen that the original SEMG signal of the control signal has some delay compared with the filtered SEMG signal.

Fuzzy sliding mode control of a wearable rehabilitation robot for wrist and finger

PurposeThe purpose of this paper is to introduce a new design for a finger and wrist rehabilitation robot. Furthermore, a fuzzy sliding mode controller has been designed to control the system.Design/methodology/approachFollowing an introduction regarding the hand rehabilitation, this paper discusses the conceptual and detailed design of a novel wrist and finger rehabilitation robot. The robot provides the possibility of rehabilitating each phalanx individually which is very important in the finger rehabilitation process. Moreover, due to the model uncertainties, disturbances and chattering in the system, a fuzzy sliding mode controller design method is proposed for the robot.FindingsWith the novel design for moving the DOFs of the system, the rehabilitation for the wrist and all phalanges of fingers is done with only two actuators which are combined in one device. These features make the system a good choice for home rehabilitation. To control the robot, a fuzzy sliding mode controller has been designed for the system. The fuzzy controller does not affect the coefficient of the sliding mode controller and uses the overall error of the system to make a control signal. Thus, the dependence of the controller to the model decreases and the system is more robust. The stability of the system is proved by the Lyapunov theorem.Originality/valueThe paper provides a novel design of a hand rehabilitation robot and a controller which is used to compensate the effects of the uncertain parameters and chattering phenomenon.

Estimation of Physical Human-Robot Interaction Using Cost-Effective Pneumatic Padding

The idea to use a cost-effective pneumatic padding for sensing of physical interaction between a user and wearable rehabilitation robots is not new, but until now there has not been any practical relevant realization. In this paper, we present a novel method to estimate physical human-robot interaction using a pneumatic padding based on artificial neural networks (ANNs). This estimation can serve as rough indicator of applied forces/torques by the user and can be applied for visual feedback about the user’s participation or as additional information for interaction controllers. Unlike common mostly very expensive 6-axis force/torque sensors (FTS), the proposed sensor system can be easily integrated in the design of physical human-robot interfaces of rehabilitation robots and adapts itself to the shape of the individual patient’s extremity by pressure changing in pneumatic chambers, in order to provide a safe physical interaction with high user’s comfort. This paper describes a concept of using ANNs for estimation of interaction forces/torques based on pressure variations of eight customized air-pad chambers. The ANNs were trained one-time offline using signals of a high precision FTS which is also used as reference sensor for experimental validation. Experiments with three different subjects confirm the functionality of the concept and the estimation algorithm.

1G3-3 インピーダンス制御を用いたウェアラブル・リハビリテーションロボット(OS1-2:ウェアラブルアシストシステムII,オーガナイズドセッション)

1G3-3 インピーダンス制御を用いたウェアラブル・リハビリテーションロボット(OS1-2:ウェアラブルアシストシステムII,オーガナイズドセッション)