Anindo Roy

Robot-Aided Neurorehabilitation: A Novel Robot for Ankle Rehabilitation

In this paper, we present the design and characterization of a novel ankle robot developed at the Massachusetts institute of technology (MIT). This robotic module is being tested with stroke patients at Baltimore Veterans administration medical center. The purpose of the on-going study is to train stroke survivors to overcome common foot drop and balance problems in order to improve their ambulatory performance. Its design follows the same guidelines of our upper extremity designs, i.e., it is a low friction, backdriveable device with intrinsically low mechanical impedance. Here, we report on the design and mechanical characteristics of the robot. We also present data to demonstrate the potential of this device as an efficient clinical measurement tool to estimate intrinsic ankle properties. Given the importance of the ankle during locomotion, an accurate estimate of ankle stiffness would be a valuable asset for locomotor rehabilitation. Our initial ankle stiffness estimates compare favorably with previously published work, indicating that our method may serve as an accurate clinical measurement tool.

Ankle Training With a Robotic Device Improves Hemiparetic Gait After a Stroke

Background. Task-oriented therapies such as treadmill exercise can improve gait velocity after stroke, but slow velocities and abnormal gait patterns often persist, suggesting a need for additional strategies to improve walking. Objectives. To determine the effects of a 6-week visually guided, impedance controlled, ankle robotics intervention on paretic ankle motor control and gait function in chronic stroke. Methods. This was a single-arm pilot study with a convenience sample of 8 stroke survivors with chronic hemiparetic gait, trained and tested in a laboratory. Subjects trained in dorsiflexion–plantarflexion by playing video games with the robot during three 1-hour training sessions weekly, totaling 560 repetitions per session. Assessments included paretic ankle ranges of motion, strength, motor control, and overground gait function. Results. Improved paretic ankle motor control was seen as increased target success, along with faster and smoother movements. Walking velocity also increased significantly, whereas durations of paretic single support increased and double support decreased. Conclusions. Robotic feedback training improved paretic ankle motor control with improvements in floor walking. Increased walking speeds were comparable with reports from other task-oriented, locomotor training approaches used in stroke, suggesting that a focus on ankle motor control may provide a valuable adjunct to locomotor therapies.

Measurement of Human Ankle Stiffness Using the Anklebot

In this paper we present initial results using a novel ankle robot to estimate human ankle stiffness. This lower-extremity robotic therapy module was developed at MIT to aid recovery of ankle function. Given the importance of the ankle during locomotion, an accurate estimate of ankle stiffness would be a valuable asset for locomotor rehabilitation, potentially providing a measure of recovery and a quantitative basis to design treatment protocols. We show that the ankle robot provides accurate measurement of ankle configuration and present a simple protocol to estimate ankle stiffness. Our initial ankle stiffness estimates compare favorably with previously published work, indicating that this method may serve as an efficient clinical measurement tool.

Measurement of passive ankle stiffness in subjects with chronic hemiparesis using a novel ankle robot

Our objective in this study was to assess passive mechanical stiffness in the ankle of chronic hemiparetic stroke survivors and to compare it with those of healthy young and older (age-matched) individuals. Given the importance of the ankle during locomotion, an accurate estimate of passive ankle stiffness would be valuable for locomotor rehabilitation, potentially providing a measure of recovery and a quantitative basis to design treatment protocols. Using a novel ankle robot, we characterized passive ankle stiffness both in sagittal and in frontal planes by applying perturbations to the ankle joint over the entire range of motion with subjects in a relaxed state. We found that passive stiffness of the affected ankle joint was significantly higher in chronic stroke survivors than in healthy adults of a similar cohort, both in the sagittal as well as frontal plane of movement, in three out of four directions tested with indistinguishable stiffness values in plantarflexion direction. Our findings are comparable to the literature, thus indicating its plausibility, and, to our knowledge, report for the first time passive stiffness in the frontal plane for persons with chronic stroke and older healthy adults.

Stabilizing PID Controllers for a Single-Link Biomechanical Model with Position, Velocity, and Force Feedback

In this paper we address the problem of PID stabilization of a single-link inverted pendulum-based biomechanical model with force feedback, two levels of position and velocity feedback, and with delays in all the feedback loops. The novelty of the proposed model lies in its physiological relevance, whereby both small and medium latency sensory feedbacks from muscle spindle (MS), and force feedback from Golgi tendon organ (GTO) are included in the formulation. The biomechanical model also includes active and passive viscoelastic feedback from Hill-type muscle model and a second-order low-pass function for muscle activation. The central nervous system (CNS) regulation of postural movement is represented by a proportional-integral-derivative (PID) controller. Padé approximation of delay terms is employed to arrive at an overall rational transfer function of the biomechanical model. The Hermite-Biehler theorem is then used to derive stability results, leading to the existence of stabilizing PID controllers. An algorithm for selection of stabilizing feedback gains is developed using the linear matrix inequality (LMI) approach.

PID controller tuning for the first-order-plus-dead-time process model via Hermite-Biehler theorem.

This paper discusses PID stabilization of a first-order-plus-dead-time (FOPDT) process model using the stability framework of the Hermite-Biehler theorem. The FOPDT model approximates many processes in the chemical and petroleum industries. Using a PID controller and first-order Padé approximation for the transport delay, the Hermite-Biehler theorem allows one to analytically study the stability of the closed-loop system. We derive necessary and sufficient conditions for stability and develop an algorithm for selection of stabilizing feedback gains. The results are given in terms of stability bounds that are functions of plant parameters. Sensitivity and disturbance rejection characteristics of the proposed PID controller are studied. The results are compared with established tuning methods such as Ziegler-Nichols, Cohen-Coon, and internal model control.

Increased reward in ankle robotics training enhances motor control and cortical efficiency in stroke

Robotics is rapidly emerging as a viable approach to enhance motor recovery after disabling stroke. Current principles of cognitive motor learning recognize a positive relationship between reward and motor learning. Yet no prior studies have established explicitly whether reward improves the rate or efficacy of robotics-assisted rehabilitation or produces neurophysiologic adaptations associated with motor learning. We conducted a 3 wk, 9-session clinical pilot with 10 people with chronic hemiparetic stroke, randomly assigned to train with an impedance-controlled ankle robot (anklebot) under either high reward (HR) or low reward conditions. The 1 h training sessions entailed playing a seated video game by moving the paretic ankle to hit moving onscreen targets with the anklebot only providing assistance as needed. Assessments included paretic ankle motor control, learning curves, electroencephalograpy (EEG) coherence and spectral power during unassisted trials, and gait function. While both groups exhibited changes in EEG, the HR group had faster learning curves (p = 0.05), smoother movements (p </= 0.05), reduced contralesional-frontoparietal coherence (p </= 0.05), and reduced left-temporal spectral power (p </= 0.05). Gait analyses revealed an increase in nonparetic step length (p = 0.05) in the HR group only. These results suggest that combining explicit rewards with novel anklebot training may accelerate motor learning for restoring mobility.

Clinical application of a modular ankle robot for stroke rehabilitation.

BACKGROUND Advances in our understanding of neuroplasticity and motor learning post-stroke are now being leveraged with the use of robotics technology to enhance physical rehabilitation strategies. Major advances have been made with upper extremity robotics, which have been tested for efficacy in multi-site trials across the subacute and chronic phases of stroke. In contrast, use of lower extremity robotics to promote locomotor re-learning has been more recent and presents unique challenges by virtue of the complex multi-segmental mechanics of gait. OBJECTIVES Here we review a programmatic effort to develop and apply the concept of joint-specific modular robotics to the paretic ankle as a means to improve underlying impairments in distal motor control that may have a significant impact on gait biomechanics and balance. METHODS An impedance controlled ankle robot module (anklebot) is described as a platform to test the idea that a modular approach can be used to modify training and measure the time profile of treatment response. RESULTS Pilot studies using seated visuomotor anklebot training with chronic patients are reviewed, along with results from initial efforts to evaluate the anklebots utility as a clinical tool for assessing intrinsic ankle stiffness. The review includes a brief discussion of future directions for using the seated anklebot training in the earliest phases of sub-acute therapy, and to incorporate neurophysiological measures of cerebro-cortical activity as a means to reveal underlying mechanistic processes of motor learning and brain plasticity associated with robotic training. CONCLUSIONS Finally we conclude with an initial control systems strategy for utilizing the anklebot as a gait training tool that includes integrating an Internal Model-based adaptive controller to both accommodate individual deficit severities and adapt to changes in patient performance.

A Novel Theoretical Framework for the Dynamic Stability Analysis, Movement Control, and Trajectory Generation in a Multisegment Biomechanical Model

We consider a simplified characterization of the postural control system that embraces two broad components: one representing the musculoskeletal dynamics in the sagittal plane and the other representing proprioceptive feedback and the central nervous system (CNS). Specifically, a planar four-segment neuromusculoskeletal model consisting of the ankle, knee, and hip degrees-of-freedom (DOFs) is described in this paper. The model includes important physiological constructs such as Hill-type muscle model, active and passive muscle stiffnesses, force feedback from the Golgi tendon organ, muscle length and rate feedback from the muscle spindle, and transmission latencies in the neural pathways. A proportional-integral-derivative (PID) controller for each individual DOF is assumed to represent the CNS analog in the modeling paradigm. Our main hypothesis states that all stabilizing PID controllers for such multisegment biomechanical models can be parametrized and analytically synthesized. Our analytical and simulation results show that the proposed representation adequately shapes a postural control that (a) possesses good disturbance rejection and trajectory tracking, (b) is robust against feedback latencies and torque perturbations, and (c) is flexible to embrace changes in the musculoskeletal parameters. We additionally present detailed sensitivity analysis to show that control under conditions of limited or no proprioceptive feedback results in (a) significant reduction in the stability margins, (b) substantial decrease in the available stabilizing parameter set, and (c) oscillatory movement trajectories. Overall, these results suggest that anatomical arrangement, active muscle stiffness, force feedback, and physiological latencies play a major role in shaping motor control processes in humans.

Anklebot-assisted locomotor training after stroke: A novel deficit-adjusted control approach

In this paper, we present an approach to using the impedance-controlled “anklebot” for task-oriented locomotor training after stroke. Our objective is to determine the feasibility of using the anklebot as a gait training tool by increasing the contribution of the paretic ankle in walking function. Underlying our training approach is a novel gait event-triggered, sub-task control algorithm that enables precise timing of robotic assistance to key functional deficits of hemiparetic gait, as well as sagittal-plane biomechanical models capable of predicting necessary levels of robotic support specific to the nature and severity of deficits. These features may facilitate customizability of assisted walking to individual gait deficit profiles. As with our previous studies, we employ an adaptive approach in that, training parameters are incrementally progressed towards those of more normal gait depending on subject performance and tolerance. Here, we present and validate the sub-event detection and sub-task control method, the biomechanical models for the swing and landing phases of gait, and as proof-of-concept, pilot data to demonstrate initial efficacy of the approach.