Marcia K. O'Malley

Design of a haptic arm exoskeleton for training and rehabilitation

A high-quality haptic interface is typically characterized by low apparent inertia and damping, high structural stiffness, minimal backlash, and absence of mechanical singularities in the workspace. In addition to these specifications, exoskeleton haptic interface design involves consideration of space and weight limitations, workspace requirements, and the kinematic constraints placed on the device by the human arm. These constraints impose conflicting design requirements on the engineer attempting to design an arm exoskeleton. In this paper, the authors present a detailed review of the requirements and constraints that are involved in the design of a high-quality haptic arm exoskeleton. In this context, the design of a five-degree-of-freedom haptic arm exoskeleton for training and rehabilitation in virtual environments is presented. The device is capable of providing kinesthetic feedback to the joints of the lower arm and wrist of the operator, and will be used in future work for robot-assisted rehabilitation and training. Motivation for such applications is based on findings that show robot-assisted physical therapy aids in the rehabilitation process following neurological injuries. As a training tool, the device provides a means to implement flexible, repeatable, and safe training methodologies.

Design, Control and Performance of RiceWrist: A Force Feedback Wrist Exoskeleton for Rehabilitation and Training

This paper presents the design, control and performance of a high fidelity four degree-of-freedom wrist exoskeleton robot, RiceWrist, for training and rehabilitation. The RiceWrist is intended to provide kinesthetic feedback during the training of motor skills or rehabilitation of reaching movements. Motivation for such applications is based on findings that show robot-assisted physical therapy aids in the rehabilitation process following neurological injuries. The exoskeleton device accommodates forearm supination and pronation, wrist flexion and extension and radial and ulnar deviation in a compact parallel mechanism design with low friction, zero backlash and high stiffness. As compared to other exoskeleton devices, the RiceWrist allows easy measurement of human joint angles and independent kinesthetic feedback to individual human joints. In this paper, joint-space as well as task-space position controllers and an impedance-based force controller for the device are presented. The kinematic performance of the device is characterized in terms of its workspace, singularities, manipulability, backlash and backdrivability. The dynamic performance of RiceWrist is characterized in terms of motor torque output, joint friction, step responses, behavior under closed loop set-point and trajectory tracking control and display of virtual walls. The device is singularity-free, encompasses most of the natural workspace of the human joints and exhibits low friction, zero-backlash and high manipulability, which are kinematic properties that characterize a high-quality impedance display device. In addition, the device displays fast, accurate response under position control that matches human actuation bandwidth and the capability to display sufficiently hard contact with little coupling between controlled degrees-of-freedom.

Normalized Movement Quality Measures for Therapeutic Robots Strongly Correlate With Clinical Motor Impairment Measures

In this paper, we analyze the correlations between four clinical measures (Fugl-Meyer upper extremity scale, Motor Activity Log, Action Research Arm Test, and Jebsen-Taylor Hand Function Test) and four robotic measures (smoothness of movement, trajectory error, average number of target hits per minute, and mean tangential speed), used to assess motor recovery. Data were gathered as part of a hybrid robotic and traditional upper extremity rehabilitation program for nine stroke patients. Smoothness of movement and trajectory error, temporally and spatially normalized measures of movement quality defined for point-to-point movements, were found to have significant moderate to strong correlations with all four of the clinical measures. The strong correlations suggest that smoothness of movement and trajectory error may be used to compare outcomes of different rehabilitation protocols and devices effectively, provide improved resolution for tracking patient progress compared to only pre- and post-treatment measurements, enable accurate adaptation of therapy based on patient progress, and deliver immediate and useful feedback to the patient and therapist.

Progressive shared control for training in virtual environments

Virtual environments (VEs) with haptic feedback not only provide a safe and versatile practice medium for many manual control tasks, but also promise to improve the efficacy of manual skill training with the addition of haptic guidance. However, haptic guidance schemes such as shared control may be detrimental since such schemes actively interfere with the coupled system dynamics, thereby causing participants to experience task dynamics that are altered from those of the real task. Therefore, this paper proposes a progressive approach to guidance for training in virtual environments. This progressive guidance scheme adjusts its control gains based on participant performance, aiming to expose the performer to an appropriate amount of haptic guidance throughout training. Long term training experiments were conducted for an under-actuated target-hitting manual control task. The experimental results compare the efficacy of the novel progressive haptic guidance to two common fixed-gain haptic guidance schemes and virtual practice. The results from a month-long training experiment indicate that the proposed progressive shared control scheme reduces guidance interference as compared to fixed-gain guidance schemes thus increasing training efficacy.

The effect of force saturation on the haptic perception of detail

This paper presents a quantitative study of the effects of maximum capable force magnitude of a haptic interface on the haptic perception of detail. Specifically, the haptic perception of detail is characterized by identification, detection, and discrimination of round and square cross-section ridges, in addition to corner detection tests. Test results indicate that performance, measured as a percent correct score in the perception experiments, improves in a nonlinear fashion as the maximum allowable level of force in the simulation increases. Further, all test subjects appeared to reach a limit in their perception capabilities at maximum-force output levels of 3-4 N, while the hardware was capable of 10 N of maximum continuous force output. These results indicate that haptic interface hardware may be able to convey sufficient perceptual information to the user with relatively low levels of force feedback. The data is compiled to aid those who wish to design a stylus-type haptic interface to meet certain requirements for the display of physical detail within a haptic simulation.

Negative efficacy of fixed gain error reducing shared control for training in virtual environments

Virtual reality with haptic feedback provides a safe and versatile practice medium for many manual control tasks. Haptic guidance has been shown to improve performance of manual control tasks in virtual environments; however, the efficacy of haptic guidance for training in virtual environments has not been studied conclusively. This article presents experimental results that show negative efficacy of haptic guidance during training in virtual environments. The haptic guidance in this study is a fixed-gain error-reducing shared controller, with the control effort overlaid on the dynamics of the manual control task during training. Performance of the target-hitting manual control task in the absence of guidance is compared for three training protocols. One protocol contained no haptic guidance and represented virtual practice. Two protocols utilized haptic guidance, varying the duration of exposure to guidance during the training sessions. Exposure to the fixed-gain error-reducing shared controller had a detrimental effect on performance of the target-hitting task at the conclusion of a month-long training protocol, regardless of duration of exposure. While the shared controller was designed with knowledge of the task and an intuitive sense of the motions required to achieve good performance, the results indicate that the acquisition of motor skill is a complex phenomenon that is not aided with haptic guidance during training as implemented in this experiment.

Mathematical equations as executable models of mechanical systems

Cyber-physical systems comprise digital components that directly interact with a physical environment. Specifying the behavior desired of such systems requires analytical modeling of physical phenomena. Similarly, testing them requires simulation of continuous systems. While numerous tools support later stages of developing simulation codes, there is still a large gap between analytical modeling and building running simulators. This gap significantly impedes the ability of scientists and engineers to develop novel cyber-physical systems. We propose bridging this gap by automating the mapping from analytical models to simulation codes. Focusing on mechanical systems as an important class of physical systems, we study the form of analytical models that arise in this domain, along with the process by which domain experts map them to executable codes. We show that the key steps needed to automate this mapping are 1) a light-weight analysis to partially direct equations, 2) a binding-time analysis, and 3) symbolic differentiation. In addition to producing a prototype modeling environment, we highlight some limitations in the state of the art in tool support of simulation, and suggest ways in which some of these limitations could be overcome.

ROBOTIC TRAINING AND ClINICAl ASSESSMENT OF UPPER ExTREMITy MOvEMENTS AFTER SPINAl CORD INJURy: A SINGlE CASE REPORT

CASE REPORT A 28-year-old woman, with incomplete spinal cord injury at the C2 level, classified as American Spinal Injury Impairment Scale C (AIS), participated in a robotic rehabilitation program 29 months after injury. Robotic training was provided to both upper extremities using the MAHI Exo-II, an exoskeleton device designed for rehabilitation of the upper limb, for 12 × 3-h sessions over 4 weeks. Training involved elbow flexion/extension, forearm supination/pronation, wrist flexion/extension, and radial/ulnar deviation. RESULTS Outcome measures were Action Research Arm Test, Jebsen-Taylor Hand Function Test, and AIS-upper extremity motor score. Safety measures included fatigue, pain and discomfort level using a 5-point rating scale. Following training, improvements were observed in the left arm and hand function, whereas the right arm and hand function showed no improvement in any of the functional outcome measures. No excessive pain, discomfort or fatigue was reported. CONCLUSION Data from one subject demonstrate valuable information on the feasibility, safety and effectiveness of robotic-assisted training of upper-extremity motor functions after incomplete spinal cord injury.

The Task-Dependent Efficacy of Shared-Control Haptic Guidance Paradigms

Shared-control haptic guidance is a common form of robot-mediated training used to teach novice subjects to perform dynamic tasks. Shared-control guidance is distinct from more traditional guidance controllers, such as virtual fixtures, in that it provides novices with real-time visual and haptic feedback from a real or virtual expert. Previous studies have shown varying levels of training efficacy using shared-control guidance paradigms; it is hypothesized that these mixed results are due to interactions between specific guidance implementations (“paradigms”) and tasks. This work proposes a novel guidance paradigm taxonomy intended to help classify and compare the multitude of implementations in the literature, as well as a revised proxy rendering model to allow for the implementation of more complex guidance paradigms. The efficacies of four common paradigms are compared in a controlled study with 50 healthy subjects and two dynamic tasks. The results show that guidance paradigms must be matched to a tasks dynamic characteristics to elicit effective training and low workload. Based on these results, we provide suggestions for the future development of improved haptic guidance paradigms.

Mechanical design of a distal arm exoskeleton for stroke and spinal cord injury rehabilitation

Robotic rehabilitation has gained significant traction in recent years, due to the clinical demonstration of its efficacy in restoring function for upper extremity movements and locomotor skills, demonstrated primarily in stroke populations. In this paper, we present the design of MAHI Exo II, a robotic exoskeleton for the rehabilitation of upper extremity after stroke, spinal cord injury, or other brain injuries. The five degree-of-freedom robot enables elbow flexion-extension, forearm pronation-supination, wrist flexion-extension, and radial-ulnar deviation. The device offers several significant design improvements compared to its predecessor, MAHI Exo I. Specifically, issues with backlash and singularities in the wrist mechanism have been resolved, torque output has been increased in the forearm and elbow joints, a passive degree of freedom has been added to allow shoulder abduction thereby improving alignment especially for users who are wheelchair-bound, and the hardware now enables simplified and fast swapping of treatment side. These modifications are discussed in the paper, and results for the range of motion and maximum torque output capabilities of the new design and its predecessor are presented. The efficacy of the MAHI Exo II will soon be validated in a series of clinical evaluations with both stroke and spinal cord injury patients.