Neural correlates of bilateral proprioception and adaptation with training.

Bilateral proprioception includes the ability to sense the position and motion of one hand relative to the other, without looking. This sensory ability allows us to perform daily activities seamlessly, and its impairment is observed in various neurological disorders such as cerebral palsy and stroke. It can undergo experience-dependent plasticity, as seen in trained piano players. If its neural correlates were better understood, it would provide a useful assay and target for neurorehabilitation for people with impaired proprioception. We designed a non-invasive electroencephalography-based paradigm to assess the neural features relevant to proprioception, especially focusing on bilateral proprioception, i.e., assessing the limb distance from the body with the other limb. We compared it with a movement-only task, with and without the visibility of the target hand. Additionally, we explored proprioceptive accuracy during the tasks. We tested eleven Controls and nine Skilled musicians to assess whether sensorimotor event-related spectral perturbations in µ (8-12Hz) and low-ß (12-18Hz) rhythms differ in people with musical instrument training, which intrinsically involves a bilateral proprioceptive component, or when new sensor modalities are added to the task. The Skilled group showed significantly reduced µ and low-ß suppression in bilateral tasks compared to movement-only, a significative difference relative to Controls. This may be explained by reduced top-down control due to intensive training, despite this, proprioceptive errors were not smaller for this group. Target visibility significantly reduced proprioceptive error in Controls, while no change was observed in the Skilled group. During visual tasks, Controls exhibited significant µ and low-ß power reversals, with significant differences relative to proprioceptive-only tasks compared to the Skilled group-possibly due to reduced uncertainty and top-down control. These results provide support for sensorimotor µ and low-ß suppression as potential neuromarkers for assessing proprioceptive ability. The identification of these features is significant as they could be used to quantify altered proprioceptive neural processing in skill and movement disorders. This in turn can be useful as an assay for pre and post sensory-motor intervention research.

Comparison of Admittance Control Dynamic Models for Transparent Free-Motion Human-Robot Interaction.

This paper presents an experimental comparison of multiple admittance control dynamic models implemented on a five-degree-of-freedom arm exoskeleton. The performance of each model is evaluated for transparency, stability, and impact on point-to-point reaching. Although ideally admittance control would render a completely transparent environment for physical human-robot interaction (pHRI), in practice, there are trade-offs between transparency and stability-both of which can detrimentally impact natural arm movements. Here we test four admittance modes: 1) Low-Mass: low inertia with zero damping; 2) High-Mass: high inertia with zero damping; 3) Velocity-Damping: low inertia with damping; and 4) a novel Velocity-Error-Damping: low inertia with damping based on velocity error. A single subject completed two experiments: 1) 20 repetitions of a single reach-and-return, and 2) two repetitions of reach-and-return to 13 different targets. The results suggest that the proposed novel Velocity-Error-Damping model improves transparency the most, achieving a 70% average reduction of vibration power vs. Low-Mass, while also reducing user effort, with less impact on spatial/temporal accuracy than alternate modes. Results also indicate that different models have unique situational advantages so selecting between them may depend on the goals of the specific task (i.e., assessment, therapy, etc.). Future work should investigate merging approaches or transitioning between them in real-time.

Design and Development of a Spherical 5-Bar Thumb Exoskeleton Mechanism for Poststroke Rehabilitation.

This paper presents the kinematic design and development of a two degree-of-freedom (2DOF) spherical 5-bar thumb exoskeleton to augment the finger individuating grasp exercise robot (FINGER) rehabilitation robot, which assists the index and middle fingers individually in naturalistic grasping. The thumb module expands the capabilities of FINGER, allowing for broader proprioceptive training and assessment of hand function. The design process started by digitizing thumb-grasping motions to the index and the middle fingers separately, recorded from multiple healthy subjects utilizing a motion capture system. Fitting spheres to trajectory data of each subject allowed normalization of all subjects' data to a common center and radius. A two-revolute joint serial-chain mechanism was synthesized (intermediate optimization step) to reach the normalized trajectories. Next, the two resulting grasping trajectories were spatially sampled as targets for the 2DOF spherical 5-bar synthesis. Optimization of the spherical 5-bar included symmetry constraints and cost-function penalties for poor manipulability. The resulting exoskeleton assists both flexion/extension and abduction/adduction of the thumb enabling a wide range of motions. Consistent with FINGER, the parallel structure of the spherical 5-bar places the actuators at the base of the module, allowing for desirable characteristics, including high backdrivability, high controllable bandwidth, and low mechanical impedance. The mechanical design was developed from the kinematic solution, including an adjustable thumb cuff to accommodate different hand sizes. Fit and function of the device were tested on multiple subjects, including survivors of stroke. A proportional-derivative force controller with gravity and friction compensation was implemented to reduce resistance to motion during subject testing.

Literature review of stroke assessment for upper-extremity physical function via EEG, EMG, kinematic, and kinetic measurements and their reliability.

BACKGROUND: Significant clinician training is required to mitigate the subjective nature and achieve useful reliability between measurement occasions and therapists. Previous research supports that robotic instruments can improve quantitative biomechanical assessments of the upper limb, offering reliable and more sensitive measures. Furthermore, combining kinematic and kinetic measurements with electrophysiological measurements offers new insights to unlock targeted impairment-specific therapy. This review presents common methods for analyzing biomechanical and neuromuscular data by describing their validity and reporting their reliability measures. METHODS: This paper reviews literature (2000-2021) on sensor-based measures and metrics for upper-limb biomechanical and electrophysiological (neurological) assessment, which have been shown to correlate with clinical test outcomes for motor assessment. The search terms targeted robotic and passive devices developed for movement therapy. Journal and conference papers on stroke assessment metrics were selected using PRISMA guidelines. Intra-class correlation values of some of the metrics are recorded, along with model, type of agreement, and confidence intervals, when reported. RESULTS: A total of 60 articles are identified. The sensor-based metrics assess various aspects of movement performance, such as smoothness, spasticity, efficiency, planning, efficacy, accuracy, coordination, range of motion, and strength. Additional metrics assess abnormal activation patterns of cortical activity and interconnections between brain regions and muscle groups; aiming to characterize differences between the population who had a stroke and the healthy population. CONCLUSION: Range of motion, mean speed, mean distance, normal path length, spectral arc length, number of peaks, and task time metrics have all demonstrated good to excellent reliability, as well as provide a finer resolution compared to discrete clinical assessment tests. EEG power features for multiple frequency bands of interest, specifically the bands relating to slow and fast frequencies comparing affected and non-affected hemispheres, demonstrate good to excellent reliability for populations at various stages of stroke recovery. Further investigation is needed to evaluate the metrics missing reliability information. In the few studies combining biomechanical measures with neuroelectric signals, the multi-domain approaches demonstrated agreement with clinical assessments and provide further information during the relearning phase. Combining the reliable sensor-based metrics in the clinical assessment process will provide a more objective approach, relying less on therapist expertise. This paper suggests future work on analyzing the reliability of metrics to prevent biasedness and selecting the appropriate analysis.

3D Scanning of the Forearm for Orthosis and HMI Applications.

The rise of rehabilitation robotics has ignited a global investigation into the human machine interface (HMI) between device and user. Previous research on wearable robotics has primarily focused on robotic kinematics and controls but rarely on the actual design of the physical HMI (pHMI). This paper presents a data-driven statistical forearm surface model for designing a forearm orthosis in exoskeleton applications. The forearms of 6 subjects were 3D scanned in a custom-built jig to capture data in extreme pronation and supination poses, creating 3D point clouds of the forearm surface. Resulting data was characterized into a series of ellipses from 20 to 100% of the forearm length. Key ellipse parameters in the model include: normalized major and minor axis length, normalized center point location, tilt angle, and circularity ratio. Single-subject (SS) ellipse parameters were normalized with respect to forearm radiale-stylion (RS) length and circumference and then averaged over the 6 subjects. Averaged parameter profiles were fit with 3rd-order polynomials to create combined-subjects (CS) elliptical models of the forearm. CS models were created in the jig as-is (CS1) and after alignment to ellipse centers at 20 and 100% of the forearm length (CS2). Normalized curve fits of ellipse major and minor axes in model CS2 achieve R 2 values ranging from 0.898 to 0.980 indicating a high degree of correlation between cross-sectional size and position along the forearm. Most other parameters showed poor correlation with forearm position (0.005 < R 2 < 0.391) with the exception of tilt angle in pronation (0.877) and circularity in supination (0.657). Normalized RMSE of the CS2 ellipse-fit model ranged from 0.21 to 0.64% of forearm circumference and 0.22 to 0.46% of forearm length. The average and peak surface deviation between the scaled CS2 model and individual scans along the forearm varied from 0.56 to 2.86 mm (subject averages) and 3.86 to 7.16 (subject maximums), with the peak deviation occurring between 45 and 50% RS length. The developed equations allow reconstruction of a scalable 3D model that can be sized based on two user measures, RS length and forearm circumference, or based on generic arm measurements taken from existing anthropometric databases.

Energy Density and Hysteresis Comparison in Natural Rubber Tube Springs for Wearable Exoskeleton Applications.

Wearable exoskeletons show promise as a means for compensating lost function as well as for providing optimal assistance for maximal therapeutic benefit during everyday tasks. Development of lightweight spring systems for efficient storage and return are proposed as a key component in the successful deployment of wearable exoskeletons for individuals with neurological deficits. Both spring steel and natural rubber are common materials used in energy storage, but have not been directly compared by metrics such as energy storage density, energy storage efficiency, and hysteresis. In this work, we perform cyclic loading tests on spring steel extension springs of varying wire diameter and natural rubber tubing of varying wall thicknesses. We then use measured load-extension profiles to illustrate and compute metrics to better quantify the energy storing capabilities of each material and their appropriateness for use as energy storing and returning components in wearable robotic applications. Results show that natural rubber has a higher capacity for energy storage per unit weight in comparison to steel springs. Hysteresis is also higher in natural rubber and can be dramatically reduced by applying adequate pre-strain at levels greater than the anticipated strain during use.

Gravity Compensation of an Exoskeleton Joint Using Constant-Force Springs.

Stroke is one of the leading causes of impairment in the world. Many of those who have suffered a stroke experience long-term loss of upper-limb function as a result. BLUE SABINO is an exoskeleton device being developed at the University of Idaho to help assess these patients and aid in their rehabilitation. One of the central design challenges with exoskeletons is limiting the overall weight of the device. Motors used in actuation of these devices are often oversized to allow gravity balancing of the device and user and the creation of torques to facilitate patient movements. If the torques required for gravity balancing are achieved through elastic elements, the motor and other upstream components can be lighter, potentially greatly reducing the overall weight of the device. In this paper, constant-force springs may provide an effective method of generating a constant offsetting torque to compensate for gravity. In experimental testing of multiple mounting configurations of C-shaped constant-force springs (single, back-to-back, double-wrapped), the force output fluctuated less than 8.6% over 180° of wrapping, with friction values below 2.6%, validating the viability of constant-force springs for this application. The results suggest the back-to-back configuration provides a simpler implementation with better force consistency while the double-wrapped configuration adds less friction to the system.

Mapping ADL Motion Capture Data to BLUE SABINO Exoskeleton Kinematics and Dynamics.

Design of an upper-arm exoskeleton requires knowledge of human operational ranges and workspace distributions. Motion capture recordings of right-arm motion during common tasks, known as activities of daily living (ADLs), are taken to represent a plausible workspace for an exoskeleton. An inverse kinematic model of BLUE SABINO (BiLateral Upper-extremity Exoskeleton for Simultaneous Assessment of Biomechanical and Neuromuscular Output), driven by ADL data is established to map right-arm joint locations to exoskeleton motor joint space. A kinematic representation of a human right-arm driven by ADL data is implemented via a vector analysis utilizing quaternion rotation/translation and used to visualize ADL recordings. A model of the BLUE SABINO exoskeleton whose motion is driven by the mapped motorjoint-space data is used to validate the mapping graphically. The available ADL database is mapped to motor joint space. Motor position distributions are generated from the resulting dataset and estimates of robot range of motion, (ROM) and statistics for shoulder motor positions are established. A kinematically and inertially accurate model of the BLUE SABINO is developed by exporting SolidWorksOR part models into SimScape Multibody (MathWorks). The model is used to produce operational torque estimates for shoulder motors. Initial simulations indicate that the motors of interest have been properly sized.

Design parameters and torque profile modification of a spring-assisted hand-opening exoskeleton module.

There is a growing demand for functional rehabilitation orthotics that can effectively assist in patient recovery from motor impairments after stroke. The hand in particular is a complex system that has proven difficult to mimic with current exoskeleton technologies. This paper presents data-driven design parameters to increase the functionality and improve the assistance profile of the ArmAssist-2.0 hand module. Improvements from the previous model include adjustable linkages to fulfill the largest population of users, new joint locations to more accurately represent biomechanics of the hand, and a more impairment-appropriate torque profile to assist in hand opening, adjustable through interchangeable springs. In most passive hand orthoses, assistance forces tend to decrease as the hand and thumb extend, opposite the needs of a typical patient hand. This project utilizes a variable spring moment arm about the revolute axes to match common patient impairment more accurately. The revised assistance profile for the hand maintains a nearly linear relationship. Results conclude that the final assembled device fits comfortably in the hand with noticeable improvements in joint locations, adjustability, and the force profile for the metacarpophalangeal (MCP) joint. An issue arises with the extension of the proximal interphalangeal (PIP) joint due to the nature of rapidly changing moment arms and multiple springs in series. The issue and possible solutions are discussed.

Development of a series wrapping cam mechanism for energy transfer in wearable arm support applications.

An estimated 17 million individuals suffer a stroke each year with over 5 million resulting in permanent disability. For many of these, the provision of gravity support to the impaired upper limb can provide significant and immediate improvement in arm mobility. This added mobility has the potential to improve arm function and user independence overall, but, so far, wearable arm supports have found only limited uptake by end-users. The reasons are unclear, but it is hypothesized that device uptake is strongly affected by aspects of arm support implementation such as added weight and volume and the effectiveness of the support provided. In the interest of reducing the size and visibility of wearable arm supports, cable driven actuation was investigated, and a device called the series wrapping cam was developed. This device uses two wrapping cams to stretch a spring as the user's arm elevation decreases. It optimally uses the range of motion of a custom latex spring in a compact mechanism. A one degree-of-freedom proof-of-concept prototype of the series wrapping cam was manufactured and tested. The torque supplied by the prototype correctly responds to shoulder elevation to balance the weight of the extended arm at any level of elevation. However, the support is unaffected by the degree of elbow flexion-extension. Shoulder joint torque is a function of both shoulder elevation and elbow flexion, suggesting further benefits could be achieved through a bi-articular design.

Design of a thumb module for the FINGER rehabilitation robot.

This paper describes the design and initial prototype of a thumb curling exoskeleton for movement therapy. This add-on device for the Finger INdividuating Grasp Exercise Robot (FINGER) guides the thumb through a single-degree-of-freedom naturalistic grasping motion. This motion complements the grasping motions of the index and middle fingers provided by FINGER. The kinematic design and mechanism synthesis described herein utilized 3D motion capture and included the determination of the principle plane of the thumb motion for the simple grasping movement. The results of the design process and the creation of a first prototype indicate that this thumb module for finger allows naturalistic thumb motion that expands the capabilities of the FINGER device.

Design of a spring-assisted exoskeleton module for wrist and hand rehabilitation.

This paper reports on the development of a low-profile exoskeleton module to enable training of the fingers and thumb in grasp and release tasks. The design has been made as an add-on module for use with the ArmAssist arm rehabilitation system (Tecnalia, Spain). Variable-position springs and adjustable link lengths provide adaptability to fit a variety of users. Additive manufacturing has been utilized for the majority of components allowing easy modifications. A few structural components were machined from aluminum or steel to produce a functional prototype with sufficient strength for direct evaluation. The design includes independent and adjustable assistance in finger and thumb extension using various width elastic bands, and measurement of user grasp/release forces in finger flexion/extension, thumb flexion/extension, and thumb adduction/abduction using low-profile force sensitive resistors.

Design and optimization of PARTNER: a parallel actuated robotic trainer for NEuroRehabilitation.

Robotic devices are a promising and dynamic tool in the realm of post-stroke rehabilitation. Researchers are still investigating how the use of robots affects motor learning and what design characteristics best encourage recovery. We present a parallel-actuated, end-effector robot designed to provide spatial assistance for upper-limb therapy while exhibiting low impedance and high backdrivability. A gradient based optimization was performed to find an optimal design that accounted for force isotropy, mechanical advantage, workspace size, and counter-balancing. A beta prototype has been built to these specifications (low impedance and high backdrivability) and has undergone initial controller performance as well as fit and function testing. By fitting a nonlinear model to experimental frequency response data, the apparent mass, viscous friction coefficient, and dynamic dry friction coefficient were determined to be 0.242 kg, 0.114 Ns/m, and 0.894 N respectively. The robot will serve as a testing platform to investigate motor learning and evaluate the efficacy of control schemes for post-stroke movement therapy.

Improving the match between ability and challenge: toward a framework for automatic level adaptation in game-based assessment and training.

It is believed that the quality of arm mobility in planar reach movements can be adequately characterized by measures of planar position and vertical force. For the purpose of impairment assessment, it is further proposed that a complete picture of mobility performance can be represented through the assessment of metrics representative of each of four capacities: 1) Range of motion, 2) Range of force, 3) Control of motion, and 4) Control of force. In this paper, a set of games for mobility assessment is presented and initial plots of motion profiles and several computed metrics are shown for one patient in the performance of range of motion and control of motion assessments. Assessment plots are shown for four of seven training sessions and metrics are computed at each of the seven sessions to show the progression over the course of the 2-week clinical pilot study with the ArmAssist.

Development of a powered mobile module for the ArmAssist home-based telerehabilitation platform.

The ArmAssist, developed by Tecnalia, is a system for at-home telerehabilitation of post-stroke arm impairments. It consists of a wireless mobile base module, a global position and orientation detection mat, a PC with display monitor, and a tele-rehabilitation software platform. This paper presents the recent development results on the mobile module augmenting its functionality by adding actuation components. Three DC servo motors were employed to drive the mobile module and a position control algorithm based on the kinematic model and velocity mode control was implemented such that the module tracks a path defined in the training software. Pilot tests of the powered mobile module were performed in experiments with different load conditions and two unimpaired subjects. Both test results show that the module is able to follow the predefined path within an acceptable error range for reach movement training. Further study and testing of the system in realistic conditions following stroke will be a future topic of research.

Development of computer games for assessment and training in post-stroke arm telerehabilitation.

Stroke is the leading cause of long term disability among adults in industrialized nations. The majority of these disabilities include deficiencies in arm function, which can make independent living very difficult. Research shows that better results in rehabilitation are obtained when patients receive more intensive therapy. However this intensive therapy is currently too expensive to be provided by the public health system, and at home few patients perform the repetitive exercises recommended by their therapists. Computer games can provide an affordable, enjoyable, and effective way to intensify treatment, while keeping the patient as well as their therapists informed about their progress. This paper presents the study, design, implementation and user-testing of a set of computer games for at-home assessment and training of upper-limb motor impairment after stroke.

Variable structure pantograph mechanism with spring suspension system for comprehensive upper-limb haptic movement training.

Numerous haptic devices have been developed for upper-limb neurorehabilitation, but their widespread use has been largely impeded because of complexity and cost. Here, we describe a variable structure pantograph mechanism combined with a spring suspension system that produces a versatile rehabilitation robot, called Universal Haptic Pantograph, for movement training of the shoulder, elbow, and wrist. The variable structure is a 5-degree-of-freedom (DOF) mechanism composed of 7 joints, 11 joint axes, and 3 configurable joint locks that reduce the number of system DOFs to between 0 and 3. The resulting device has eight operational modes: Arm, Wrist, ISO (isometric) 1, ISO 2, Reach, Lift 1, Lift 2, and Steer. The combination of available work spaces (reachable areas) shows a high suitability for movement training of most upper-limb activities of daily living. The mechanism, driven by series elastic actuators, performs similarly in all operational modes, with a single control scheme and set of gains. Thus, a single device with minimal setup changes can be used to treat a variety of upper-limb impairments that commonly afflict veterans with stroke, traumatic brain injury, or other direct trauma to the arm. With appropriately selected design parameters, the developed multimode haptic device significantly reduces the costs of robotic hardware for full-arm rehabilitation while performing similarly to that of single-mode haptic devices. We conducted case studies with three patients with stroke who underwent clinical training using the developed mechanism in Arm, Wrist, and/or Reach operational modes. We assessed outcomes using Fugl-Meyer Motor Assessment and Wolf Motor Function Test scores showing that upper-limb ability improved significantly following training sessions.

Telerehabilitation: toward a cost-efficient platform for post-stroke neurorehabilitation.

Motor deficits in the growing population of stroke survivors continue to strain global healthcare capacities. The use of telerehabilitation to address this need has been discussed for over a decade without a clear consensus on development strategy or a clear market success. In this paper, the cyclic and iterative phases of the Planning, Execution, Assessment (PLEXAS) rehabilitation cycle are discussed, and the potential roles of an integrated telerehabilitation platform within this cycle are presented. Some preliminary work on a multicenter project called TeleREHA is presented along with relevant clinical insight and discussion.

A variable structure pantograph mechanism for comprehensive upper extremity haptic movement training.

Numerous haptic devices have been developed for neurorehabilitation of upper extremities, but their wide-spread use has been largely impeded for reasons of complexity and cost. In this paper we describe a variable structure pantograph mechanism that produces a versatile rehabilitation robot for movement training of the shoulder, elbow, and wrist. The device has three operational modes: ARM, REACH and WRIST. The performance of the mechanism, driven by series elastic actuators, is similar in all three operational modes while using a single control scheme and set of gains. This means a single device with minimal setup changes can be used to treat a variety of upper limb impairments following stroke, traumatic brain injury, or other direct trauma to the arm.

Real-time myoprocessors for a neural controlled powered exoskeleton arm.

Exoskeleton robots are promising assistive/rehabilitative devices that can help people with force deficits or allow the recovery of patients who have suffered from pathologies such as stroke. The key component that allows the user to control the exoskeleton is the human machine interface (HMI). Setting the HMI at the neuro-muscular level may lead to seamless integration and intuitive control of the exoskeleton arm as a natural extension of the human body. At the core of the exoskeleton HMI there is a model of the human muscle, the "myoprocessor," running in real-time and in parallel to the physiological muscle, that predicts joint torques as a function of the joint kinematics and neural activation levels. This paper presents the development of myoprocessors for the upper limb based on the Hill phenomenological muscle model. Genetic algorithms are used to optimize the internal parameters of the myoprocessors utilizing an experimental database that provides inputs to the model and allows for performance assessment. The results indicate high correlation between joint moment predictions of the model and the measured data. Consequently, the myoprocessor seems an adequate model, sufficiently robust for further integration into the exoskeleton control system.