Review of control strategies for robotic movement training after neurologic injury

Exoskeleton robot control for synchronous walking assistance in repetitive manual handling works based on dual unscented Kalman filter

Prolong walking is a notable risk factor for work-related lower-limb disorders (WRLLD) in industries such as agriculture, construction, service profession, healthcare and retail works. It is one of the common causes of lower limb fatigue or muscular exhaustion leading to poor balance and fall. Exoskeleton technology is seen as a modern strategy to assist worker’s in these professions to minimize or eliminate the risk of WRLLDs. Exoskeleton has potentials to benefit workers in prolong walking (amongst others) by augmenting their strength, increasing their endurance, and minimizing high muscular activation, resulting in overall work efficiency and productivity. Controlling exoskeleton to achieve this purpose for able-bodied personnel without impeding their natural movement is, however, challenging. In this study, we propose a control strategy that integrates a Dual Unscented Kalman Filter (DUKF) for trajectory generation/prediction of the spatio-temporal features of human walking (i.e. joint position, and velocity, and acceleration) and an impedance cum supervisory controller to enable the exoskeleton to follow this trajectory to synchronize with the human walking. Experiment is conducted with four subjects carrying a load and walking at their normal speed- a typical scenario in industries. EMG signals taken at two muscles: Right Vastus Intermedius (on the thigh) and Right Gastrocnemius (on the calf) indicated reduction in muscular activation during the experiment. The results also show the ability of the control system to predict spatio-temporal features of the pilots’ walking and to enable the exoskeleton to move in concert with the pilot.

Application of an LDA Classifier for Determining User-Intent in Multi-DOF Quasi-Static Shoulder Tasks in Individuals with Chronic Stroke: Preliminary Analysis

Abnormal synergies commonly present after stroke, limiting function and accomplishment of ADL's. They cause co-activation of sets of muscles spanning multiple joints across the affected upper-extremity. These synergies present proportionally to the amount of shoulder effort, thus the effects of the synergy reduce with reduced effort of shoulder muscles. A promising solution may be the application of a wearable exoskeletal robotic device to support the paretic shoulder in hopes to maximize function. To date, control strategies for such a device remain unknown. This work examines the feasibility of using two different linear discriminant analysis classifiers to control shoulder abduction and adduction as well as external and internal rotation simultaneously, two primary degrees of freedom that have gone largely unstudied in hemiparetic stroke. Forces, moments, and muscle activity were recorded during single and dual-tasks involving these degrees of freedom. A classifier that classified all tasks was able to determine user-intent in 14 of the 15 tasks above 90% accuracy. A classifier using force and moment data provided an average 94.3% accuracy, EMG 79%, and data sets combined, 94.9% accuracy. Parallel classifiers identifying user-intent in either abduction and adduction or internal and external rotation were 95.4%, 92.6%, and 97.3% accurate for the respective data sets. These preliminary results indicate that it seems possible to classify user-intent of the paretic shoulder in these degrees of freedom to an adequate accuracy using load cell data or load cell and EMG data combined that would enable control of a powered exoskeletal device.

Energetics during robot-assisted training predicts recovery in stroke

Clinical investigators have asserted patients should be active participants in the therapy process in stroke rehabilitation. While robotics introduces new tools for measurement and treatment of motor impairments, it also presents challenges for evaluating how much a patient contributes to observed movements during training. Our approach employs established methods of inverse dynamics combined with measurements of human motion and interaction forces between the human and robot. Here, we investigated whether measures of patient active involvement predict the level of upper limb recovery due to robot-assisted therapy. Stroke survivors (n=11) completed "exploration" training with customizable forces that increased their velocities (i.e., negative damping). While our results showed a mild trend between mechanical work during training and expanded velocity capability (Pearson r = 0.57), we found significant correlations with the amount of positive work (i.e., propulsion; r = 0.77), but not negative work (i.e., braking; r = 0.41). This work supports robotic tools that encourage more positive work.

A Portable Passive Rehabilitation Robot for Upper-Extremity Functional Resistance Training

OBJECTIVE

Loss of arm function is common in individuals with neurological damage, such as stroke or cerebral palsy. Robotic devices that address muscle strength deficits in a task-specific manner can assist in the recovery of arm function; however, current devices are typically large, bulky, and expensive to be routinely used in the clinic or at home. This study sought to address this issue by developing a portable planar passive rehabilitation robot, PaRRo.

METHODS

We designed PaRRo with a mechanical layout that incorporated kinematic redundancies to generate forces that directly oppose the user's movement. Cost-efficient eddy current brakes were used to provide scalable resistances. The lengths of the robot's linkages were optimized to have a reasonably large workspace for human planar reaching. We then performed theoretical analysis of the robot's resistive force generating capacity and steerable workspace using MATLAB simulations. We also validated the device by having a subject move the end-effector along different paths at a set velocity using a metronome while simultaneously collecting surface electromyography (EMG) and end-effector forces felt by the user.

RESULTS

Results from simulation experiments indicated that the robot was capable of producing sufficient end-effector forces for functional resistance training. We also found the endpoint forces from the user were similar to the theoretical forces expected at any direction of motion. EMG results indicated that the device was capable of providing adjustable resistances based on subjects' ability levels, as the muscle activation levels scaled with increasing magnet exposures.

CONCLUSION

These results indicate that PaRRo is a feasible approach to provide functional resistance training to the muscles along the upper extremity.

SIGNIFICANCE

The proposed robotic device could provide a technological breakthrough that will make rehabilitation robots accessible for small outpatient rehabilitation centers and in-home therapy.

Perceptual control models of pursuit manual tracking demonstrate individual specificity and parameter consistency

Computational models that simulate individuals’ movements in pursuit-tracking tasks have been used to elucidate mechanisms of human motor control. Whilst there is evidence that individuals demonstrate idiosyncratic control-tracking strategies, it remains unclear whether models can be sensitive to these idiosyncrasies. Perceptual control theory (PCT) provides a unique model architecture with an internally set reference value parameter, and can be optimized to fit an individual’s tracking behavior. The current study investigated whether PCT models could show temporal stability and individual specificity over time. Twenty adults completed three blocks of 15 1-min, pursuit-tracking trials. Two blocks (training and post-training) were completed in one session and the third was completed after 1 week (follow-up). The target moved in a one-dimensional, pseudorandom pattern. PCT models were optimized to the training data using a least-mean-squares algorithm, and validated with data from post-training and follow-up. We found significant inter-individual variability (partial η²: .464–.697) and intra-individual consistency (Cronbach’s α: .880–.976) in parameter estimates. Polynomial regression revealed that all model parameters, including the reference value parameter, contribute to simulation accuracy. Participants’ tracking performances were significantly more accurately simulated by models developed from their own tracking data than by models developed from other participants’ data. We conclude that PCT models can be optimized to simulate the performance of an individual and that the test-retest reliability of individual models is a necessary criterion for evaluating computational models of human performance.

A Challenge-Based Approach to Body Weight-Supported Treadmill Training Poststroke: Protocol for a Randomized Controlled Trial

Background

Body weight support treadmill training protocols in conjunction with other modalities are commonly used to improve poststroke balance and walking function. However, typical body weight support paradigms tend to use consistently stable balance conditions, often with handrail support and or manual assistance.

Objective

In this paper, we describe our study protocol, which involved 2 unique body weight support treadmill training paradigms of similar training intensity that integrated dynamic balance challenges to help improve ambulatory function post stroke. The first paradigm emphasized walking without any handrails or manual assistance, that is, hands-free walking, and served as the control group, whereas the second paradigm incorporated practicing 9 essential challenging mobility skills, akin to environmental barriers encountered during community ambulation along with hands-free walking (ie hands-free + challenge walking).

Methods

We recruited individuals with chronic poststroke hemiparesis and randomized them to either group. Participants trained for 6 weeks on a self-driven, robotic treadmill interface that provided body weight support and a safe gait-training environment. We assessed participants at pre-, mid- and post 6 weeks of intervention-training, with a 6-month follow-up. We hypothesized greater walking improvements in the hands-free + challenge walking group following training because of increased practice opportunity of essential mobility skills along with hands-free walking.

Results

We assessed 77 individuals with chronic hemiparesis, and enrolled and randomized 30 individuals poststroke for our study (hands-free group=19 and hands-free + challenge walking group=20) from June 2012 to January 2015. Data collection along with 6-month follow-up continued until January 2016. Our primary outcome measure is change in comfortable walking speed from pre to post intervention for each group. We will also assess feasibility, adherence, postintervention efficacy, and changes in various exploratory secondary outcome measures. Additionally, we will also assess participant responses to a study survey, conducted at the end of training week, to gauge each group's training experiences.

Conclusions

Our treadmill training paradigms, and study protocol represent advances in standardized approaches to selecting body weight support levels without the necessity for using handrails or manual assistance, while progressively providing dynamic challenges for improving poststroke ambulatory function during rehabilitation.

Trial Registration

ClinicalTrials.gov NCT02787759; https://clinicaltrials.gov/ct2/show/NCT02787759 (Archived by Webcite at http://www.webcitation.org/6yJZCrIea)

Training children aged 5-10 years in manual compliance control to improve drawing and handwriting

A large proportion of school-aged children exhibit poor drawing and handwriting. This prevalence limits the availability of therapy. We developed an automated method for training improved manual compliance control and relatedly, prospective control of a stylus. The approach included a difficult training task, while providing parametrically modifiable support that enables the children to perform successfully while developing good compliance control. The task was to use a stylus to push a bead along a 3D wire path. Support was provided by making the wire magnetically attractive to the stylus. Support was progressively reduced as 3D tracing performance improved. We report studies that (1) compared performance of Typically Developing (TD) children and children with Developmental Coordination Disorder (DCD), (2) tested training with active versus passive movement, (3) tested progressively reduced versus constant or no support during training, (4) tested children of different ages, (5) tested the transfer of training to a drawing task, (6) tested the specificity of training in respect to the size, shape and dimensionality of figures, and (7) investigated the relevance of the training task to the Beery VMI, an inventory used to diagnose DCD. The findings were as follows. (1) Pre-training performance of TD and DCD children was the same and good with high support but distinct and poor with low support. Support yielded good self-efficacy that motivated training. Post training performance with no support was improved and the same for TD and DCD children. (2) Actively controlled movements were required for improved performance. (3) Progressively reduced support was required for good performance during and after training. (4) Age differences in performance during pre-training were eliminated post-training. (5) Improvements transferred to drawing. (6) There was no evidence of specificity of training in transfer. (7) Disparate Beery scores were reflected in pre-training but not post-training performance. We conclude that the method improves manual compliance control, and more generally, prospective control of movements used in drawing performance.

Technological Approaches for Neurorehabilitation: From Robotic Devices to Brain Stimulation and Beyond

Neurological diseases causing motor/cognitive impairments are among the most common causes of adult-onset disability. More than one billion of people are affected worldwide, and this number is expected to increase in upcoming years, because of the rapidly aging population. The frequent lack of complete recovery makes it desirable to develop novel neurorehabilitative treatments, suited to the patients, and better targeting the specific disability. To date, rehabilitation therapy can be aided by the technological support of robotic-based therapy, non-invasive brain stimulation, and neural interfaces. In this perspective, we will review the above methods by referring to the most recent advances in each field. Then, we propose and discuss current and future approaches based on the combination of the above. As pointed out in the recent literature, by combining traditional rehabilitation techniques with neuromodulation, biofeedback recordings and/or novel robotic and wearable assistive devices, several studies have proven it is possible to sensibly improve the amount of recovery with respect to traditional treatments. We will then discuss the possible applied research directions to maximize the outcome of a neurorehabilitation therapy, which should include the personalization of the therapy based on patient and clinician needs and preferences.

A Semi-passive Planar Manipulandum for Upper-Extremity Rehabilitation

Robotic rehabilitation is a promising approach to treat individuals with neurological or orthopedic disorders. However, despite significant advancements in the field of rehabilitation robotics, this technology has found limited traction in clinical practice. A key reason for this issue is that most robots are expensive, bulky, and not scalable for in-home rehabilitation. Here, we introduce a semi-passive rehabilitation robot (SepaRRo) that uses controllable passive actuators (i.e., brakes) to provide controllable resistances at the end-effector over a large workspace in a manner that is cost-effective and safe for in-home use. We also validated the device through theoretical analyses, hardware experiments, and human subject experiments. We found that by including kinematic redundancies in the robot's linkages, the device was able to provide controllable resistances to purely resist the movement of the end-effector, or to gently steer (i.e., perturb) its motion away from the intended path. When testing these capabilities on human subjects, we found that many of the upper-extremity muscles could be selectively targeted based on the forcefield prescribed to the user. These results indicate that SepaRRo could serve as a low-cost therapeutic tool for upper-extremity rehabilitation; however, further testing is required to evaluate its therapeutic benefits in patient population.

A Review of Robotics in Neurorehabilitation: Towards an Automated Process for Upper Limb

Robot-mediated neurorehabilitation is a growing field that seeks to incorporate advances in robotics combined with neuroscience and rehabilitation to define new methods for treating problems related with neurological diseases. In this paper, a systematic literature review is conducted to identify the contribution of robotics for upper limb neurorehabilitation, highlighting its relation with the rehabilitation cycle, and to clarify the prospective research directions in the development of more autonomous rehabilitation processes. With this aim, first, a study and definition of a general rehabilitation process are made, and then, it is particularized for the case of neurorehabilitation, identifying the components involved in the cycle and their degree of interaction between them. Next, this generic process is compared with the current literature in robotics focused on upper limb treatment, analyzing which components of this rehabilitation cycle are being investigated. Finally, the challenges and opportunities to obtain more autonomous rehabilitation processes are discussed. In addition, based on this study, a series of technical requirements that should be taken into account when designing and implementing autonomous robotic systems for rehabilitation is presented and discussed.

A review in gait rehabilitation devices and applied control techniques

PURPOSE

The aim of this review is to analyse the different existing technologies for gait rehabilitation, focusing mainly in robotic devices. Those robots help the patient to recover a lost function due to neurological gait disorders, accidents or after injury. Besides, they facilitate the identification of normal and abnormal features by registering muscle activity providing the doctor important data where he can observe the evolution of the patient.

METHOD

A deep literature review was realized using selected keywords considering not only the most common medical and engineering databases, but also other available sources that provide information on commercial and scientific gait rehabilitation devices. The founded literature for this review corresponds to control techniques for gait rehabilitation robots, since the early seventies to the present year.

RESULTS

Different control strategies for gait analysis in rehabilitation devices have been developed and implemented such as position control, force and impedance control, haptic simulation, and control of EMG signals. These control techniques are used to analyze the force of the patient during therapy, compensating it with the force generated by the mechanism in the rehabilitation device. It is observed that the largest number of studies reported, focuses on the impedance control technique. Leading to include new control techniques and validate them using the necessary protocols with ill patients, obtaining reliable results that allows a progressive and active rehabilitation.

CONCLUSIONS

With this exhaustive review, we can conclude that the degree of complexity of the rehabilitation device influences in short and long-term therapeutic results since the movements become more controlled. However, there is still a lot of work in the sense of motion control in order to perform trajectories that are more alike the natural movements of humans. There are many control techniques in other areas, which seek to improve the performance of the process. These techniques may possibly be applicable in gait rehabilitation devices, obtaining controllers that are more efficient and that adapts to different people and the necessities that entail every disease. Implications for Rehabilitation Rehabilitation helps people to improve the activities of their daily life, allowing them to observe their progress in the functional abilities as the months pass by with intensive and repetitive therapies. There is a mobility issue when the patient needs to move to the hospital or to the laboratory, which is not always feasible. For overcoming it, patients use the equipment at home to perform their daily therapy. However, they need the sufficient knowledge about its operation, also about the therapeutic movements, the therapy duration and the movement speed. Besides, is necessary to place the equipment in a proper and lively environment that helps to forget or reduce pain while the patient moves his joints progressively. The purpose of robotic rehabilitation devices is to generate repetitive and progressive movements, according to the motor disability. There are training trajectories to follow, which motivate patients to generate active movements. The benefits of robotic rehabilitation depend on the ability of each patient to adapt to the speed and load variations generated by the device, improving and reinforcing motor functions in therapy, especially in patients with advanced disabilities in early rehabilitation. Multi-joint rehabilitation devices are more effective than single-joint rehabilitation devices because they involve a higher number of muscles in the therapy. The greater the number of degrees of freedom (DoF) of the device, it cushions its effect in the patient because the inertia is reduced and higher torques are generated. The assistive technological devices allows to explore different rehabilitation techniques that motivate the patient in therapy, increasing appropriately the energy and pressure in the blood which is reflected in gradually recovering his ability to walk.

The effect of haptic interaction between balance assessment robot and pelvis on muscle activation of leg muscles

Admittance control is considered as a promising paradigm in rehabilitation that provides us with means to establish well controlled and adjustable interaction and cooperation between rehabilitation devices and patients. Recently we developed balance assessment robot (BAR) for studying postural responses during walking as well as for pelvis manipulation during walking that implements admittance control as a mean of interaction with user. In this study we evaluated the characteristics of transparent haptic interaction and investigated whether transparent haptic interaction induces adaptations in muscle activation patterns with respect to free walking. In one neurologically intact individual we measured interaction forces, ground reaction forces and center of pressure as well as EMG of selected leg muscles while walking free and while walking with BAR. Results show that the amplitude of interaction forces in transparent mode of operation remained below levels that could have imposed considerable adjustments in muscle activation patterns of leg muscles.

Is EMG a Viable Alternative to BCI for Detecting Movement Intention in Severe Stroke?

OBJECTIVE

In light of the shortcomings of current restorative brain-computer interfaces (BCI), this study investigated the possibility of using EMG to detect hand/wrist extension movement intention to trigger robot-assisted training in individuals without residual movements.

METHODS

We compared movement intention detection using an EMG detector with a sensorimotor rhythm based EEG-BCI using only ipsilesional activity. This was carried out on data of 30 severely affected chronic stroke patients from a randomized control trial using an EEG-BCI for robot-assisted training.

RESULTS

The results indicate the feasibility of using EMG to detect movement intention in this severely handicapped population; probability of detecting EMG when patients attempted to move was higher (p 0.001) than at rest. Interestingly, 22 out of 30 (or 73%) patients had sufficiently strong EMG in their finger/wrist extensors. Furthermore, in patients with detectable EMG, there was poor agreement between the EEG and EMG intent detectors, which indicates that these modalities may detect different processes.

CONCLUSION

A substantial segment of severely affected stroke patients may benefit from EMG-based assisted therapy. When compared to EEG, a surface EMG interface requires less preparation time, which is easier to don/doff, and is more compact in size.

SIGNIFICANCE

This study shows that a large proportion of severely affected stroke patients have residual EMG, which yields a direct and practical way to trigger robot-assisted training.

Learning by Demonstration for Motion Planning of Upper-Limb Exoskeletons

The reference joint position of upper-limb exoskeletons is typically obtained by means of Cartesian motion planners and inverse kinematics algorithms with the inverse Jacobian; this approach allows exploiting the available Degrees of Freedom (i.e. DoFs) of the robot kinematic chain to achieve the desired end-effector pose; however, if used to operate non-redundant exoskeletons, it does not ensure that anthropomorphic criteria are satisfied in the whole human-robot workspace. This paper proposes a motion planning system, based on Learning by Demonstration, for upper-limb exoskeletons that allow successfully assisting patients during Activities of Daily Living (ADLs) in unstructured environment, while ensuring that anthropomorphic criteria are satisfied in the whole human-robot workspace. The motion planning system combines Learning by Demonstration with the computation of Dynamic Motion Primitives and machine learning techniques to construct task- and patient-specific joint trajectories based on the learnt trajectories. System validation was carried out in simulation and in a real setting with a 4-DoF upper-limb exoskeleton, a 5-DoF wrist-hand exoskeleton and four patients with Limb Girdle Muscular Dystrophy. Validation was addressed to (i) compare the performance of the proposed motion planning with traditional methods; (ii) assess the generalization capabilities of the proposed method with respect to the environment variability. Three ADLs were chosen to validate the system: drinking, pouring and lifting a light sphere. The achieved results showed a 100% success rate in the task fulfillment, with a high level of generalization with respect to the environment variability. Moreover, an anthropomorphic configuration of the exoskeleton is always ensured.

Modulation of shoulder muscle and joint function using a powered upper-limb exoskeleton

Robotic-assistive exoskeletons can enable frequent repetitive movements without the presence of a full-time therapist; however, human-machine interaction and the capacity of powered exoskeletons to attenuate shoulder muscle and joint loading is poorly understood. This study aimed to quantify shoulder muscle and joint force during assisted activities of daily living using a powered robotic upper limb exoskeleton (ArmeoPower, Hocoma). Six healthy male subjects performed abduction, flexion, horizontal flexion, reaching and nose touching activities. These tasks were repeated under two conditions: (i) the exoskeleton compensating only for its own weight, and (ii) the exoskeleton providing full upper limb gravity compensation (i.e., weightlessness). Muscle EMG, joint kinematics and joint torques were simultaneously recorded, and shoulder muscle and joint forces calculated using personalized musculoskeletal models of each subject's upper limb. The exoskeleton reduced peak joint torques, muscle forces and joint loading by up to 74.8% (0.113 Nm/kg), 88.8% (5.8%BW) and 68.4% (75.6%BW), respectively, with the degree of load attenuation strongly task dependent. The peak compressive, anterior and superior glenohumeral joint force during assisted nose touching was 36.4% (24.6%BW), 72.4% (13.1%BW) and 85.0% (17.2%BW) lower than that during unassisted nose touching, respectively. The present study showed that upper limb weight compensation using an assistive exoskeleton may increase glenohumeral joint stability, since deltoid muscle force, which is the primary contributor to superior glenohumeral joint shear, is attenuated; however, prominent exoskeleton interaction moments are required to position and control the upper limb in space, even under full gravity compensation conditions. The modeling framework and results may be useful in planning targeted upper limb robotic rehabilitation tasks.

A review: Motor rehabilitation after stroke with control based on human intent

Strokes are a leading cause of acquired disability worldwide, and there is a significant need for novel interventions and further research to facilitate functional motor recovery in stroke patients. This article reviews motor rehabilitation methods for stroke survivors with a focus on rehabilitation controlled by human motor intent. The review begins with the neurodevelopmental principles of motor rehabilitation that provide the neuroscientific basis for intuitively controlled rehabilitation, followed by a review of methods allowing human motor intent detection, biofeedback approaches, and quantitative motor rehabilitation assessment. Challenges for future advances in motor rehabilitation after stroke using intuitively controlled approaches are addressed.

Position and torque control via rehabilitation robot and functional electrical stimulation

Two common rehabilitation therapies for individuals possessing neurological conditions are functional electrical stimulation (FES) and robotic assistance. This paper focuses on combining the two rehabilitation strategies for use on the biceps brachii muscle group. FES is used to elicit muscle contractions to actuate the forearm and a rehabilitation robot is used to challenge the muscle group in its efforts. Two controllers were developed and implemented to accomplish the multifaceted objective, both of which achieve global exponential stability for position and torque tracking as proven through a Lyapunov stability analysis. Experiments performed on one able bodied individual demonstrate an average RMS error of 5.8 degrees for position tracking and 0.40 Newton-meters for torque tracking.

Design and Evaluation of an Instrumented Wobble Board for Assessing and Training Dynamic Seated Balance

Methods that effectively assess and train dynamic seated balance are critical for enhancing functional independence and reducing risk of secondary health complications in the elderly and individuals with neuromuscular impairments. The objective of this research was to devise and validate a portable tool for assessing and training dynamic seated balance. An instrumented wobble board was designed and constructed that (1) elicits multidirectional perturbations in seated individuals, (2) quantifies seated balance proficiency, and (3) provides real-time, kinematics-based vibrotactile feedback. After performing a technical validation study to compare kinematic wobble board measurements against a gold-standard motion capture system, 15 nondisabled participants performed a dynamic sitting task using the wobble board. Our results demonstrate that the tilt angle measurements were highly accurate throughout the range of wobble board dynamics. Furthermore, the posturographic analyses for the dynamic sitting task revealed that the wobble board can effectively discriminate between the different conditions of perturbed balance, demonstrating its potential to serve as a clinical tool for the assessment and training of seated balance. Vibrotactile feedback decreased the variance of wobble board tilt, demonstrating its potential for use as a balance training tool. Unlike similar instrumented tools, the wobble board is portable, requires no laboratory equipment, and can be adjusted to meet the user's balance abilities. While future work is warranted, obtained findings will aid in effective translation of assessment and training techniques to a clinical setting, which has the potential to enhance the diagnosis and prognosis for individuals with seated balance impairments.

An overview of robotic/mechanical devices for post-stroke thumb rehabilitation

PURPOSE

This article aims to clarify the current state-of-the-art of robotic/mechanical devices for post-stroke thumb rehabilitation as well as the anatomical characteristics and motions of the thumb that are crucial for the development of any device that aims to support its motion.

METHODS

A systematic literature search was conducted to identify robotic/mechanical devices for post-stroke thumb rehabilitation. Specific electronic databases and well-defined search terms and inclusion/exclusion criteria were used for such purpose. A reasoning model was devised to support the structured abstraction of relevant data from the literature of interest.

RESULTS

Following the main search and after removing duplicated and other non-relevant studies, 68 articles (corresponding to 32 devices) were left for further examination. These articles were analyzed to extract data relative to (i) the motions assisted/permitted - either actively or passively - by the device per anatomical joint of the thumb and (ii) mechanical-related aspects (i.e., architecture, connections to thumb, other fingers supported, adjustability to different hand sizes, actuators - type, quantity, location, power transmission and motion trajectory).

CONCLUSIONS

Most articles describe preliminary design and testing of prototypes, rather than the thorough evaluation of commercially ready devices. Defining appropriate kinematic models of the thumb upon which to design such devices still remains a challenging and unresolved task. Further research is needed before these devices can actually be implemented in clinical environments to serve their intended purpose of complementing the labour of therapists by facilitating intensive treatment with precise and repeatable exercises. Implications for Rehabilitation Post-stroke functional disability of the hand, and particularly of the thumb, significantly affects the capability to perform activities of daily living, threatening the independence and quality of life of the stroke survivors. The latest studies show that a high-dose intensive therapy (in terms of frequency, duration and intensity/effort) is the key to effectively modify neural organization and recover the motor skills that were lost after a stroke. Conventional therapy based on manual interaction with physical therapists makes the procedure labour intensive and increases the costs. Robotic/mechanical devices hold promise for complementing conventional post-stroke therapy. Specifically, these devices can provide reliable and accurate therapy for long periods of time without the associated fatigue. Also, they can be used as a means to assess patients? performance and progress in an objective and consistent manner. The full potential of robot-assisted therapy is still to be unveiled. Further exploration will surely lead to devices that can be well accepted equally by therapists and patients and that can be useful both in clinical and home-based rehabilitation practice such that motor recovery of the hand becomes a common outcome in stroke survivors. This overview provides the reader, possibly a designer of such a device, with a complete overview of the state-of-the-art of robotic/mechanical devices consisting of or including features for the rehabilitation of the thumb. Also, we clarify the anatomical characteristics and motions of the thumb that are crucial for the development of any device that aims to support its motion. Hopefully, this?combined with the outlined opportunities for further research?leads to the improvement of current devices and the development of new technology and knowledge in the field.

Volition-adaptive control for gait training using wearable exoskeleton: preliminary tests with incomplete spinal cord injury individuals

BACKGROUND

Gait training for individuals with neurological disorders is challenging in providing the suitable assistance and more adaptive behaviour towards user needs. The user specific adaptation can be defined based on the user interaction with the orthosis and by monitoring the user intentions. In this paper, an adaptive control model, commanded by the user intention, is evaluated using a lower limb exoskeleton with incomplete spinal cord injury individuals (SCI).

METHODS

A user intention based adaptive control model has been developed and evaluated with 4 incomplete SCI individuals across 3 sessions of training per individual. The adaptive control model modifies the joint impedance properties of the exoskeleton as a function of the human-orthosis interaction torques and the joint trajectory evolution along the gait sequence, in real time. The volitional input of the user is identified by monitoring the neural signals, pertaining to the user's motor activity. These volitional inputs are used as a trigger to initiate the gait movement, allowing the user to control the initialization of the exoskeleton movement, independently. A Finite-state machine based control model is used in this set-up which helps in combining the volitional orders with the gait adaptation.

RESULTS

The exoskeleton demonstrated an adaptive assistance depending on the patients' performance without guiding them to follow an imposed trajectory. The exoskeleton initiated the trajectory based on the user intention command received from the brain machine interface, demonstrating it as a reliable trigger. The exoskeleton maintained the equilibrium by providing suitable assistance throughout the experiments. A progressive change in the maximum flexion of the knee joint was observed at the end of each session which shows improvement in the patient performance. Results of the adaptive impedance were evaluated by comparing with the application of a constant impedance value. Participants reported that the movement of the exoskeleton was flexible and the walking patterns were similar to their own distinct patterns.

CONCLUSIONS

This study demonstrates that user specific adaptive control can be applied on a wearable robot based on the human-orthosis interaction torques and modifying the joints' impedance properties. The patients perceived no external or impulsive force and felt comfortable with the assistance provided by the exoskeleton. The main goal of such a user dependent control is to assist the patients' needs and adapt to their characteristics, thus maximizing their engagement in the therapy and avoiding slacking. In addition, the initiation directly controlled by the brain allows synchronizing the user's intention with the afferent stimulus provided by the movement of the exoskeleton, which maximizes the potentiality of the system in neuro-rehabilitative therapies.

Underactuated Potential Energy Shaping with Contact Constraints: Application to a Powered Knee-Ankle Orthosis

Body-weight support (i.e., gravity compensation) is an effective clinical tool for gait rehabilitation after neurological impairment. Body-weight supported training systems have been developed to help patients regain mobility and confidence during walking, but conventional systems constrain the patient's treatment in clinical environments. We propose that this challenge could be addressed by virtually providing patients with bodyweight support through the actuators of a powered orthosis (or exoskeleton) utilizing potential energy shaping control. However, the changing contact conditions and degrees of underactuation encountered during human walking present significant challenges to consistently matching a desired potential energy for the human in closed loop. We therefore derive a generalized matching condition for shaping Lagrangian systems with holonomic contact constraints. By satisfying this matching condition for four phases of gait, we derive passivity-based control laws to achieve virtual body-weight support through a powered knee-ankle orthosis. We demonstrate beneficial effects of virtual body-weight support in simulations of a human-like biped model, indicating the potential clinical value of this proposed control approach.

Mapping upper-limb motor performance after stroke - a novel method with utility for individualized motor training

Background

Chronic upper limb motor impairment is a common outcome of stroke. Therapeutic training can reduce motor impairment. Recently, a growing interest in evaluating motor training provided by robotic assistive devices has emerged. Robot-assisted therapy is attractive because it provides a means of increasing practice intensity without increasing the workload of physical therapists. However, movements practised through robotic assistive devices are commonly pre-defined and fixed across individuals. More optimal training may result from individualizing the selection of the trained movements based on the individual’s impairment profile. This requires quantitative assessment of the degree of the motor impairment prior to training, in relevant movement tasks. However, standard clinical measures for profiling motor impairment after stroke are often subjective and lack precision. We have developed a novel robot-mediated method for systematic and fine-grained mapping (or profiling) of individual performance across a wide range of planar arm reaching movements. Here we describe and demonstrate this mapping method and its utilization for individualized training. We also present a novel principle for the individualized selection of training movements based on the performance maps.

Methods and Results

To demonstrate the utility of our method we present examples of 2D performance maps produced from the kinetic and kinematics data of two individuals with stroke-related upper limb hemiparesis. The maps outline distinct regions of high motor impairment. The procedure of map-based selection of training movements and the change in motor performance following training is demonstrated for one participant.

Conclusions

The performance mapping method is feasible to produce (online or offline). The 2D maps are easy to interpret and to be utilized for selecting individual performance-based training. Different performance maps can be easily compared within and between individuals, which potentially has diagnostic utility.

Electronic supplementary material

The online version of this article (10.1186/s12984-017-0335-x) contains supplementary material, which is available to authorized users.

SAP97 Binding Partner CRIPT Promotes Dendrite Growth In Vitro and In Vivo

The dendritic tree is a key determinant of neuronal information processing. In the motor system, the dendritic tree of spinal cord neurons undergoes dramatic remodeling in an activity-dependent manner during early postnatal life. This leads to the proper segmental spinal cord connectivity that subserves normal locomotor behavior. One molecular system driving the establishment of dendrite architecture of mammalian motor neurons relies on AMPA receptors (AMPA-Rs) assembled with the GluA1 subunit, and this occurs in an NMDA receptor (NMDA-R)-independent manner. The dendrite growth promoting activity of GluA1-containing AMPA-Rs depends on its intracellular binding partner, SAP97, and SAP97's PDZ3 domain. We show here that cysteine-rich interactor of PDZ3 (CRIPT) is a bona fide SAP97 PDZ3-domain binding partner, localizes to synapses with GluA1 and SAP97 along the dendritic tree, and is a determinant of the dendritic growth of mammalian spinal cord neurons. We further show that CRIPT has a well-conserved ortholog in the nematode, Caenorhabditis elegans, and animals lacking CRIPT display decreased dendrite branching of the well-studied PVD neuron in vivo. The lack of CRIPT leads to a selective defect in touch perception, and this is rescued by expression of wild-type (WT) human CRIPT (hCRIPT) in the nervous system. This work brings new light into the molecular machinery that drives dendritic growth during development and may prove relevant to the promotion of nervous system plasticity following insult.

Robot Training With Vector Fields Based on Stroke Survivors' Individual Movement Statistics

The wide variation in upper extremity motor impairments among stroke survivors necessitates more intelligent methods of customized therapy. However, current strategies for characterizing individual motor impairments are limited by the use of traditional clinical assessments (e.g., Fugl-Meyer) and simple engineering metrics (e.g., goal-directed performance). Our overall approach is to statistically identify the range of volitional movement capabilities, and then apply a robot-applied force vector field intervention that encourages under-expressed movements. We investigated whether explorative training with such customized force fields would improve stroke survivors' (n = 11) movement patterns in comparison to a control group that trained without forces (n = 11). Force and control groups increased Fugl-Meyer UE scores (average of 1.0 and 1.1, respectively), which is not considered clinically meaningful. Interestingly, participants from both groups demonstrated dramatic increases in their range of velocity during exploration following only six days of training (average increase of 166.4% and 153.7% for the Force and Control group, respectively). While both groups showed evidence of improvement, we also found evidence that customized forces affected learning in a systematic way. When customized forces were active, we observed broader distributions of velocity that were not present in the controls. Second, we found that these changes led to specific changes in unassisted motion. In addition, while the shape of movement distributions changed significantly for both groups, detailed analysis of the velocity distributions revealed that customized forces promoted a greater proportion of favorable changes. Taken together, these results provide encouraging evidence that patient-specific force fields based on individuals' movement statistics can be used to create new movement patterns and shape them in a customized manner. To the best of our knowledge, this paper is the first to directly link engineering assessments of stroke survivors' exploration movement behaviors to the design of customized robot therapy.

Design and Preliminary Feasibility Study of a Soft Robotic Glove for Hand Function Assistance in Stroke Survivors

Various robotic exoskeletons have been proposed for hand function assistance during activities of daily living (ADL) of stroke survivors. However, traditional exoskeletons involve the use of complex rigid systems that impede the natural movement of joints, and thus reduce the wearability and cause discomfort to the user. The objective of this paper is to design and evaluate a soft robotic glove that is able to provide hand function assistance using fabric-reinforced soft pneumatic actuators. These actuators are made of silicone rubber which has an elastic modulus similar to human tissues. Thus, they are intrinsically soft and compliant. Upon air pressurization, they are able to support finger range of motion (ROM) and generate the desired actuation of the finger joints. In this work, the soft actuators were characterized in terms of their blocked tip force, normal and frictional grip force outputs. Combining the soft actuators and flexible textile materials, a soft robotic glove was developed for grasping assistance during ADL for stroke survivors. The glove was evaluated on five healthy participants for its assisted ROM and grip strength. Pilot test was performed in two stroke survivors to evaluate the efficacy of the glove in assisting functional grasping activities. Our results demonstrated that the actuators designed in this study could generate desired force output at a low air pressure. The glove had a high kinematic transparency and did not affect the active ROM of the finger joints when it was being worn by the participants. With the assistance of the glove, the participants were able to perform grasping actions with sufficient assisted ROM and grip strength, without any voluntary effort. Additionally, pilot test on stroke survivors demonstrated that the patient's grasping performance improved with the presence and assistance of the glove. Patient feedback questionnaires also showed high level of patient satisfaction and comfort. In conclusion, this paper has demonstrated the possibility of using soft wearable exoskeletons that are more wearable, lightweight, and suitable to be used on a daily basis for hand function assistance of stroke survivors during activities of daily living.

The effectiveness of robotic training depends on motor task characteristics

Previous research suggests that the effectiveness of robotic training depends on the motor task to be learned. However, it is still an open question which specific task's characteristics influence the efficacy of error-modulating training strategies. Motor tasks can be classified based on the time characteristics of the task, in particular the task's duration (discrete vs. continuous). Continuous tasks require movements without distinct beginning or end. Discrete tasks require fast movements that include well-defined postures at the beginning and the end. We developed two games, one that requires a continuous movement-a tracking task-and one that requires discrete movements-a fast reaching task. We conducted an experiment with thirty healthy subjects to evaluate the effectiveness of three error-modulating training strategies-no guidance, error amplification (i.e., repulsive forces proportional to errors) and haptic guidance-on self-reported motivation and learning of the continuous and discrete games. Training with error amplification resulted in better motor learning than haptic guidance, besides the fact that error amplification reduced subjects' interest/enjoyment and perceived competence during training. Only subjects trained with error amplification improved their performance after training the discrete game. In fact, subjects trained without guidance improved the performance in the continuous game significantly more than in the discrete game, probably because the continuous task required greater attentional levels. Error-amplifying training strategies have a great potential to provoke better motor learning in continuous and discrete tasks. However, their long-lasting negative effects on motivation might limit their applicability in intense neurorehabilitation programs.

Effect of Error Augmentation on Brain Activation and Motor Learning of a Complex Locomotor Task

Up to date, the functional gains obtained after robot-aided gait rehabilitation training are limited. Error augmenting strategies have a great potential to enhance motor learning of simple motor tasks. However, little is known about the effect of these error modulating strategies on complex tasks, such as relearning to walk after a neurologic accident. Additionally, neuroimaging evaluation of brain regions involved in learning processes could provide valuable information on behavioral outcomes. We investigated the effect of robotic training strategies that augment errors—error amplification and random force disturbance—and training without perturbations on brain activation and motor learning of a complex locomotor task. Thirty-four healthy subjects performed the experiment with a robotic stepper (MARCOS) in a 1.5 T MR scanner. The task consisted in tracking a Lissajous figure presented on a display by coordinating the legs in a gait-like movement pattern. Behavioral results showed that training without perturbations enhanced motor learning in initially less skilled subjects, while error amplification benefited better-skilled subjects. Training with error amplification, however, hampered transfer of learning. Randomly disturbing forces induced learning and promoted transfer in all subjects, probably because the unexpected forces increased subjects' attention. Functional MRI revealed main effects of training strategy and skill level during training. A main effect of training strategy was seen in brain regions typically associated with motor control and learning, such as, the basal ganglia, cerebellum, intraparietal sulcus, and angular gyrus. Especially, random disturbance and no perturbation lead to stronger brain activation in similar brain regions than error amplification. Skill-level related effects were observed in the IPS, in parts of the superior parietal lobe (SPL), i.e., precuneus, and temporal cortex. These neuroimaging findings indicate that gait-like motor learning depends on interplay between subcortical, cerebellar, and fronto-parietal brain regions. An interesting observation was the low activation observed in the brain's reward system after training with error amplification compared to training without perturbations. Our results suggest that to enhance learning of a locomotor task, errors should be augmented based on subjects' skill level. The impacts of these strategies on motor learning, brain activation, and motivation in neurological patients need further investigation.

Exploration of Two Training Paradigms Using Forced Induced Weight Shifting With the Tethered Pelvic Assist Device to Reduce Asymmetry in Individuals After Stroke: Case Reports

Many robotic devices in rehabilitation incorporate an assist-as-needed haptic guidance paradigm to promote training. This error reduction model, while beneficial for skill acquisition, could be detrimental for long-term retention. Error augmentation (EA) models have been explored as alternatives. A robotic Tethered Pelvic Assist Device has been developed to study force application to the pelvis on gait and was used here to induce weight shift onto the paretic (error reduction) or nonparetic (error augmentation) limb during treadmill training. The purpose of these case reports is to examine effects of training with these two paradigms to reduce load force asymmetry during gait in two individuals after stroke (>6 mos). Participants presented with baseline gait asymmetry, although independent community ambulators. Participants underwent 1-hr trainings for 3 days using either the error reduction or error augmentation model. Outcomes included the Borg rating of perceived exertion scale for treatment tolerance and measures of force and stance symmetry. Both participants tolerated training. Force symmetry (measured on treadmill) improved from pretraining to posttraining (36.58% and 14.64% gains), however, with limited transfer to overground gait measures (stance symmetry gains of 9.74% and 16.21%). Training with the Tethered Pelvic Assist Device device proved feasible to improve force symmetry on the treadmill irrespective of training model. Future work should consider methods to increase transfer to overground gait.

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.

A lower-extremity exoskeleton improves knee extension in children with crouch gait from cerebral palsy

The ability to walk contributes considerably to physical health and overall well-being, particularly in children with motor disability, and is therefore prioritized as a rehabilitation goal. However, half of ambulatory children with cerebral palsy (CP), the most prevalent childhood movement disorder, cease to walk in adulthood. Robotic gait trainers have shown positive outcomes in initial studies, but these clinic-based systems are limited to short-term programs of insufficient length to maintain improved function in a lifelong disability such as CP. Sophisticated wearable exoskeletons are now available, but their utility in treating childhood movement disorders remains unknown. We evaluated an exoskeleton for the treatment of crouch (or flexed-knee) gait, one of the most debilitating pathologies in CP. We show that the exoskeleton reduced crouch in a cohort of ambulatory children with CP during overground walking. The exoskeleton was safe and well tolerated, and all children were able to walk independently with the device. Rather than guiding the lower limbs, the exoskeleton dynamically changed the posture by introducing bursts of knee extension assistance during discrete portions of the walking cycle, a perturbation that resulted in maintained or increased knee extensor muscle activity during exoskeleton use. Six of seven participants exhibited postural improvements equivalent to outcomes reported from invasive orthopedic surgery. We also demonstrate that improvements in crouch increased over the course of our multiweek exploratory trial. Together, these results provide evidence supporting the use of wearable exoskeletons as a treatment strategy to improve walking in children with CP.

EMU: A transparent 3D robotic manipulandum for upper-limb rehabilitation

This paper introduces the EMU, a three-dimensional robotic manipulandum for rehabilitation of the upper extremity for patients with neurological injury. The device has been designed to be highly transparent, have a large workspace, and allow the use of the hand for interaction with real-world objects to provide additional contextual cues during exercises. The transparency is achieved through the use of a capstan transmission for the drive joints; a hybrid serial parallel kinematics minimising moving inertia; and lightweight materials. An experimental protocol is reported here which demonstrates the transparency through a comparison to out-of-robot movements, and with an existing rehabilitation robotic device. Additionally, an adjustable gravity compensation method is constructed, which minimises the torque required at the shoulder to carry the subject's arm. These characteristics allow the EMU to serve as a multi-purpose platform for the further development of novel robot assisted rehabilitation strategies.

Making neurorehabilitation fun: Multiplayer training via damping forces balancing differences in skill levels

Multiplayer environments are thought to increase the training intensity in robot-aided rehabilitation therapy after stroke. We developed a haptic-based environment to investigate the dynamics of two-player training performing time-constrained reaching movements using the ARMin rehabilitation robot. We implemented a challenge level adaptation algorithm that controlled a virtual damping coefficient to reach a desired success rate. We tested the algorithm's effectiveness in regulating the success rate during game play in a simulation with computer-controlled players, in a feasibility study with six unimpaired players, and in a single session with one stroke patient. The algorithm demonstrated its capacity to adjust the damping coefficient to reach three levels of success rate (low [50%], moderate [70%], and high [90%]) during singleplayer and multiplayer training. For the patient - tested in single-player mode at the moderate success rate only - the algorithm showed also promising behavior. Results of the feasibility study showed that to increase the player's willingness to play at a more challenging task condition, the effect of the challenge level adaptation - regardless of being played in single player or multiplayer mode - might be more important than the provision of multiplayer setting alone. Furthermore, the multiplayer setting tends to be a motivating and encouraging therapy component. Based on these results we will optimize and expand the multiplayer training platform and further investigate multiplayer settings in stroke therapy.

Online adaptive assistance control in robot-based neurorehabilitation therapy

Repetitive and task specific robot-based rehabilitation has been proved to be effective for motor recovery over time. During a therapy, the task should improve subject's impaired movements, but also enhance their efforts for a more effective recovery. This requires an accurate tuning of the task difficulty, which should be tailored directly to the patient. In this work, we propose a system for real-time assistance adaptation based on online performance evaluation for post-stroke subjects. In particular, the aim of the system is to implement the "assist-as-needed" paradigm based on actual patients' motor skills during a therapy session with an active upper-limb robotic exoskeleton. The strength of the work is to propose a real-time algorithm for the assistance tuning based on an "assistance-performance" relationship. Such a relationship is based on experimental measurements, and allows the algorithm to compute a straightforward calculation of the assistance required. Finally, an assessment phase will show how the system provides assistance based on the difficulties experienced from the subjects, also facilitating their adaptation during the task.

Studying the implementation of iterative impedance control for assistive hand rehabilitation using an exoskeleton

A positive training synergy can be obtained when two individuals attempt to learn the same motor task while mechanically coupled to one another. In this paper, we have studied how mimicking this interaction through impedance control can be exploited to improve assistance delivered by hand exoskeleton devices during rehabilitation. In this context, the machine and user take complementary roles akin to two coupled individuals. We present the derivation of a dynamic model of the human hand for the purpose of controller development for new hand exoskeleton platforms. Using this model, we have simulated the behavior of an iterative impedance controller programmed for rehabilitative training. The controller interacts with cylindrical objects to be grasped by means of an inverse kinematic mapping and tuning of mechanical impedance characteristic of the finger joints. Through fusion of concepts from motor control theory, muscle impedance and task oriented control, the controller is capable of iteratively learn to accomplish simple tasks involving grasping and lifting while cooperating with a user. The controller is also capable of adapting to more complex dynamics for more dexterous tasks, such as pulling on a hand-bar or loosening the cap of a jar. We believe the human-robot synergy established in this investigation has benefits to therapy. It can be combined with a broad range of training exercises and represents an incremental step towards mimicking natural human motor responses.

Compensating for telecommunication delays during robotic telerehabilitation

Rehabilitation robotic systems may afford better care and telerehabilitation may extend the use and benefits of robotic therapy to the home. Data transmissions over distance are bound by intrinsic communication delays which can be significant enough to deem the activity unfeasible. Here we describe an approach that combines unilateral robotic telerehabilitation and serious games. This approach has a modular and distributed design that permits different types of robots to interact without substantial code changes. We demonstrate the approach through an online multiplayer game. Two users can remotely interact with each other with no force exchanges, while a smoothing and prediction algorithm compensates motions for the delay in the Internet connection. We demonstrate that this approach can successfully compensate for data transmission delays, even when testing between the United States and Brazil. This paper presents the initial experimental results, which highlight the performance degradation with increasing delays as well as improvements provided by the proposed algorithm, and discusses planned future developments.

A novel protocol to evaluate ankle movements during reaching tasks using pediAnklebot

The aim of the study is to design a novel protocol to characterize the ankle movements during dorsal and plantar flexion reaching tasks using the pediAnklebot. Five healthy children were instructed to control a pointer and hit targets appearing on the monitor, by moving their ankle alternatively up and down. The protocol consisted of 60 targets, 30 up and 30 down, reachable via dorsiflexion and plantarflexion movements, respectively. Ankle angular displacements and torques were gathered by encoders and load cells embedded in the robot. Ankle motor performance was evaluated by means of kinematic, submovements and dynamic indices. Results suggest that (i) plantarflexion movements are faster and more accurate than the dorsiflexion ones, but children are able to perform with a higher level of smoothness the latter ones; (ii) children are able to stop the ankle movement more easily at the end of dorsiflexion rather than plantarflexion; (iii) the central nervous system plans plantarflexion and dorsiflexion movements with the same efficiency; (iv) children apply different torque levels during the two motor tasks and they cannot balance the inversion and eversion moments during dorsiflexion. These findings provide an important starting point for the assessment of a reference baseline of motor indices for the ankle joint.

Robotic Assistance for Training Finger Movement Using a Hebbian Model: A Randomized Controlled Trial

BACKGROUND

Robots that physically assist movement are increasingly used in rehabilitation therapy after stroke, yet some studies suggest robotic assistance discourages effort and reduces motor learning.

OBJECTIVE

To determine the therapeutic effects of high and low levels of robotic assistance during finger training.

METHODS

We designed a protocol that varied the amount of robotic assistance while controlling the number, amplitude, and exerted effort of training movements. Participants (n = 30) with a chronic stroke and moderate hemiparesis (average Box and Blocks Test 32 ± 18 and upper extremity Fugl-Meyer score 46 ± 12) actively moved their index and middle fingers to targets to play a musical game similar to GuitarHero 3 h/wk for 3 weeks. The participants were randomized to receive high assistance (causing 82% success at hitting targets) or low assistance (55% success). Participants performed ~8000 movements during 9 training sessions.

RESULTS

Both groups improved significantly at the 1-month follow-up on functional and impairment-based motor outcomes, on depression scores, and on self-efficacy of hand function, with no difference between groups in the primary endpoint (change in Box and Blocks). High assistance boosted motivation, as well as secondary motor outcomes (Fugl-Meyer and Lateral Pinch Strength)-particularly for individuals with more severe finger motor deficits. Individuals with impaired finger proprioception at baseline benefited less from the training.

CONCLUSIONS

Robot-assisted training can promote key psychological outcomes known to modulate motor learning and retention. Furthermore, the therapeutic effectiveness of robotic assistance appears to derive at least in part from proprioceptive stimulation, consistent with a Hebbian plasticity model.

Research on Safety and Compliance of a New Lower Limb Rehabilitation Robot

The lower limb rehabilitation robot is an application of robotic technology for stroke people with lower limb disabilities. A new applicable and effective sitting/lying lower limb rehabilitation robot (LLR-Ro) is proposed, which has the mechanical limit protection, the electrical limit protection, and the software protection to prevent the patient from the secondary damage. Meanwhile, as a new type of the rehabilitation robots, its hip joint rotation ranges are different in the patient sitting training posture and lying training posture. The mechanical leg of the robot has a variable workspace to work in both training postures. So, if the traditional mechanical limit and the electrical limit cannot be used in the hip joint mechanism design, a follow-up limit is first proposed to improve the compatibility of human-machine motion. Besides, to eliminate the accident interaction force between the patient and LLR-Ro in the process of the passive training, an amendment impedance control strategy based on the position control is proposed to improve the compliance of the LLR-Ro. A simulation experiment and an experiment with a participant show that the passive training of LLR-Ro has compliance.

Enhancing reading abilities of learners with intellectual impairments through computer technology

BACKGROUND

Developments in the teaching of children with disabilities support pedagogy that emphasises learners' strengths as opposed to their assumed deficiencies. Educators and mediators who advocate this view continually strive for tools and methodologies that enhance learner participation in academic environments. Computer technology is one of the tools recognised for its potential to enrich learning experiences of learners with an intellectual impairment.

OBJECTIVES

We sought to assess the influence of text-to-speech stories on the reading ability of intellectually challenged learners.

METHOD

A qualitative action research study that involves learners at a special school in Cape Town, South Africa. Pre- and post-test data of the reading performance of learners are analysed with a focus on how they demonstrate change.

RESULTS

Although no claims can be made about the explicit influence on reading performance, computer-assisted learning has the potential in isolating reading processes that classroom-based interventions can address. In addition, computers enhance motivation and enthusiasm to learn.

CONCLUSION

A need for education based on inclusion and positive differentiation remains the key driver in any educational interventions.

Can Lokomat therapy with children and adolescents be improved? An adaptive clinical pilot trial comparing Guidance force, Path control, and FreeD

Background

Robot-assisted gait therapy is increasingly being used in pediatric neurorehabilitation to complement conventional physical therapy. The robotic device applied in this study, the Lokomat (Hocoma AG, Switzerland), uses a position control mode (Guidance Force), where exact positions of the knee and hip joints throughout the gait cycle are stipulated. Such a mode has two disadvantages: Movement variability is restricted, and patients tend to walk passively. Kinematic variability and active participation, however, are crucial for motor learning. Recently, two new control modes were introduced. The Path Control mode allows the patient to walk within a virtual tunnel surrounding the ideal movement trajectory. The FreeD was developed to support weight shifting through mediolaterally moveable pelvis and leg cuffs. The aims of this study were twofold: 1) To present an overview of the currently available control modes of the Lokomat. 2) To evaluate if an increase in kinematic variability as provided by the new control modes influenced leg muscle activation patterns and intensity, as well as heart rate while walking in the Lokomat.

Methods

In 15 adolescents with neurological gait disorders who walked in the Lokomat, 3 conditions were compared: Guidance Force, Path Control, and FreeD. We analyzed surface electromyographic (sEMG) activity from 5 leg muscles of the more affected leg and heart rate. Muscle activation patterns were compared with norm curves.

Results

Several muscles, as well as heart rate, demonstrated tendencies towards a higher activation during conditions with more kinematic freedom. sEMG activation patterns of the M.rectus femoris and M.vastus medialis showed the highest similarity to over-ground walking under Path Control, whereas walking under FreeD led to unphysiological muscle activation in the tested sample.

Conclusions

Results indicate that especially Path Control seems promising for adolescent patients undergoing neurorehabilitation, as it increases proximal leg muscle activity while facilitating a physiological muscle activation. Therefore, this may be a solution to increase kinematic variability and patients’ active participation in robot-assisted gait training.

Electronic supplementary material

The online version of this article (doi:10.1186/s12984-017-0287-1) contains supplementary material, which is available to authorized users.

A Novel Spatial Feature for the Identification of Motor Tasks Using High-Density Electromyography

Estimation of neuromuscular intention using electromyography (EMG) and pattern recognition is still an open problem. One of the reasons is that the pattern-recognition approach is greatly influenced by temporal changes in electromyograms caused by the variations in the conductivity of the skin and/or electrodes, or physiological changes such as muscle fatigue. This paper proposes novel features for task identification extracted from the high-density electromyographic signal (HD-EMG) by applying the mean shift channel selection algorithm evaluated using a simple and fast classifier-linear discriminant analysis. HD-EMG was recorded from eight subjects during four upper-limb isometric motor tasks (flexion/extension, supination/pronation of the forearm) at three different levels of effort. Task and effort level identification showed very high classification rates in all cases. This new feature performed remarkably well particularly in the identification at very low effort levels. This could be a step towards the natural control in everyday applications where a subject could use low levels of effort to achieve motor tasks. Furthermore, it ensures reliable identification even in the presence of myoelectric fatigue and showed robustness to temporal changes in EMG, which could make it suitable in long-term applications.

Adaptive control of an actuated-ankle-foot-orthosis

This paper deals with the control of an active ankle foot orthosis (AAFO) to assist the gait of paretic patients. The AAFO system is driven by both, the residual human torque delivered by the muscles spanning the ankle joint and the AAFO's actuator's torque. A projection-based model reference adaptive control is proposed to assist dorsiflexion and plantar-flexion of the ankle joint during daily living walking activities. Unlike most classical model-based controllers, the proposed one does not require any prior estimation of the system's (foot-AAFO) parameters. The ankle reference trajectory was extracted from healthy subjects gait activities in a clinical environment. The input-to-state stability of the foot-AAFO system with respect to a bounded human muscular torque is proved in closed-loop based on a Lyapunov analysis. Preliminary experimental results with a healthy subject walking on a treadmill, show satisfactory results in terms of tracking performance and ankle assistance throughout the gait cycle.

Use of Lower-Limb Robotics to Enhance Practice and Participation in Individuals With Neurological Conditions

PURPOSE

To review lower-limb technology currently available for people with neurological disorders, such as spinal cord injury, stroke, or other conditions. We focus on 3 emerging technologies: treadmill-based training devices, exoskeletons, and other wearable robots.

SUMMARY OF KEY POINTS

Efficacy for these devices remains unclear, although preliminary data indicate that specific patient populations may benefit from robotic training used with more traditional physical therapy. Potential benefits include improved lower-limb function and a more typical gait trajectory.

STATEMENT OF CONCLUSIONS

Use of these devices is limited by insufficient data, cost, and in some cases size of the machine. However, robotic technology is likely to become more prevalent as these machines are enhanced and able to produce targeted physical rehabilitation.

RECOMMENDATIONS FOR CLINICAL PRACTICE

Therapists should be aware of these technologies as they continue to advance but understand the limitations and challenges posed with therapeutic/mobility robots.