Jiping He

Design and Control of RUPERT: A Device for Robotic Upper Extremity Repetitive Therapy

The structural design, control system, and integrated biofeedback for a wearable exoskeletal robot for upper extremity stroke rehabilitation are presented. Assisted with clinical evaluation, designers, engineers, and scientists have built a device for robotic assisted upper extremity repetitive therapy (RUPERT). Intense, repetitive physical rehabilitation has been shown to be beneficial overcoming upper extremity deficits, but the therapy is labor intensive and expensive and difficult to evaluate quantitatively and objectively. The RUPERT is developed to provide a low cost, safe and easy-to-use, robotic-device to assist the patient and therapist to achieve more systematic therapy at home or in the clinic. The RUPERT has four actuated degrees-of-freedom driven by compliant and safe pneumatic muscles (PMs) on the shoulder, elbow, and wrist. They are programmed to actuate the device to extend the arm and move the arm in 3-D space. It is very important to note that gravity is not compensated and the daily tasks are practiced in a natural setting. Because the device is wearable and lightweight to increase portability, it can be worn standing or sitting providing therapy tasks that better mimic activities of daily living. The sensors feed back position and force information for quantitative evaluation of task performance. The device can also provide real-time, objective assessment of functional improvement. We have tested the device on stroke survivors performing two critical activities of daily living (ADL): reaching out and self feeding. The future improvement of the device involves increased degrees-of-freedom and interactive control to adapt to a users physical conditions.

Recent developments in biofeedback for neuromotor rehabilitation

The original use of biofeedback to train single muscle activity in static positions or movement unrelated to function did not correlate well to motor function improvements in patients with central nervous system injuries. The concept of task-oriented repetitive training suggests that biofeedback therapy should be delivered during functionally related dynamic movement to optimize motor function improvement. Current, advanced technologies facilitate the design of novel biofeedback systems that possess diverse parameters, advanced cue display, and sophisticated control systems for use in task-oriented biofeedback. In light of these advancements, this article: (1) reviews early biofeedback studies and their conclusions; (2) presents recent developments in biofeedback technologies and their applications to task-oriented biofeedback interventions; and (3) discusses considerations regarding the therapeutic system design and the clinical application of task-oriented biofeedback therapy. This review should provide a framework to further broaden the application of task-oriented biofeedback therapy in neuromotor rehabilitation.

Spinal cord stimulation facilitates functional walking in a chronic, incomplete spinal cord injured.

Design: This paper describes a treatment paradigm to facilitate functional gait in a quadriplegic, ASIA C spinal cord injured (SCI), wheelchair-dependent subject who presented with some large fiber sensation, sub-functional motor strength in all lower limb muscles, and moderate spasticity. The study utilizes partial weight bearing therapy (PWBT) followed by epidural spinal cord stimulation (ESCS) with the assumption that both treatments would be necessary to elicit a well organized, near effortless functional gait with a walker. Function is defined in terms of accomplishing task-specific activities in the home and community.Objectives: To demonstrate the feasibility and benefits of combined PWBT and ESCS therapies aimed at promoting functional gait in a wheelchair-dependent ASIA C SCI subject.Setting: The Clinical Neurobiology and Bioengineering Research Laboratories at Good Samaritan Regional Medical Center, Phoenix, Arizona, USA, and the Department of Bioengineering, Arizona State University, Tempe, Arizona, USA.Methods: The study began with the application of PWBT. The subject walked on the treadmill until a plateau in gait rhythm generation was reached. Subsequently, ESCS, applied to the lumbar enlargement, was utilized to facilitate PWBT and, later, over-ground walking for a standard distance of 15 m. Gait performance was analyzed by measuring average speed, stepping symmetry, sense of effort, physical work capacity, and whole body metabolic activity.Results: PWBT led to improved stereotypic stepping patterns associated with markedly reduced spasticity, but was insufficient for over-ground walking in terms of safety, energy cost, and fatigue. ESCS with PWBT generated immediate improvement in the subjects gait rhythm when appropriate stimulation parameters were used. When compared to the non-stimulated condition, over-ground walking with ESCS across a 15 m distance was featured by a reduction in time and energy cost of walking, sense of effort, and a feeling of ‘lightness’ in the legs. After a few months of training, performance in speed, endurance, and metabolic responses gradually converged with/without ESCS at this short distance, suggesting a learned response to these conditions. However, at longer distances (eg, 50–250 m), performance with ESCS was considerably superior. The subject was able to perform multiple functional tasks within the home and community with ESCS.Conclusion: We propose that ESCS augments the use-dependent plasticity created by PWBT and may be a valuable adjunct to post-SCI treadmill training in ASIA C subjects. We also conclude that ESCS elicits greater activation of an oxidative motor unit pool, thereby reducing the subjects sense of effort and energetic cost of walking.

Polyimide-based intracortical neural implant with improved structural stiffness

A novel structure for chronically implantable cortical electrodes using polyimide bio-polymer was devised, which provides both flexibility for micro-motion compliance between brain tissues and the skull and at the brain/implant interface and stiffness for better surgical handling. A 5–10 µm thick silicon backbone layer was attached to the tip of the electrode to enhance the structural stiffness. This stiff segment was then followed by a 1 mm flexible segment without a silicon backbone layer. The fabricated implants have tri-shanks with five recording sites (20 µm × 20 µm) and two vias of 40 µm × 40 µm on each shank. In vitro cytotoxicity tests of prototype implants revealed no adverse toxic effects on cells. Bench test impedance values were assessed, resulting in an average impedance value of ~2 MΩ at 1 KHz. For a 5 µm thick silicon backbone electrode, the stiffness of polyimide-based electrodes was increased ten times over that of electrodes without the silicon backbone layer. Furthermore, polyimide-based electrodes with 5 µm and 10 µm thick silicon backbone layer penetrated pia of rat brain without buckling that has been observed in implants without silicon reinforcement.

Selection and parameterization of cortical neurons for neuroprosthetic control

When designing neuroprosthetic interfaces for motor function, it is crucial to have a system that can extract reliable information from available neural signals and produce an output suitable for real life applications. Systems designed to date have relied on establishing a relationship between neural discharge patterns in motor cortical areas and limb movement, an approach not suitable for patients who require such implants but who are unable to provide proper motor behavior to initially tune the system. We describe here a method that allows rapid tuning of a population vector-based system for neural control without arm movements. We trained highly motivated primates to observe a 3D center-out task as the computer played it very slowly. Based on only 10-12 s of neuronal activity observed in M1 and PMd, we generated an initial mapping between neural activity and device motion that the animal could successfully use for neuroprosthetic control. Subsequent tunings of the parameters led to improvements in control, but the initial selection of neurons and estimated preferred direction for those cells remained stable throughout the remainder of the day. Using this system, we have observed that the contribution of individual neurons to the overall control of the system is very heterogeneous. We thus derived a novel measure of unit quality and an indexing scheme that allowed us to rate each neurons contribution to the overall control. In offline tests, we found that fewer than half of the units made positive contributions to the performance. We tested this experimentally by having the animals control the neuroprosthetic system using only the 20 best neurons. We found that performance in this case was better than when the entire set of available neurons was used. Based on these results, we believe that, with careful task design, it is feasible to parameterize control systems without any overt behaviors and that subsequent control system design will be enhanced with cautious unit selection. These improvements can lead to systems demanding lower bandwidth and computational power, and will pave the way for more feasible clinical systems.

RUPERT: An exoskeleton robot for assisting rehabilitation of arm functions

The design of a wearable upper extremity therapy robot RUPERT IVtrade (Robotic Upper Extremity Repetitive Trainer) device is presented. It is designed to assist in repetitive therapy tasks related to activities of daily living which has been advocated for being more effective for functional recovery. RUPERTtrade has five actuated degrees of freedom driven by compliant and safe pneumatic muscle actuators (PMA) assisting shoulder elevation, humeral external rotation, elbow extension, forearm supination and wrist/hand extension. The device is designed to extend the arm and move in a 3D space with no gravity compensation, which is a natural setting for practicing day-to-day activities. Because the device is wearable and lightweight, the device is very portable; it can be worn standing or sitting for performing therapy tasks that better mimic activities of daily living. A closed-loop controller combining a PID-based feedback controller and a iterative learning controller (ILC)-based feedforward controller is proposed for RUPERT for passive repetitive task training. This type of control aids in overcoming the highly nonlinear nature of the plant under control, and also helps in adapting easily to different subjects for performing different tasks. The system was tested on two able-bodied subjects to evaluate its performance.

Epidural spinal-cord stimulation facilitates recovery of functional walking following incomplete spinal-cord injury

We investigated a novel treatment paradigm for developing functional ambulation in wheelchair-dependent individuals with chronic, incomplete spinal-cord injury. By coordinating epidural stimulation of the dorsal structures of the spinal cord with partial weight bearing treadmill therapy, we observed improvement in treadmill and over-ground ambulation in an individual with chronic incomplete tetraplegia. The application of partial weight-bearing therapy alone was not sufficient to achieve functional ambulation over ground, though treadmill ambulation improved significantly. Combining epidural spinal-cord stimulation (ESCS, T/sub 10/-T/sub 12/ vertebral levels) with partial weight-bearing therapy resulted in further improvement during treadmill ambulation. Moreover, the combination of therapies facilitated the transfer of the learned gait into over ground ambulation. Performance improvements were elicited by applying continuous, charge-balanced, monophasic pulse trains at a frequency of 40-60 Hz, a pulse duration of 800 /spl mu/s, and an amplitude determined by the midpoint (50%) between the sensory and motor threshold values. The participant initially reported a reduction in sense of effort for over ground walking from 8/10 to 3/10 (Borg scale), and was able to double his walking speed. After several weeks of over ground training, he reached maximum walking speeds of 0.35 m/s, and was able to ambulate over 325 m. We propose that ESCS facilitated locomotor recovery in this patient by augmenting the use-dependent plasticity created by partial weight bearing therapy. Confirmation of these promising results in a controlled study of groups of spinal-cord-injured subjects is warranted.

Determining natural arm configuration along reaching trajectory

Owing to the flexibility and redundancy of neuromuscular and skeletal systems, humans can trace the same hand trajectory in space with various arm configurations. However, the joint trajectories of typical unrestrained movements tend to be consistent both within and across subjects. In this paper we propose a method to solve the 3-D inverse kinematics problem based on minimizing the magnitude of total work done by joint torques. We examined the fit of the joint-space trajectories against those observed from human performance in a variety of movement paths in 3-D workspace. The results showed that the joint-space trajectories produced by the method are in good agreement with the subjects’ arm movements (r2>0.98), with the exception of shoulder adduction/abduction (where, in the worst case, r2 ∼0.8). Comparison of humeral rotation predicted by our algorithm with other models showed that the correlation coefficient (r2) between actual data and our predictions is extremely high (mostly >0.98, 11 out of 15 cases, with a few exceptions, 4 of 15, in the range of 0.8–0.9) and the slope of linear regression is much closer to one (<0.05 distortion in 12 out of 15 cases, with only one case >0.15). However, the discrepancy in shoulder adduction/abduction indicated that when only the hand path is known, additional constraint(s) may be required to generate a complete match with human performance.

Closed-loop cortical control of direction using support vector machines

Motor neuroprosthetics research has focused on reproducing natural limb motions by correlating firing rates of cortical neurons to continuous movement parameters. We propose an alternative system where specific spatial-temporal spike patterns, emerging in tasks, allow detection of classes of behavior with the aid of sophisticated nonlinear classification algorithms. Specifically, we attempt to examine ensemble activity from motor cortical neurons, not to reproduce the action this neural activity normally precedes, but rather to predict an output supervisory command to potentially control a vehicle. To demonstrate the principle, this design approach was implemented in a discrete directional task taking a small number of motor cortical signals (8-10 single units) fed into a support vector machine (SVM) to produce the commands Left and Right. In this study, rats were placed in a conditioning chamber performing a binary paddle pressing task mimicking the control of a wheelchair turning left or right. Four animal subjects (male Sprague-Dawley rats) were able to use such a brain-machine interface (BMI) with an average accuracy of 78% on their first day of exposure. Additionally, one animal continued to use the interface for three consecutive days with an average accuracy over 90%.

Low-cost, at-home assessment system with Wii Remote based motion capture

We present an at-home assessment system for upper extremity rehabilitation with simple motion capture that is functional and affordable. This system uses lighted targets to initiate a reach to grasp (or touch, if the patient is unable to grasp) to three touch- and force-sensitive cones. During the reach, end-point reach trajectory is captured using a low-cost, custom-built infrared motion capture system using two Wii remotes. An embedded computer collects data for tracking patientpsilas progress over time. The system is a low cost way to track reaching trajectory, reaching time, reaction time and relative grasp forces. It requires minimal setup and instruction.