Feasibility of Manual Teach-and-Replay and Continuous Impedance Shaping for Robotic Locomotor Training Following Spinal Cord Injury

Robotic gait training is an emerging technique for retraining walking ability following spinal cord injury (SCI). A key challenge in this training is determining an appropriate stepping trajectory and level of assistance for each patient, since patients have a wide range of sizes and impairment levels. Here, we demonstrate how a lightweight yet powerful robot can record subject-specific, trainer-induced leg trajectories during manually assisted stepping, then immediately replay those trajectories. Replay of the subject-specific trajectories reduced the effort required by the trainer during manual assistance, yet still generated similar patterns of muscle activation for six subjects with a chronic SCI. We also demonstrate how the impedance of the robot can be adjusted on a step-by-step basis with an error-based, learning law. This impedance-shaping algorithm adapted the robot's impedance so that the robot assisted only in the regions of the step trajectory where the subject consistently exhibited errors. The result was that the subjects stepped with greater variability, while still maintaining a physiologic gait pattern. These results are further steps toward tailoring robotic gait training to the needs of individual patients

MODIFIED INTERNAL MODEL CONTROL FOR A THERAPEUTIC ROBOT

We present the use of the modified internal model controller (MIMC) and the “Probability Tube” (PT) action representation for robot-assisted upper extremities training of hemiplegic patients. The robot-assisted training session has two phases. During the first "demonstration" phase the robot learns from the therapist the target path through examples. In the second "exercise" phase the robot assists a patient to follow the target path. During this process, the control limits the interface force between the robot and the hand to be below the preset threshold (F = 50 N). The system allows the assessment of the range of movement, the positional error between the target and the reached position, the amount of added assistance (the interface force between the hand and the robot). We demonstrate the operation in two hemiplegic patients. The patients and therapist suggested after the tests that the new system is straightforward and intuitive for clinical applications

Short-term locomotor adaptation to a robotic ankle exoskeleton does not alter soleus Hoffmann reflex amplitude

<p>Abstract</p> <p>Background</p> <p>To improve design of robotic lower limb exoskeletons for gait rehabilitation, it is critical to identify neural mechanisms that govern locomotor adaptation to robotic assistance. Previously, we demonstrated soleus muscle recruitment decreased by ~35% when walking with a pneumatically-powered ankle exoskeleton providing plantar flexor torque under soleus proportional myoelectric control. Since a substantial portion of soleus activation during walking results from the stretch reflex, increased reflex inhibition is one potential mechanism for reducing soleus recruitment when walking with exoskeleton assistance. This is clinically relevant because many neurologically impaired populations have hyperactive stretch reflexes and training to reduce the reflexes could lead to substantial improvements in their motor ability. The purpose of this study was to quantify soleus Hoffmann (H-) reflex responses during powered versus unpowered walking.</p> <p>Methods</p> <p>We tested soleus H-reflex responses in neurologically intact subjects (n=8) that had trained walking with the soleus controlled robotic ankle exoskeleton. Soleus H-reflex was tested at the mid and late stance while subjects walked with the exoskeleton on the treadmill at 1.25 m/s, first without power (first unpowered), then with power (powered), and finally without power again (second unpowered). We also collected joint kinematics and electromyography.</p> <p>Results</p> <p>When the robotic plantar flexor torque was provided, subjects walked with lower soleus electromyographic (EMG) activation (27-48%) and had concomitant reductions in H-reflex amplitude (12-24%) compared to the first unpowered condition. The H-reflex amplitude in proportion to the background soleus EMG during powered walking was not significantly different from the two unpowered conditions.</p> <p>Conclusion</p> <p>These findings suggest that the nervous system does not inhibit the soleus H-reflex in response to short-term adaption to exoskeleton assistance. Future studies should determine if the findings also apply to long-term adaption to the exoskeleton.</p

A Novel Design and Implementation of a 4-DOF Upper Limb Exoskeleton for Stroke Rehabilitation with Active Assistive Control Strategy

We developed a robot, CUREs (Chulalongkorn University Rehabilitation Robotic Exoskeleton system), for upper extremity rehabilitation. The active assistive control strategy based on the impedance force control is developed and implemented to obtain assistive-resistive paths tracking for rehabilitation activities. The desired trajectory or rehabilitated training pattern for each specific patient need to be assigned first by a medical doctor and a physical therapy. The therapist can program the desired trajectory by guiding the patient arm based on the assigned path pattern and the set of via points will be stored and used for generating the desired trajectory. The desired trajectory will be stored specific for the patient and can be called back anytime. During the rehabilitation, the robot can assist and resist the patient’s arm to follow the desired trajectory. If the patient has difficulty moving his arm to track the desired path, the robot will help by adding more torque to help the patient to move his arm to reduce the error between the desired path and the actual posture. And if the patient himself can move his arm tracking the desired path, the robot will not apply any more force to assist or resist. The necessary state variables such as angular position and torque can be recorded during the training. The main purpose of the experiment, follow the medical ethic, is to assure that there is no side effect for using this rehabilitation robot. Five subacute stroke patients participated in this pilot study. All patients have severe upper extremity weakness. The medical doctor will assign the training pattern based on patient condition. The result showed that the Fugl-Meyer Assessment Upper Extremity Scale was improved after 10 days of training in all participants without any sign of side effect.We developed a robot, CUREs (Chulalongkorn University Rehabilitation Robotic Exoskeleton system), for upper extremity rehabilitation. The active assistive control strategy based on the impedance force control is developed and implemented to obtain assistive-resistive paths tracking for rehabilitation activities. The desired trajectory or rehabilitated training pattern for each specific patient need to be assigned first by a medical doctor and a physical therapy. The therapist can program the desired trajectory by guiding the patient arm based on the assigned path pattern and the set of via points will be stored and used for generating the desired trajectory. The desired trajectory will be stored specific for the patient and can be called back anytime. During the rehabilitation, the robot can assist and resist the patient’s arm to follow the desired trajectory. If the patient has difficulty moving his arm to track the desired path, the robot will help by adding more torque to help the patient to move his arm to reduce the error between the desired path and the actual posture. And if the patient himself can move his arm tracking the desired path, the robot will not apply any more force to assist or resist. The necessary state variables such as angular position and torque can be recorded during the training. The main purpose of the experiment, follow the medical ethic, is to assure that there is no side effect for using this rehabilitation robot. Five subacute stroke patients participated in this pilot study. All patients have severe upper extremity weakness. The medical doctor will assign the training pattern based on patient condition. The result showed that the Fugl-Meyer Assessment Upper Extremity Scale was improved after 10 days of training in all participants without any sign of side effect

Patient-cooperative control increases active participation of individuals with SCI during robot-aided gait training

ABSTRACT: BACKGROUND: Manual body weight supported treadmill training and robot-aided treadmill training are frequently used techniques for the gait rehabilitation of individuals after stroke and spinal cord injury. Current evidence suggests that robot-aided gait training may be improved by making robotic behavior more patient-cooperative. In this study, we have investigated the immediate effects of patient-cooperative versus non-cooperative robot-aided gait training on individuals with incomplete spinal cord injury (iSCI). METHODS: Eleven patients with iSCI participated in a single training session with the gait rehabilitation robot Lokomat. The patients were exposed to four different training modes in random order: During both non-cooperative position control and compliant impedance control, fixed timing of movements was provided. During two variants of the patient-cooperative path control approach, free timing of movements was enabled and the robot provided only spatial guidance. The two variants of the path control approach differed in the amount of additional support, which was either individually adjusted or exaggerated. Joint angles and torques of the robot as well as muscle activity and heart rate of the patients were recorded. Kinematic variability, interaction torques, heart rate and muscle activity were compared between the different conditions. RESULTS: Patients showed more spatial and temporal kinematic variability, reduced interaction torques, a higher increase of heart rate and more muscle activity in the patient-cooperative path control mode with individually adjusted support than in the non-cooperative position control mode. In the compliant impedance control mode, spatial kinematic variability was increased and interaction torques were reduced, but temporal kinematic variability, heart rate and muscle activity were not significantly higher than in the position control mode. CONCLUSIONS: Patient-cooperative robot-aided gait training with free timing of movements made individuals with iSCI participate more actively and with larger kinematic variability than non-cooperative, position-controlled robot-aided gait training

Active interaction control applied to a lower limb rehabilitation robot by using EMG recognition and impedance model

Purpose – The purpose of this paper is to propose a seamless active interaction control method integrating electromyography (EMG)-triggered assistance and the adaptive impedance control scheme for parallel robot-assisted lower limb rehabilitation and training. Design/methodology/approach – An active interaction control strategy based on EMG motion recognition and adaptive impedance model is implemented on a six-degrees of freedom parallel robot for lower limb rehabilitation. The autoregressive coefficients of EMG signals integrating with a support vector machine classifier are utilized to predict the movement intention and trigger the robot assistance. An adaptive impedance controller is adopted to influence the robot velocity during the exercise, and in the meantime, the user’s muscle activity level is evaluated online and the robot impedance is adapted in accordance with the recovery conditions. Findings – Experiments on healthy subjects demonstrated that the proposed method was able to drive the robot according to the user’s intention, and the robot impedance can be updated with the muscle conditions. Within the movement sessions, there was a distinct increase in the muscle activity levels for all subjects with the active mode in comparison to the EMG-triggered mode. Originality/value – Both users’ movement intention and voluntary participation are considered, not only triggering the robot when people attempt to move but also changing the robot movement in accordance with user’s efforts. The impedance model here responds directly to velocity changes, and thus allows the exercise along a physiological trajectory. Moreover, the muscle activity level depends on both the normalized EMG signals and the weight coefficients of involved muscles

Review of control strategies for robotic movement training after neurologic injury

There is increasing interest in using robotic devices to assist in movement training following neurologic injuries such as stroke and spinal cord injury. This paper reviews control strategies for robotic therapy devices. Several categories of strategies have been proposed, including, assistive, challenge-based, haptic simulation, and coaching. The greatest amount of work has been done on developing assistive strategies, and thus the majority of this review summarizes techniques for implementing assistive strategies, including impedance-, counterbalance-, and EMG- based controllers, as well as adaptive controllers that modify control parameters based on ongoing participant performance. Clinical evidence regarding the relative effectiveness of different types of robotic therapy controllers is limited, but there is initial evidence that some control strategies are more effective than others. It is also now apparent there may be mechanisms by which some robotic control approaches might actually decrease the recovery possible with comparable, non-robotic forms of training. In future research, there is a need for head-to-head comparison of control algorithms in randomized, controlled clinical trials, and for improved models of human motor recovery to provide a more rational framework for designing robotic therapy control strategies