Vijaykumar Rajasekaran

Control of an ambulatory exoskeleton with a brain-machine interface for spinal cord injury gait rehabilitation

The closed-loop control of rehabilitative technologies by neural commands has shown a great potential to improve motor recovery in patients suffering from paralysis. Brain–machine interfaces (BMI) can be used as a natural control method for such technologies. BMI provides a continuous association between the brain activity and peripheral stimulation, with the potential to induce plastic changes in the nervous system. Paraplegic patients, and especially the ones with incomplete injuries, constitute a potential target population to be rehabilitated with brain-controlled robotic systems, as they may improve their gait function after the reinforcement of their spared intact neural pathways. This paper proposes a closed-loop BMI system to control an ambulatory exoskeleton—without any weight or balance support—for gait rehabilitation of incomplete spinal cord injury (SCI) patients. The integrated system was validated with three healthy subjects, and its viability in a clinical scenario was tested with four SCI patients. Using a cue-guided paradigm, the electroencephalographic signals of the subjects were used to decode their gait intention and to trigger the movements of the exoskeleton. We designed a protocol with a special emphasis on safety, as patients with poor balance were required to stand and walk. We continuously monitored their fatigue and exertion level, and conducted usability and user-satisfaction tests after the experiments. The results show that, for the three healthy subjects, 84.44 ± 14.56% of the trials were correctly decoded. Three out of four patients performed at least one successful BMI session, with an average performance of 77.6 1 ± 14.72%. The shared control strategy implemented (i.e., the exoskeleton could only move during specific periods of time) was effective in preventing unexpected movements during periods in which patients were asked to relax. On average, 55.22 ± 16.69% and 40.45 ± 16.98% of the trials (for healthy subjects and patients, respectively) would have suffered from unexpected activations (i.e., false positives) without the proposed control strategy. All the patients showed low exertion and fatigue levels during the performance of the experiments. This paper constitutes a proof-of-concept study to validate the feasibility of a BMI to control an ambulatory exoskeleton by patients with incomplete paraplegia (i.e., patients with good prognosis for gait rehabilitation).

Recovering Planned Trajectories in Robotic Rehabilitation Therapies under the Effect of Disturbances

Robotic rehabilitation is an emerging technology in the field of Neurorehabilitation, which aims to achieve an effective patient recovery. This research focusses on the control strategy for an assistive exoskeleton aiming to reduce the effects of disturbances on planned trajectories during rehabilitation therapies. Disturbances are mostly caused by muscle synergies or by unpredictable actions produced by functional electrical stimulation. The effect of these disturbances can be either assistive or resistive forces depending on the patients movement, which increase or decrease the speed of the affected joints by forcing the control unit to act consequently. In some therapies, like gait assistance, it is also essential to maintain synchronization between joint movements, to ensure a dynamic stability. A force control approach is used for all the joints individually, while two control methods are defined to act when disturbances are detected: Cartesian position control (Cartesian level) and Variable execution speed (joint level). The trajectory to be followed by the patient is previously recorded using an active exoskeleton, H1, worn by healthy subjects. A realistic simulation model of the exoskeleton is used for testing the effect of disturbances on the particular joints and on the planned trajectory and for evaluating the performance of the two proposed control methods. The performances of the presented methods are evaluated by comparing the resulting trajectories with respect to those planned. The evaluation of the most suitable method is performed considering the following factors: stability, minimum time delay and synchronization of the joints.

Event-based control for sit-to-stand transition using a wearable exoskeleton

Sit-to-stand transition is an essential step in a lower limb rehabilitation therapy, mainly for assisting the patient to transit from wheel chair to the next level of therapy. A mixed stiffness-damping control adaptation is proposed for this task which will help in reaching the final position with a constant velocity. A combination of control model is proposed to ensure the initiation and the final stage of the transition, such as to ensure stability and to maintain the equilibrium. The combined control model helps in reaching the goal position with equal participation from the user. For patient studies, such as with paraplegic patients, a combinational control model with muscle stimulation can be included to provide a complete assistance. The role of muscle stimulation and joint movement assistance is also considered in this control model. Further, final stage of this transition must ensure keeping or helping the user to maintain the upright position.

User Intention Driven Adaptive Gait Assistance Using a Wearable Exoskeleton

A user intention based rehabilitation strategy for a lower-limb wearable robot is proposed and evaluated. The control strategy, which involves monitoring the human-orthosis interaction torques, determines the gait initiation instant and modifies orthosis operation for gait assistance, when needed. Orthosis operation is classified as assistive or resistive in function of its evolution with respect to a normal gait pattern. The control algorithm relies on the adaptation of the joints’ stiffness in function of their interaction torques and their deviation from the desired trajectories. An average of recorded gaits obtained from healthy subjects is used as reference input. The objective of this work is to develop a control strategy that can trigger the gait initiation from the user’s intention and maintain the dynamic stability, using an efficient real-time stiffness adaptation for multiple joints, simultaneously maintaining their synchronization. The algorithm has been tested with five healthy subjects showing its efficient behavior in initiating the gait and maintaining the equilibrium while walking in presence of external forces. The work is performed as a preliminary study to assist patients suffering from incomplete Spinal cord injury and Stroke.

Adaptive walking assistance based on human-orthosis interaction

An assistive rehabilitation strategy for a lower-limb wearable robot is proposed and evaluated. The control strategy monitors the human-orthosis interaction torques and modifies the orthosis operation mode depending on its evolution with respect to a normal gait pattern. The control algorithm relies on the adaptation of the joints stiffness in function of these interaction torques and to the deviation from the desired trajectory. A walking pattern, an average of recorded gaits, is used as reference input. The human-orthosis interaction torques are used to define the time instant when robot assistance is needed and its degree. The objective of this work is to demonstrate the feasibility of ensuring a dynamic stability by means of an efficient real-time stiffness adaptation for multiple joints and simultaneously maintaining their synchronization. The algorithm has been tested with five healthy subjects showing its efficient behavior in maintaining the equilibrium while walking in presence of external forces. The work is performed as a preliminary study to assist patients suffering from Spinal cord injury and Stroke.

Volition-adaptive control for gait training using wearable exoskeleton: preliminary tests with incomplete spinal cord injury individuals

BackgroundGait training for individuals with neurological disorders is challenging in providing the suitable assistance and more adaptive behaviour towards user needs. The user specific adaptation can be defined based on the user interaction with the orthosis and by monitoring the user intentions. In this paper, an adaptive control model, commanded by the user intention, is evaluated using a lower limb exoskeleton with incomplete spinal cord injury individuals (SCI).MethodsA user intention based adaptive control model has been developed and evaluated with 4 incomplete SCI individuals across 3 sessions of training per individual. The adaptive control model modifies the joint impedance properties of the exoskeleton as a function of the human-orthosis interaction torques and the joint trajectory evolution along the gait sequence, in real time. The volitional input of the user is identified by monitoring the neural signals, pertaining to the user’s motor activity. These volitional inputs are used as a trigger to initiate the gait movement, allowing the user to control the initialization of the exoskeleton movement, independently. A Finite-state machine based control model is used in this set-up which helps in combining the volitional orders with the gait adaptation.ResultsThe exoskeleton demonstrated an adaptive assistance depending on the patients’ performance without guiding them to follow an imposed trajectory. The exoskeleton initiated the trajectory based on the user intention command received from the brain machine interface, demonstrating it as a reliable trigger. The exoskeleton maintained the equilibrium by providing suitable assistance throughout the experiments. A progressive change in the maximum flexion of the knee joint was observed at the end of each session which shows improvement in the patient performance. Results of the adaptive impedance were evaluated by comparing with the application of a constant impedance value. Participants reported that the movement of the exoskeleton was flexible and the walking patterns were similar to their own distinct patterns.ConclusionsThis study demonstrates that user specific adaptive control can be applied on a wearable robot based on the human-orthosis interaction torques and modifying the joints’ impedance properties. The patients perceived no external or impulsive force and felt comfortable with the assistance provided by the exoskeleton. The main goal of such a user dependent control is to assist the patients’ needs and adapt to their characteristics, thus maximizing their engagement in the therapy and avoiding slacking. In addition, the initiation directly controlled by the brain allows synchronizing the user’s intention with the afferent stimulus provided by the movement of the exoskeleton, which maximizes the potentiality of the system in neuro-rehabilitative therapies.

Handling Disturbances on Planned Trajectories in Robotic Rehabilitation Therapies

Robotic rehabilitation therapies are an emerging tool in the field of Neurorehabilitation in order to achieve an effective therapeutic development in the patient. In this paper, the role of disturbances caused by muscle synergies or unpredictable effects of artificial stimulation in muscles during rehabilitation therapies is analyzed. In terms of gait assistance it is also important to maintain synchronized movements to ensure a dynamically stable gait. Although, disturbances affecting joints are corrected by a force control approach, we define two methods to ensure stability and synchronization of joint movements in the trajectory to be followed. The performance of the presented methods is evaluated in comparison with a preplanned trajectory to be followed by the patients.

Robotic Rehabilitation: Ten Critical Questions about Current Status and Future Prospects Answered by Emerging Researchers

Robotic rehabilitation research and development accelerated dramatically in the last 20 years, yet the success of the field is still debatable. A critical evaluation of the the current status and future prospects of the field is provided by discussing 10 key questions for the field. Five emerging researchers in the field offer responses to the questions, intending to provide a means to step back and see the field through new eyes. A senior researcher in the field briefly comments on this emerging perspective. Enhanced adaptability and intelligence in addition to better integration within the patients environmental context were identified in this chapter as the areas for future breakthroughs.