RiceWrist Robotic Device for Upper Limb Training: Feasibility Study and Case Report of Two Tetraplegic Persons with Spinal Cord Injury

Regaining upper extremity function is the primary concern of persons with tetraplegia caused by spinal cord injury (SCI). Robotic rehabilitation has been inadequately tested and underutilized in rehabilitation of the upper extremity in the SCI population. Given the acceptance of robotic training in stroke rehabilitation and SCI gait training, coupled with recent evidence that the spinal cord, like the brain, demonstrates plasticity that can be enhanced by repetitive movement training such as that available with robotic devices, it is probable that robotic upper extremity training of persons with SCI could be clinically beneficial. The primary goal of this pilot study was to test the feasibility of using a novel robotic device –the RiceWrist Exoskeleton- for rehabilitation of the upper limbs (UL) of two tetraplegic persons with incomplete SCI. Two pilot experiments were conducted. Experiment 1was the first novel attempt to administer treatment with the RiceWrist. The left UL of a tetraplegic subject was treated during seven therapy sessions. The subject’s feedback and the investigator’s obser-vations were used to enhance the robotic device and the corresponding graphical-interface. In Experiment 2, a second tetra-plegic subject underwent 10 three-hour training sessions administered by a physical therapist. Smoothness factor (FS) –a new measure developed in Experiment 1- was used as the primary outcome to test the subject’s performance before and after the training. The RiceWrist was modified according to the feedback obtained in Experiment 1. Thereafter, the device was suc-cessfully administered for upper limb training of the tetraplegic individual. Noticeable improvements in FS were observed for the stronger arm of the subject who completed 10 sessions of training. Improvements were also observed in the subject’s hand according to the Jebsen-Taylor Hand Function Test. Results from this study suggest a potential application of the RiceWrist for rehabilitation of SCI individuals and offer valuable information regarding development of UL robotic devices for this population

Design, Characterization, and Validation of the OpenWrist Exoskeleton

Robotic devices have been clinically verified for use in long duration and high intensity rehabilitation needed for motor recovery after neurological injury. Targeted and coordinated hand and wrist therapy, often overlooked in rehabilitation robotics, is required to regain the ability to perform activities of daily living. To this end, a new coupled hand-wrist exoskeleton has been designed. This thesis details the design of the wrist module and several human-related considerations made to maximize its potential as a coordinated hand-wrist device. The serial wrist mechanism has been engineered to facilitate donning and doffing for impaired subjects and to insure compatibility with the hand module in virtual and assisted grasping tasks. Several other practical requirements have also been addressed, including device ergonomics, clinician-friendliness, and ambidextrous reconfigurability. The wrist module's capabilities as a rehabilitation training device are quantified experimentally in terms of functional workspace and dynamic properties. Finally, the device is validated as an rehabilitation assessment tool by considering its impact on commonly used assessment metrics. The presented wrist module's performance and operational considerations support its use in a wide range of future clinical investigations

Reviewing high-level control techniques on robot-assisted upper-limb rehabilitation

This paper presents a comprehensive review of high-level control techniques for upper-limb robotic training. It aims to compare and discuss the potentials of these different control algorithms, and specify future research direction. Included studies mainly come from selected papers in four review articles. To make selected studies complete and comprehensive, especially some recently-developed upper-limb robotic devices, a search was further conducted in IEEE Xplore, Google Scholar, Scopus and Web of Science using keywords (‘upper limb*’ or ‘upper body*’) and (‘rehabilitation*’ or ‘treatment*’) and (‘robot*’ or ‘device*’ or ‘exoskeleton*’). The search is limited to English-language articles published between January 2013 and December 2017. Valuable references in related publications were also screened. Comparative analysis shows that high-level interaction control strategies can be implemented in a range of methods, mainly including impedance/admittance based strategies, adaptive control techniques, and physiological signal control. Even though the potentials of existing interactive control strategies have been demonstrated, it is hard to identify the one leading to maximum encouragement from human users. However, it is reasonable to suggest that future studies should combine different control strategies to be application specific, and deliver appropriate robotic assistance based on physical disability levels of human users

EMG-Based Continuous and Simultaneous Estimation of Arm Kinematics in Able-Bodied Individuals and Stroke Survivors

Among the potential biological signals for human-machine interactions (brain, nerve, and muscle signals), electromyography (EMG) widely used in clinical setting can be obtained non-invasively as motor commands to control movements. The aim of this study was to develop a model for continuous and simultaneous decoding of multi-joint dynamic arm movements based on multi-channel surface EMG signals crossing the joints, leading to application of myoelectrically controlled exoskeleton robots for upper-limb rehabilitation. Twenty subjects were recruited for this study including 10 stroke subjects and 10 able-bodied subjects. The subjects performed free arm reaching movements in the horizontal plane with an exoskeleton robot. The shoulder, elbow and wrist movements and surface EMG signals from six muscles crossing the three joints were recorded. A non-linear autoregressive exogenous (NARX) model was developed to continuously decode the shoulder, elbow and wrist movements based solely on the EMG signals. The shoulder, elbow and wrist movements were decoded accurately based only on the EMG inputs in all the subjects, with the variance accounted for (VAF) > 98% for all three joints. The proposed approach is capable of simultaneously and continuously decoding multi-joint movements of the human arm by taking into account the non-linear mappings between the muscle EMGs and joint movements, which may provide less effortful control of robotic exoskeletons for rehabilitation training of individuals with neurological disorders and arm impairment

Hybrid FES-exoskeleton control: Using MPC to distribute actuation for elbow and wrist movements

IntroductionIndividuals who have suffered a cervical spinal cord injury prioritize the recovery of upper limb function for completing activities of daily living. Hybrid FES-exoskeleton systems have the potential to assist this population by providing a portable, powered, and wearable device; however, realization of this combination of technologies has been challenging. In particular, it has been difficult to show generalizability across motions, and to define optimal distribution of actuation, given the complex nature of the combined dynamic system.MethodsIn this paper, we present a hybrid controller using a model predictive control (MPC) formulation that combines the actuation of both an exoskeleton and an FES system. The MPC cost function is designed to distribute actuation on a single degree of freedom to favor FES control effort, reducing exoskeleton power consumption, while ensuring smooth movements along different trajectories. Our controller was tested with nine able-bodied participants using FES surface stimulation paired with an upper limb powered exoskeleton. The hybrid controller was compared to an exoskeleton alone controller, and we measured trajectory error and torque while moving the participant through two elbow flexion/extension trajectories, and separately through two wrist flexion/extension trajectories.ResultsThe MPC-based hybrid controller showed a reduction in sum of squared torques by an average of 48.7 and 57.9% on the elbow flexion/extension and wrist flexion/extension joints respectively, with only small differences in tracking accuracy compared to the exoskeleton alone.DiscussionTo realize practical implementation of hybrid FES-exoskeleton systems, the control strategy requires translation to multi-DOF movements, achieving more consistent improvement across participants, and balancing control to more fully leverage the muscles' capabilities

Virtual reality and exercises for paretic upper limb of stroke survivors

U ovom se radu razmatraju pitanja biološke povratne sprege u virtualnoj stvarnosti (VR - virtual reality). Taj modul VR kod robota ELISE omogućuje rekonstrukciju oštećenih motoričkih veza u mozgu, koje se mogu aktivirati posredstvom zrcalnih neurona ili motoričkih predodžbi o nekom pojmu. Robot ELISE doprinosi bržem oporavku nakon raznovrsnih neuroloških poremećaja, a naročito posljedica moždanog udara. Detaljno se opisuju četiri igre iz niza manipulacijsko-edukacijsko-socijalnih igara. U radu su predstavljene najvažnije tehničke karakteristike projekta, posebno dizajn, modul VR, modul gumenog dodatka za rehabilitaciju spastične ruke te detalji sustava hardware/software. Uz to se uvodi aspekt psihološke rehabilitacije kroz inovativnu virtualnu pomoć fizioterapeuta. Tijekom prvih testova predstavljena je funkcionalnost mehatroničkog uređaja za rehabilitaciju šake, podlaktice i ruke, a preliminarna procjena uporabljivosti i prihvaćanja obećavajuća je.The article presents the issues of biofeedback in virtual reality (VR). This VR module in ELISE robot gives a possible re-arrangement of the damaged motor cortex which can be activated with the mediation of mirror neurons or through the subject’s motor imagery. This ELISE robot will help to accelerate the recovery from various kinds of neurological disorders, especially from the effects of stroke. Four physical/education games in virtual reality are described in more detail. This paper presents the main technical characteristics of the project, especially design, VR module, rubber expander module for the spastic hand rehabilitation and the details of the hardware/software system. Moreover, psychological rehabilitation aspect is introduced through an innovative virtual assistant of physiotherapist. The functionality of the mechatronic device for hand, forearm and arm rehabilitation has been presented during the first tests, and preliminary assessment of usability and acceptance is promising

Development and Control of a 3-DoF Exoskeleton Robot for Forearm and Wrist Rehabilitation

The research conducted under this project directly contributes to the development of a forearm and wrist rehabilitation robot (UWM-FWRR). Upper extremity impairment following stroke, trauma, sports injuries, occupational injuries, spinal cord injuries, and orthopaedic injuries results in significant deficits in hand manipulation and the performance of everyday tasks. Strokes affect nearly 800,000 people in the United States each year. Rehabilitation programs are the main method of promoting functional recovery in individuals with finger impairment. The conventional therapeutic approach requiring a long commitment by both the clinician and the patient. Robotic devices (RDs) are novel and rapidly expanding technologies in hand rehabilitation. However, existing RDs have not been able to fully restore hand functionality as they cannot provide the independent joint control and levels of velocity and torque required. Our customer discovery [1] reveals that therapists often prescribe therapeutic devices for passive arm/leg movement assistance but no therapeutic devices exist for combined hand, wrist, and forearm movements that can be used at home/clinic. Regaining hand strength and mobility plays an important role in supporting essential activities of daily living, such as eating, and thus has the potential to improve the physical and mental status of both stroke patients and their family caregivers. Therefore, through this research author has develop UWM-FWRR that can provide rehabilitative exercises for forearm and, wrist movements. In contrast to existing RDs, developed UWM-FWRR is a portable, light weight, low cost, and novel powered rehabilitation device that will be developed to provide therapeutic exercises to a wide group of patients with different degrees of impairments. This innovation provides an opportunity for the patients to perform exercises not only with the guidance of a therapist at clinic but also be used at home as a telerehabilitation device through smartphone application (Future works)

Robot-aided assessment of wrist proprioception

Introduction: Impaired proprioception severely affects the control of gross and fine motor function. However, clinical assessment of proprioceptive deficits and its impact on motor function has been difficult to elucidate. Recent advances in haptic robotic interfaces designed for sensorimotor rehabilitation enabled the use of such devices for the assessment of proprioceptive function. Purpose: This study evaluated the feasibility of a wrist robot system to determine proprioceptive discrimination thresholds for two different DoFs of the wrist. Specifically, we sought to accomplish three aims: first, to establish data validity; second, to show that the system is sensitive to detect small differences in acuity; third, to establish test–retest reliability over repeated testing. Methodology: Eleven healthy adult subjects experienced two passive wrist movements and had to verbally indicate which movement had the larger amplitude. Based on a subject’s response data, a psychometric function was fitted and the wrist acuity threshold was established at the 75% correct response level. A subset of five subjects repeated the experimentation three times (T1, T2, and T3) to determine the test–retest reliability. Results: Mean threshold for wrist flexion was 2.15° ± 0.43° and 1.52° ± 0.36° for abduction. Encoder resolutions were 0.0075° (flexion–extension) and 0.0032° (abduction–adduction). Motor resolutions were 0.2°(flexion–extension) and 0.3° (abduction–adduction). Reliability coefficients were rT2-T1 = 0.986 and rT3-T2 = 0.971. Conclusion: We currently lack established norm data on the proprioceptive acuity of the wrist to establish direct validity. However, the magnitude of our reported thresholds is physiological, plausible, and well in line with available threshold data obtained at the elbow joint. Moreover, system has high resolution and is sensitive enough to detect small differences in acuity. Finally, the system produces reliable data over repeated testing

Design of ELISE robot for the paretic upper limb of stroke survivors

To characterize the ELISE project, a concept robot applicable in the neuro-rehabilitation of the entire paretic upper limb. The project has been designed and implemented based on comprehensive rehabilitation of the shoulder, forearm and hand. ELISE is a concept robotic system prepared for individualized approach in rehabilitation of stroke patients including diagnostics, passive and/or active exercises and reports. The ELISE system includes dual biofeedback solutions: rehabilitation exercises in virtual reality (VR) and the virtual assistant of therapist. The biomechanical, ergonomics, electrical/electronics, hardware/software aspects of the design are described in detail here. This paper suggests a new approach to rehabilitation robots for the spastic upper limb of stroke survivors. Rehabilitation with ELISE robot was based on movement exercises, which incorporate biofeedback in VR. The patient realizes common tasks from ordinary life. This innovative rehabilitation connects practical/social aspect of rehabilitation with movement exercises. With the aid of these stimulations, the ELISE robot is intended to speed up the process of recovery from damaged neuron connections in brain. Robot was designed for flexible assembly and can be tailored to individual needs and unique expectations of each therapist and patient. This is possible thanks to the modular design of the robot arm and software. The ELISE robot will be sold in different configurations (e.g. without an expander or a set of virtual games or a virtual assistant of therapist)