Posts Tagged Neurorehabilitation

[ARTICLE] Functional electrical stimulation therapy for restoration of motor function after spinal cord injury and stroke: a review – Full Text

Abstract

Functional electrical stimulation is a technique to produce functional movements after paralysis. Electrical discharges are applied to a person’s muscles making them contract in a sequence that allows performing tasks such as grasping a key, holding a toothbrush, standing, and walking. The technology was developed in the sixties, during which initial clinical use started, emphasizing its potential as an assistive device. Since then, functional electrical stimulation has evolved into an important therapeutic intervention that clinicians can use to help individuals who have had a stroke or a spinal cord injury regain their ability to stand, walk, reach, and grasp. With an expected growth in the aging population, it is likely that this technology will undergo important changes to increase its efficacy as well as its widespread adoption. We present here a series of functional electrical stimulation systems to illustrate the fundamentals of the technology and its applications. Most of the concepts continue to be in use today by modern day devices. A brief description of the potential future of the technology is presented, including its integration with brain–computer interfaces and wearable (garment) technology.

Background

Losing the ability to move voluntarily can have devastating consequences for the independence and quality of life of a person. Stroke and spinal cord injury (SCI) are two important causes of paralysis which affect thousands of individuals around the world. Extraordinary efforts have been made in an attempt to mitigate the effects of paralysis. In recent years, rehabilitation of voluntary movement has been enriched by the constant integration of new neurophysiological knowledge about the mechanisms behind motor function recovery. One central concept that has improved neurorehabilitation significantly is neuroplasticity, the ability of the central nervous system to reorganize itself during the acquisition, retention, and consolidation of motor skills [1]. In this document, we present one of the interventions that has flourished as a consequence of our increased understanding of the plasticity of the nervous system: functional electrical stimulation therapy or FEST. The document, which is not a systematic review, is intended to describe early work that played an important historical role in the development of this field, while providing a general understanding of the technology and applications that continue to be used today. Readers interested in systematic reviews of functional electrical simulation (FES) are directed to other sources (e.g., [2,3,4]).[…]

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figure4
Textile-based neuroprostheses. a Finger extension produced using a shirt designed for implementing a neuroprosthesis for reaching and grasping. The garment includes rectangular areas (dark grey patches) made of conductive yarn that function as electrodes. b Forward reaching. Details can be found in [65]

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[Abstract] The medical avatar and its role in neurorehabilitation and neuroplasticity: A review

Abstract

BACKGROUND:One of the most interesting emerging medical devices is the medical avatar – a digital representation of the patient that can be used toward myriad ends, the full potential of which remains to be explored. Medical avatars have been instantiated as telemedical tools used to establish a representation of the patient in tele-space, upon which data about the patient’s health can be represented and goals and progress can be visually tracked. Manipulation of the medical avatar has also been explored as a means of increasing motivation and inducing neural plasticity.

OBJECTIVE:The article reviews the literature on body representation, simulation, and action-observation and explores how these components of neurorehabilitation are engaged by an avatar-based self-representation.

METHODS:Through a review of the literature on body representation, simulation, and action-observation and a review of how these components of neurorehabilitation can be engaged and manipulated with an avatar, the neuroplastic potential of the medical avatar is explored. Literature on the use of the medical avatar for neurorehabilitation is also reviewed.

RESULTS:This review demonstrates that the medical avatar has vast potentialities in neurorehabilitation and that further research on its use and effect is needed.

Source: https://content.iospress.com/articles/neurorehabilitation/nre203063

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[Abstract + References] The Efficiency, Efficacy, and Retention of Task Practice in Chronic Stroke

Abstract

In motor skill learning, larger doses of practice lead to greater efficacy of practice, lower efficiency of practice, and better long-term retention. Whether such learning principles apply to motor practice after stroke is unclear. Here, we developed novel mixed-effects models of the change in the perceived quality of arm movements during and following task practice. The models were fitted to data from a recent randomized controlled trial of the effect of dose of task practice in chronic stroke. Analysis of the models’ learning and retention rates demonstrated an increase in efficacy of practice with greater doses, a decrease in efficiency of practice with both additional dosages and additional bouts of training, and fast initial decay following practice. Two additional effects modulated retention: a positive “self-practice” effect, and a negative effect of dose. Our results further suggest that for patients with sufficient arm use post-practice, self-practice will further improve use.

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[ARTICLE] Timing-dependent effects of transcranial direct current stimulation with mirror therapy on daily function and motor control in chronic stroke: a randomized controlled pilot study – Full Text

Abstract

Background

The timing of transcranial direct current stimulation (tDCS) with neurorehabilitation interventions may affect its modulatory effects. Motor function has been reported to be modulated by the timing of tDCS; however, whether the timing of tDCS would also affect restoration of daily function and upper extremity motor control with neurorehabilitation in stroke patients remains largely unexplored. Mirror therapy (MT) is a potentially effective neurorehabilitation approach for improving paretic arm function in stroke patients. This study aimed to determine whether the timing of tDCS with MT would influence treatment effects on daily function, motor function and motor control in individuals with chronic stroke.

Methods

This study was a double-blinded randomized controlled trial. Twenty-eight individuals with chronic stroke received one of the following three interventions: (1) sequentially combined tDCS with MT (SEQ), (2) concurrently combined tDCS with MT (CON), and (3) sham tDCS with MT (SHAM). Participants received interventions for 90 min/day, 5 days/week for 4 weeks. Daily function was assessed using the Nottingham Extended Activities of Daily Living Scale. Upper extremity motor function was assessed using the Fugl-Meyer Assessment Scale. Upper extremity motor control was evaluated using movement kinematic assessments.

Results

There were significant differences in daily function between the three groups. The SEQ group had greater improvement in daily function than the CON and SHAM groups. Kinematic analyses showed that movement time of the paretic hand significantly reduced in the SEQ group after interventions. All three groups had significant improvement in motor function from pre-intervention to post-intervention.

Conclusion

The timing of tDCS with MT may influence restoration of daily function and movement efficiency of the paretic hand in chronic stroke patients. Sequentially applying tDCS prior to MT seems to be advantageous for enhancing daily function and hand movement control, and may be considered as a potentially useful strategy in future clinical application.

Introduction

Stroke remains one of the leading causes of long-term disability [1]. Most stroke patients have difficulties performing every day activities due to paresis of upper limbs, which results in impaired activities of daily living (ADL) and reduced quality of life [23]. Identifying strategies that can facilitate functional recovery is thus an important goal for stroke rehabilitation. In recent years, several neurorehabilitation approaches have been developed to augment functional recovery, for example repetitive, task-oriented training and non-invasive brain stimulation (NIBS) [45]. Repetitive, task-oriented training emphasizes repetitive practice of task-related arm movements to facilitate motor relearning and restore correct movement patterns [6]. On the other hand, non-invasive brain simulation aims to maximize brain plasticity by externally applying electrical stimulation to modulate cortical excitability [7]. Since these two types of approaches individually have been shown to improve stroke recovery, it has been proposed that a synergistic approach that combines both of them may further augment overall treatment effects [89].

Mirror therapy (MT) is one type of repetitive task-oriented training that has been widely used in clinical and research settings [10]. During MT training, a mirror is positioned in between the paretic and non-paretic arm. The paretic arm is behind the mirror and participants can only see the non-paretic arm and its mirror reflection. Participants are required to focus their attention on the mirror reflection and imagine it is the paretic arm while performing bilateral movements as simultaneously as possible. This mirrored visual feedback is hypothesized to restore the efferent-afferent loop that is damaged after stroke and facilitate re-learning of correct movement patterns [11]. MT has been demonstrated to reduce arm impairment and improve sensorimotor function and quality of life in individuals with stroke [10,11,12,13].

Transcranial direct current stimulation (tDCS) is a commonly used NIBS technique in stroke rehabilitation. tDCS applies weak direct current to the scalp to modulate brain excitability [14]. This weak direct current gradually changes neural membrane potentials to facilitate depolarization (excitation) or hyper-polarization (inhibition) of the neurons to enhance plasticity of the brain [15]. tDCS has been demonstrated to modulate neural networks and enhance motor learning in stroke patients [716,17,18]. Although tDCS can be used alone, it is often combined with other rehabilitation approaches to boost responses of the brain to therapies [81920]. A recent meta-analysis further showed that combining tDCS with rehabilitation interventions could produce greater treatment effects on recovery of motor function than tDCS alone in stroke patients [21].

Combining tDCS with MT is a potentially promising approach to not only augment neural responses of the brain but also increase treatment benefits of MT. Nevertheless, one crucial factor that needs to be considered when combining tDCS with MT is the timing of tDCS [22]. tDCS can be applied prior to MT (i.e., offline tDCS) or concurrently with MT (i.e., online tDCS). To our knowledge, only two studies have examined the synergistic effects of combined tDCS with MT in chronic stroke patients [2324]. Cho et al. (2015) applied tDCS prior to MT or motor training without mirror reflection. They found significant improvements in manual dexterity and grip strength in the combined tDCS with MT group, suggesting that sequentially applying tDCS prior to MT could improve motor function. By contrast, Jin et al. (2019) delivered tDCS prior to or concurrently with MT and found advantageous effects on hand function in the concurrent tDCS with MT group. The conflicting results between these two studies indicated further needs to explore the interaction effects of the timing of tDCS with MT to determine the optimal combination strategy.

The important factor to consider when examining the effects of combined tDCS with MT is the treatment outcomes, especially for outcomes that are related to daily activities. ADL such as the basic ADL and complex instrumental ADL (IADL) are essential for independent living and well-being of stroke patients. Therefore, restoring daily function should be one of the priority goals of stroke rehabilitation. However, the previous two studies only examined the effects of combined tDCS with MT on motor function [2324]. No studies to date have examined the timing-dependent effects of tDCS with MT on daily function in chronic stroke patients. Whether the timing of tDCS can affect restoration of daily function with MT remains uncertain.

In addition to daily function, investigating arm movement kinematics changes with respect to the timing of tDCS with MT is also critical for determining the optimal combination strategy. Movement kinematics of the arms can provide information of whether true behavioral changes or compensation strategies occur during training [2526]. However, the two previous studies included only clinical motor function measurements [2324]. While these clinical measurements can inform clinicians/researchers of motor function changes, they may not necessarily capture spatial and temporal characteristics of movement as well as motor control strategies changes after the combined interventions [2627]. Assessing movement kinematics changes with respect to the timing of tDCS with MT would help to unravel the benefits of combined approach on motor control of the paretic arm.

The purpose of this study was to examine the timing-dependent effects of tDCS with MT on daily function, upper extremity motor function and motor control in chronic stroke patients. The tDCS was applied sequentially prior to MT (i.e., sequentially combined tDCS with MT group, SEQ) or concurrently with MT (i.e., concurrently combined tDCS with MT, CON). The sham tDCS with MT was used as the control condition. In addition to motor function outcomes, we further included the ADL/IADL measurement and movement kinematics assessments. We hypothesized that the SEQ and COM groups would demonstrate differential improvements in daily function, motor function and motor control.[…]

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Source: https://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-020-00722-1

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[ARTICLE] A Spatial-Motion Assist-as-Needed Controller for the Passive, Active, and Resistive Robot-Aided Rehabilitation of the Wrist – Full Text PDF

Abstract

Demand for robot-assisted therapy has increased at every stage of the neurorehabilitation recovery. This paper presents a controller that is suitable for the assist-as-needed (AAN) training of the wrist when performing the spatial motion. A compact wrist exoskeleton robot is presented to realize the AAN controller. This wrist robot includes series elastic actuators with high torque-to-weight ratios to provide accurate force control required for the AAN controller. In addition to assist-as-needed rehabilitation, the parameters of the AAN controller can be adjusted to deliver passive, active, or resistive rehabilitation. Experimental results demonstrate that the proposed AAN controller can provide the total solution to cover each stage of wrist spatial-motion rehabilitation.

(a) Orientation of the wrist and handlebar (b) Omni-directional stiffness K and omni-directional damping B

(a) Orientation of the wrist and handlebar (b) Omni-directional stiffness K and omni-directional damping B

via (PDF) A Spatial-Motion Assist-as-Needed Controller for the Passive, Active, and Resistive Robot-Aided Rehabilitation of the Wrist

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[ARTICLE] The Promotoer, a brain-computer interface-assisted intervention to promote upper limb functional motor recovery after stroke: a study protocol for a randomized controlled trial to test early and long-term efficacy and to identify determinants of response – Full Text

Abstract

Background

Stroke is a leading cause of long-term disability. Cost-effective post-stroke rehabilitation programs for upper limb are critically needed. Brain-Computer Interfaces (BCIs) which enable the modulation of Electroencephalography (EEG) sensorimotor rhythms are promising tools to promote post-stroke recovery of upper limb motor function. The “Promotoer” study intends to boost the application of the EEG-based BCIs in clinical practice providing evidence for a short/long-term efficacy in enhancing post-stroke hand functional motor recovery and quantifiable indices of the participants response to a BCI-based intervention. To these aims, a longitudinal study will be performed in which subacute stroke participants will undergo a hand motor imagery (MI) training assisted by the Promotoer system, an EEG-based BCI system fully compliant with rehabilitation requirements.

Methods

This longitudinal 2-arm randomized controlled superiority trial will include 48 first ever, unilateral, subacute stroke participants, randomly assigned to 2 intervention groups: the BCI-assisted hand MI training and a hand MI training not supported by BCI. Both interventions are delivered (3 weekly session; 6 weeks) as add-on regimen to standard intensive rehabilitation. A multidimensional assessment will be performed at: randomization/pre-intervention, 48 h post-intervention, and at 1, 3 and 6 month/s after end of intervention. Primary outcome measure is the Fugl-Meyer Assessment (FMA, upper extremity) at 48 h post-intervention. Secondary outcome measures include: the upper extremity FMA at follow-up, the Modified Ashworth Scale, the Numeric Rating Scale for pain, the Action Research Arm Test, the National Institute of Health Stroke Scale, the Manual Muscle Test, all collected at the different timepoints as well as neurophysiological and neuroimaging measures.

Discussion

We expect the BCI-based rewarding of hand MI practice to promote long-lasting retention of the early induced improvement in hand motor outcome and also, this clinical improvement to be sustained by a long-lasting neuroplasticity changes harnessed by the BCI-based intervention. Furthermore, the longitudinal multidimensional assessment will address the selection of those stroke participants who best benefit of a BCI-assisted therapy, consistently advancing the transfer of BCIs to a best clinical practice.

Trial registration

Name of registry: BCI-assisted MI Intervention in Subacute Stroke (Promotoer).

Trial registration number: NCT04353297; registration date on the ClinicalTrial.gov platform: April, 15/2020.

Peer Review reports

Background

Stroke is a major public health and social care concern worldwide [1]. The upper limb motor impairment commonly persists after stroke, and it represents the major contribution to long-term disability [2]. It has been estimated that the main clinical predictor of whether a patient would come back to work is the degree of upper extremity function [3]. Despite the intensive rehabilitation, the variability in the nature and extent of upper limb recovery remains a crucial factor affecting rehabilitation outcomes [4].

Electroencephalography (EEG)-based Brain-Computer Interface (BCI) is an emerging technology that enables a direct translation of brain activity into motor action [5]. Recently, EEG-based BCIs have been recognized as potential tools to promote functional motor recovery of upper limbs after stroke (for review see [6]). Several randomized controlled trials have shown that stroke patients can learn to modulate their EEG sensorimotor rhythms [7] to control external devices and this practice might facilitate neurological recovery both in subacute and chronic stroke phase [8,9,10].

We were previously successful in the design and validation of an EEG sensorimotor rhythms–based BCI combined with realistic visual feedback of upper limb to support hand motor imagery (MI) practice in stroke patients [1112]. Our previous pilot randomized controlled study [8] with the participation of 28 subacute stroke patients with severe motor deficit, suggested that 1 month BCI-assisted MI practice as an add-on intervention to the usual rehabilitation care was superior with respect to the add-on, 1 month MI training alone (ie., without BCI support) in improving hand functional motor outcomes (indicated by the significantly higher mean score at upper extremity Fugl-Meyer scale in the BCI with respect to control group). A greater involvement of the ipsilesional hemisphere, as reflected by a stronger motor-related EEG oscillatory activity and connectivity in response to MI of the paralyzed trained hand was also observed only in the BCI-assisted MI training condition. These promising findings corroborated the idea that a relatively low-cost technique (i.e. EEG-based BCI) can be exploited to deliver an efficacious rehabilitative intervention such as MI training and prompted us to undertake a translational effort by implementing an all-in-one BCI-supported MI training station– the Promotoer [13].

Yet, important questions remain to be addressed in order to improve the clinical viability of BCIs such as defining whether the expected early improvements in functional motor outcomes induced by the BCI-assisted MI training in subacute stroke [8] can be sustained in a long-term as it has been shown for other BCI-based approaches in chronic stroke patients [1014]. This requires advancements in the knowledge on brain functional re-organization early after stroke and on how this re-organization would correlate with the functional motor outcome (evidence-base medicine). Last but not least, the definition of the determinants of the patients response to treatment is paramount to optimize the process of personalized medicine in rehabilitation. We will address these questions by carrying out a randomized trial to eventually establish the fundamentals for a cost-effective use of EEG-based BCI technology to deliver a rehabilitative intervention such as the MI in hospitalized stroke patients.

Aim and hypotheses

The “Promotoer” study is a randomized controlled trial (RCT) designed to provide evidence for a significant early improvement of hand motor function induced by the BCI-assisted MI training operated via the Promotoer and for a persistency (up to 6 months) of such improvement. Task-specific training was reported to induce long-term improvements in arm motor function after stroke [15,16,17]. Thus, our hypothesis is that the BCI-based rewarding of hand MI tasks would promote long-lasting retention of early induced positive effect on motor performance with respect to MI tasks practiced in an open loop condition (ie, without BCI). Accordingly, the primary aim of the “Promotoer” RCT will be first to determine whether the BCI based intervention (MI-BCI) administered by means of a BCI system fully compatible with a clinical setting (the Promotoer), is superior to a non-BCI assisted MI training (MI Control) in improving hand motor function outcomes in sub-acute stroke patients admitted to the hospital for their standard rehabilitation care; secondly, we will test whether the efficacy of BCI-based intervention on hand motor function outcomes is sustained long-term after the end of intervention (6 months follow-up). A further hypothesis is that such clinical improvement would be sustained by a long-lasting neuroplasticity changes as harnessed by the BCI–based intervention. This hypothesis rises from current evidence for an early enhancement of post-stroke plastic changes enabled by BCI-based trainings [8,9,10]. To test this hypothesis, a longitudinal assessment of the brain network organization derived from advanced EEG signal processing (secondary objective) will be performed.

The heterogeneity of stroke makes prediction of treatment responders a great challenge [18]. The potential value of a combination of neurophysiological and neuroimaging biomarkers with the clinical assessment in predicting post-stroke motor recovery has been recently highlighted [19]. Our hypothesis is that the longitudinal combined functional, neurophysiological and neuroimaging assessment over 6 months from the intervention will allow for insights into biomarkers and potential predictors of patients response to the BCI-Promotoer training (secondary aim). To this purpose, well-recognized factors contributing to recovery after stroke such as the relation between clinical profile, lesion characteristics and patterns of post-stroke motor cortical re-organization (eg., ipsilesional/contralesional primary and non-primary motor areas, cortico-spinal tract integrity, severity of motor deficits at baseline; for review see [19]) will be taken into account.[…}

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figure2
The Promotoer system. The Promoter is equipped with a computer, a commercial wireless EEG/EMG system (g.MOBIlab, g.tec medical engineering GmbH Austria), a screen for the therapist feedback (for the electroencephalographic – EEG activity and electromyographic- EMG activity monitoring) and screen for the ecological feedback to the participant; this ecological feedback is delivered by means of a custom software program that provides for (personalized) visual representation of the participant’s own hands. As such, this software allows the therapists to create an artificial reproduction of a given participant’s hand and forearm by adjusting a digitally created image in shape, size, skin color and orientation to match as much as possible the real hand and arm of the participant. Real-time feedback is provided by means of BCI2000 software [40]. The degree of EEG desynchronization over selected electrodes within selected frequencies (BCI control features) determines the vertical velocity of the cursor on the therapist’s screen and it operates the “virtual” hand software accordingly. The image is original as it is owned by the authors

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[Abstract] Can robotic gait rehabilitation plus Virtual Reality affect cognitive and behavioural outcomes in patients with chronic stroke? A randomized controlled trial involving three different protocols

Abstract

Background

The rehabilitation of cognitive and behavioral abnormalities in individuals with stroke is essential for promoting patient’s recovery and autonomy. The aim of our study is to evaluate the effects of robotic neurorehabilitation using Lokomat with and without VR on cognitive functioning and psychological well-being in stroke patients, as compared to traditional therapy.

Methods

Ninety stroke patients were included in this randomized controlled clinical trial. The patients were assigned to one of the three treatment groups, i.e. the Robotic Rehabilitation group undergoing robotic rehab with VR (RRG+VR), the Robotic Rehabilitation Group (RRG-VR) using robotics without VR, and the Conventional Rehabilitation group (CRG) submitted to conventional physiotherapy and cognitive treatment.

Results

The analysis showed that either the robotic training (with and without VR) or the conventional rehabilitation led to significant improvements in the global cognitive functioning, mood, and executive functions, as well as in activities of daily living. However, only in the RRG+VR we observed a significant improvement in cognitive flexibility and shifting skills, selective attention/visual research, and quality of life, with regard to the perception of the mental and physical state.

Conclusion

Our study shows that robotic treatment, especially if associated with VR, may positively affect cognitive recovery and psychological well-being in patients with chronic stroke, thanks to the complex interation between movement and cognition.

Source: https://www.sciencedirect.com/science/article/abs/pii/S1052305720304122

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[Abstract] How brain imaging provides predictive biomarkers for therapeutic success in the context of virtual reality cognitive training

Highlight

VR environments help improve rehabilitation of impaired complex cognitive functions

Combining neuroimaging and VR boosts ecological validity, generates practical gains

These are the first neurofunctional predictive biomarkers of VR cognitive training

Abstract

As Virtual reality (VR) is increasingly used in neurological disorders such as stroke, traumatic brain injury, or attention deficit disorder, the question of how it impacts the brain’s neuronal activity and function becomes essential. VR can be combined with neuroimaging to offer invaluable insight into how the targeted brain areas respond to stimulation during neurorehabilitation training. That, in turn, could eventually serve as a predictive marker for therapeutic success. Functional magnetic resonance imaging (fMRI) identified neuronal activity related to blood flow to reveal with a high spatial resolution how activation patterns change, and restructuring occurs after VR training. Portable and quiet, electroencephalography (EEG) conveniently allows the clinician to track spontaneous electrical brain activity in high temporal resolution. Then, functional near-infrared spectroscopy (fNIRS) combines the spatial precision level of fMRIs with the portability and high temporal resolution of EEG to constitute an ideal measuring tool in virtual environments (VEs). This narrative review explores the role of VR and concurrent neuroimaging in cognitive rehabilitation.

Source: https://www.sciencedirect.com/science/article/abs/pii/S0149763420304218?dgcid=rss_sd_all&utm_campaign=RESR_MRKT_Researcher_inbound&utm_medium=referral&utm_source=researcher_app

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[ARTICLE] Key components of mechanical work predict outcomes in robotic stroke therapy – Full Text

Abstract

Background

Clinical practice typically emphasizes active involvement during therapy. However, traditional approaches can offer only general guidance on the form of involvement that would be most helpful to recovery. Beyond assisting movement, robots allow comprehensive methods for measuring practice behaviors, including the energetic input of the learner. Using data from our previous study of robot-assisted therapy, we examined how separate components of mechanical work contribute to predicting training outcomes.

Methods

Stroke survivors (n = 11) completed six sessions in two-weeks of upper extremity motor exploration (self-directed movement practice) training with customized forces, while a control group (n = 11) trained without assistance. We employed multiple regression analysis to predict patient outcomes with computed mechanical work as independent variables, including separate features for elbow versus shoulder joints, positive (concentric) and negative (eccentric), flexion and extension.

Results

Our analysis showed that increases in total mechanical work during therapy were positively correlated with our final outcome metric, velocity range. Further analysis revealed that greater amounts of negative work at the shoulder and positive work at the elbow as the most important predictors of recovery (using cross-validated regression, R2 = 52%). However, the work features were likely mutually correlated, suggesting a prediction model that first removed shared variance (using PCA, R2 = 65–85%).

Conclusions

These results support robotic training for stroke survivors that increases energetic activity in eccentric shoulder and concentric elbow actions.

Background

Assistance is often provided to aid limb movement during the rehabilitation process of stroke survivors. Many clinical researchers agree that active participation enhances recovery, and the goal of therapy should be to maximize “involvement” [12]. Too much assistance can actually discourage patient effort [3]. However, measurement of the degree to which patients are actually active is often difficult. Advances in rehabilitation devices allow for the measurement of forces and motion to better monitor patient activity. Here we investigate how upper limb mechanics during training relate to recovery.

Current tools for measuring physical activity during therapy offer limited information for describing interaction with the external environment or agent. While studies have shown that the intensity of therapy influences patient improvement, researchers have relied on simple metrics related to experimental conditions (e.g. movement repetitions, time-on-task, and therapy dosage) [45]. More sophisticated tools have been used to directly measure energetic contributions during therapy, such as oxygen consumption devices to measure metabolic cost [6] or electromyography to measure muscle activity [78]. However, such measures do not account for the time-varying force-motion relationships that occur during assisted movement. Robots easily measure both kinematic and kinetic variables facilitating the computation of energetic contributions in terms of mechanical power and work.

While energetic descriptions of movement have been widely studied, it has mainly focused on cyclic [9] or sustained movements, such as walking. Researchers have computed work and power to characterize normal and abnormal gait patterns [1011], to evaluate robot-assisted locomotion [12], and to reduce energetic costs when using exoskeletons [13]. Recently our work has focused on robotic augmentation of upper limb dynamics to facilitate vigorous movement during practice [1415]. We showed that stroke survivors increase total work output during force training [16]. Our intervention was fundamentally different than many previous strategies in that patients trained over a broader range of movements. In contrast to reaching studies [1718], such self-directed exploration allows for the examination of how energetics might depend on different force and motion states.

To better evaluate the variation in patient energetics, we believe more comprehensive measures are required beyond total expenditure of power or work. Researchers have also examined compartmentalized work and power measures in normal limb behaviors, for example, associating magnitudes of mechanical energy (e.g. positive/concentric and negative/eccentric work) with movement actions (e.g. flexion and extension) at individual joints [19]. Motor impairments due to stroke are also typically described in the context of motor actions of the limb. For example, stroke survivors exhibit abnormal flexion and extension synergies [20] and alterations in concentric and eccentric muscle contractions [2122]. As such, impairments can be associated with subcomponents of work and power. As patients interact differently in response to forces, subcomponents of work and power could reveal individual differences in involvement.

An emerging trend in rehabilitation is to identify certain factors that predict individual improvement in response to therapy. Researchers have identified patient biomarkers (impairment level, neurophysiological) correlated to patient outcomes providing better recommendations for therapy [23,24,25]. Similarly, our goal is to determine if particular types of work are more important to patient recovery. Such evaluation could inform decisions on design strategies and optimize assistance to each individual. In contrast to previous studies which have relied on independent analyses of many individual predictors, our analysis goal necessitates more rigorous statistical methods to deal with potentially related work features. One possible solution is to employ multiple regression analysis which can identify features most important for prediction.

In this paper, we investigate how the energetic contributions of stroke survivors during robot-assisted training relate to upper limb recovery. We employ well-established methods of inverse dynamics to estimate the torques generated by each patient during self-directed motor exploration training with customized forces. These methods conveniently allow us to quantify the energetic involvement of each individual joint in terms of mechanical work. We then use multiple regression analysis to identify which components of work are most important for predicting recovery. We hypothesize that positive work (concentric) in elbow extension is the best predictor of outcome. This study provides a key preliminary step towards evaluating energetic descriptions of patient involvement which can inform methods for upper limb robotic therapy practice.

Methods

Study participants

This investigation considered data collected from a previous study that featured 22 stroke survivors [15]. The main inclusion criteria included: 1) chronic stroke (8+ months post-stroke) 2) hemiparesis with moderate to severe arm impairment measured by the upper extremity portion of the Fugl-Meyer Assessment (UEFM score of 15–50) 3) primary cortex involvement. Each individual gave informed consent in accordance with the Northwestern University Institutional Review Board (IRB).

Apparatus

Experiment participants were asked to operate a two-degree of freedom robotic device with the affected arm (Fig. 1a). A custom video display system (not shown) provided visual feedback of the location of the wrist as the arm moved in the horizontal plane. During movement, the weight of the arm was supported. Movement data was collected at 200 Hz and filtered using a 5th order Butterworth low pass filter with a 12 Hz cutoff. Using anthropometric measurements recorded from each participant, we computed inverse kinematic relationships to obtain elbow and shoulder joint angles corresponding to endpoint position data. The robot control and instrumentation were mediated by a Simulink-based XPC Target computer, with a basic rate of 1 kHz. The robot controller compensated for the dynamics of the robot arm. A force sensor attached to the end-effector measured the human-robot interaction forces.

figure1
Experimental design. a Stroke survivors performed self-directed motor exploration by moving the robot handle in the horizontal plane. Measurements of their limb motion and the interaction forces were used to estimate the positive (concentric) and negative (eccentric) mechanical work exerted in different directions of shoulder and elbow joint motion. b The probability distribution of each individual’s movement velocities during unassisted motor exploration (top; blue indicates lower probability, red indicates higher probability, black contour line represents the 90th percentile velocity coverage) formed the basis for the design of customized training forces (bottom; red arrows indicate the direction and relative magnitude of forces applied, colored contour lines represents Gaussian model fit to velocity data)

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[ARTICLE] Review of the effects of soft robotic gloves for activity-based rehabilitation in individuals with reduced hand function and manual dexterity following a neurological event – Full Text

Despite limited scientific evidence, there is an increasing interest in soft robotic gloves to optimize hand- and finger-related functional abilities following a neurological event. This review maps evidence on the effects and effectiveness of soft robotic gloves for hand rehabilitation and, whenever possible, patients’ satisfaction. A systematized search of the literature was conducted using keywords structured around three areas: technology attributes, anatomy, and rehabilitation. A total of 272 titles, abstracts, and keywords were initially retrieved, and data were extracted out of 13 articles. Six articles investigated the effects of wearing a soft robotic glove and eight studied the effect or effectiveness of an intervention with it. Some statistically significant and meaningful beneficial effects were confirmed with the 29 outcome measures used. Finally, 11 articles also confirmed users’ satisfaction with regard to the soft robotic glove, while some articles also noticed an increased engagement in the rehabilitation program with this technology. Despite the heterogeneity across studies, soft robotic gloves stand out as a safe and promising technology to improve hand- and finger-related dexterity and functional performance. However, strengthened evidence of the effects or effectiveness of such devices is needed before their transition from laboratory to clinical practice. 

The hand and fingers are essential organs to perform a multitude of functional tasks in daily life, particularly to grasp and handle objects. In fact, the movements performed with the hand to grasp and handle objects, which can solicit up to 19 articulations driven by 29 muscles,1 can be grouped into two broad categories: power and precision grasps. Power grasping requires an individual performing gross motor tasks to generate large forces to firmly hold an object. In contrast, precision grasping requires an individual performing fine motor tasks to generate multiple levels of force to hold an object. The power grasps can be further characterized into cylindrical, spherical, or hook grasps whereas the precision grasps can be further categorized into pinch, tripodal, or lumbrical grasps (Figure 1).2 Whenever sensorimotor impairments of the hand and fingers develop as a result of a neurological event (e.g. stroke, spinal cord injury, Parkinson’s disease),3 the ability to grasp becomes jeopardized to various extents and may negatively impact functional abilities, as well as social participation and life satisfaction.4


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Figure 1. Different types of power and precision grasps.

Despite intensive neurorehabilitation efforts, the likelihood of regaining optimal hand and finger-related functional abilities remains low following a neurological event. For examples, three months after a stroke, only 12% of survivors say they have no problem at all whereas 38% report major difficulties with hand and finger-related functional abilities,5,6 while 75% of individuals with a spinal cord injury at the cervical vertebral level (i.e. tetraplegia), who were asked which function they would most like to have restored, chose upper extremity function,7 with improvement in hand function being their highest-ranked goal.8 Therefore, it is no surprise that one of the most commonly expressed goals of individuals who have sustained a neurological event (i.e. stoke, tetraplegia) and rehabilitation professionals is to engage in neurorehabilitation interventions that can reduce hand and finger sensorimotor impairments, thus improving related functional abilities that are crucial for optimal social participation and life satisfaction.

Rehabilitation strategies designed to maximize hand and finger-related functional abilities are predominantly founded on activity-based therapy, integrating the principles of neuroplasticity.9 Such an approach requires these individuals to engage in meaningful hand- and finger-specific exercises that they must repeat intensively on a daily basis.10,11 In fact, to expect beneficial neuroplastic adaptations, animal studies focusing on gait suggest that up to 1000 to 2000 steps must be taken daily, whereas human studies focusing on grasping in stroke survivors suggest that at least 100 repetitions need to be completed daily.12 Although the evidence suggests the need, adhering to these principles13 remains challenging in clinical practice, especially given various time and productivity constraints. Indeed, it is common to observe in clinical practice that exercise programs are performed individually with direct supervision by a rehabilitation professional, which leads to productivity issues and limits the possibility of implementing interventions at high intensity.14,15 In fact, evidence suggests that the number of repetitions observed for upper extremity work in stroke survivors undergoing neurorehabilitation typically ranges between 12 and 60 repetitions per session, which is far below the number required to expect neuroplastic adaptations.16,17 In addition, recovery may be limited by lack of treatment time, due to the elevated demand for neurorehabilitation services and increased therapists’ workload, especially in publicly funded healthcare environments.18 As a result, individuals with sensorimotor deficits undergoing intensive functional rehabilitation may not achieve the full potential of their hand and fingers sensorimotor and related functional recovery and may reach a ‘recovery plateau’ earlier than expected during the rehabilitation process.

To overcome this challenge, the last decade has seen substantial progress in the development of soft robotic gloves that can facilitate hand and finger movements when performing activities of daily living (ADL) and instrumental activities (iADL) that require grasping objects.19 Moreover, these soft robotic gloves are predicted to be a promising adjunct neurorehabilitation intervention to potentiate the effects of conventional rehabilitation interventions and are now about to be introduced into clinical practice; their effects, however, remain uncertain due to a paucity of evidence. In this context, the present review aims to map, for the first time, the evidence of the effects of the soft robotic glove on the performance of hand- and finger-related functional activities (i.e. with vs. without the technology) and on hand and finger sensorimotor and related functional abilities (i.e. before vs. after an intervention using the technology), among individuals with hand and finger sensorimotor impairments and related disabilities and, whenever investigated, patients’ satisfaction related to the use of the soft robotic glove. Specifically, this review seeks to address the following objectives: (1) determine the effects of rehabilitation interventions using soft robotic gloves; and (2) determine the acceptability and the perceived usefulness of this technology.[…]

Continue —->  Review of the effects of soft robotic gloves for activity-based rehabilitation in individuals with reduced hand function and manual dexterity following a neurological event – Camille E Proulx, Myrka Beaulac, Mélissa David, Catryne Deguire, Catherine Haché, Florian Klug, Mario Kupnik, Johanne Higgins, Dany H. Gagnon, 2020

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