Posts Tagged upper limb

[ARTICLE] Soft Robotic Haptic Interface with Variable Stiffness for Rehabilitation of Neurologically Impaired Hand Function – Full Text

The human hand comprises complex sensorimotor functions that can be impaired by neurological diseases and traumatic injuries. Effective rehabilitation can bring the impaired hand back to a functional state because of the plasticity of the central nervous system to relearn and remodel the lost synapses in the brain. Current rehabilitation therapies focus on strengthening motor skills, such as grasping, employ multiple objects of varying stiffness so that affected persons can experience a wide range of strength training. These devices have limited range of stiffness due to the rigid mechanisms employed in their variable stiffness actuators. This paper presents a novel soft robotic haptic device for neuromuscular rehabilitation of the hand, which is designed to offer adjustable stiffness and can be utilized in both clinical and home settings. The device eliminates the need for multiple objects by employing a pneumatic soft structure made with highly compliant materials that act as the actuator of the haptic interface. It is made with interchangeable sleeves that can be customized to include materials of varying stiffness to increase the upper limit of the stiffness range. The device is fabricated using existing 3D printing technologies, and polymer molding and casting techniques, thus keeping the cost low and throughput high. The haptic interface is linked to either an open-loop system that allows for an increased pressure during usage or closed-loop system that provides pressure regulation in accordance to the stiffness the user specifies. Preliminary evaluation is performed to characterize the effective controllable region of variance in stiffness. It was found that the region of controllable stiffness was between points 3 and 7, where the stiffness appeared to plateau with each increase in pressure. The two control systems are tested to derive relationships between internal pressure, grasping force exertion on the surface, and displacement using multiple probing points on the haptic device. Additional quantitative evaluation is performed with study participants and juxtaposed to a qualitative analysis to ensure adequate perception in compliance variance. The qualitative evaluation showed that greater than 60% of the trials resulted in the correct perception of stiffness in the haptic device.


The human hand is a complex sensorimotor apparatus that consists of many joints, muscles, and sensory receptors. Such complexity allows for skillful and dexterous manual actions in activities of daily living (ADL). When the sensorimotor function of hand is impaired by neurological diseases or traumatic injuries, the quality of life of the affected individual could be severely impacted. For example, stroke is a condition that is broadly defined as a loss in brain function due to necrotic cell death stemming from a sudden loss in blood supply within the cranium (Hankey, 2017). This event can lead to a multitude of repercussions on sensorimotor function, one of which being impaired hand control such as weakened grip strength (Foulkes et al., 1988Duncan et al., 1994Nakayama et al., 1994Jørgensen et al., 1995Wilkinson et al., 1997Winstein et al., 2004Legg et al., 2007). Other potential causes of impaired hand function include cerebral palsy, multiple sclerosis, and amputation. Therefore, effective rehabilitation to help patients regain functional hand control is critically important in clinical practice. It has been shown that recovery of sensory motor function relies on the plasticity of the central nervous system to relearn and remodel the brain (Warraich and Kleim, 2010). Specifically, there are several factors that are known to contribute to neuroplasticity (Kleim and Jones, 2008): specificity, number of repetition, training intensity, time, and salience. However, existing physical therapy of hand is limited by the resource and accessibility, leading to inadequate dosage and lack of patients’ motivation. Robot-assisted hand rehabilitation has recently attracted a lot of attention because robotic devices have the advantage to provide (1) enriched environment to strengthen motivation, (2) increase number of repetition through automated control, and (3) progressive intensity levels that adapts to patient’s need (for review, see Balasubramanian et al., 2010).

Specifically, haptic interfaces and variable stiffness mechanisms are usually incorporated into robotic rehabilitation devices to provide varying difficulties by adjusting force output or stiffness. For example, the LINarm++ is a rehabilitative device that appropriates variable stiffness actuators with multimodal sensors to provide changing resistance in a physical environment in which users performs arm movement (Malosio et al., 2016Spagnuolo et al., 2017). This device also encompasses a functional electrical stimulation system which has been shown to promote motor recovery in upper limb rehabilitation (Popović and Popović, 2006). The Haptic Knob is a device that trains stroke patients’ grasping movements, and wrist pronation and supination motions by rotating a dial that is able to produce forces and torques up to 50 N and 1.5 Nm, respectively, depending on the patient’s level of impairment (Lambercy et al., 2009). The GripAble is a handheld rehabilitative device that allows the patient to squeeze, lift, and rotate to play a video game with increasing difficulty and gives feedback through vibration in response to the patient’s performance (Mace et al., 20152017). The MIT-MANUS, a planar rehabilitation robot, also has a hand-module that converts rotary motions to linear motions, and in turn allows for controllable impedance in the device (Masia et al., 2006). In addition, pneumatic particle jamming systems have been designed to provide users with haptic feedback by changing the stiffness and geometry of the surface the user presses on with their fingertips (Stanley et al., 2013Genecov et al., 2014). These devices and systems, however, are either costly and bulky due to complex mechanical design or have limited range of stiffness due to passive mechanical components.

To overcome these limitations, this paper proposes the design of a novel pneumatically actuated soft robotics-based variable stiffness haptic interface to support rehabilitation of sensorimotor function of hands (Figure 1). Soft robotics is a rapidly growing field that utilizes highly compliant materials that are fluidic actuated to effectively adapt to shapes and constraints that traditionally rigid machines are unable to Majidi (2014) and Polygerinos et al. (2017). Several soft-robotics devices have been developed to provide assistance to stroke patients, but none of these has been designed as resistive training devices. An example of an existing device includes the use of soft actuators that bend, twist, and extend through finger-like motions in a rehabilitative exoglove to be worn by stroke patients (Polygerinos et al., 2015a,bYap et al., 2017). A variable stiffness device that employs soft-robotics allows a greater range of stiffness to be implemented since there is minimal or no impedance to the initial stiffness of the device. In addition, soft robotics methods allow devices to be manufactured with lowered cost and have much less complexity, thus suitable to be used not only inpatient but also outpatient hand rehabilitative services (Taylor et al., 1996Godwin et al., 2011).


Figure 1. The prototyped soft haptic variable stiffness interface with a hand grasping it.

In Section “Materials and Methods” of this paper, the materials and methods employed in designing and fabricating the soft robotic haptic interface are described, including the design criteria of the prototype. This section also describes the methodology for a stiffness perception test on healthy participant with the proposed device. In addition, the overall closed-loop control system of the device to provide pressure regulation is presented in this section. Section “Results” describes the preliminary results obtained from characterization of the device’s varying stiffness in response to changing pressure inputs, and the subjective evaluation of perceived stiffness obtained from test participants. Finally, Section “Discussion” includes an overall discussion of open question and future research directions. […]

Continue —>  Frontiers | Soft Robotic Haptic Interface with Variable Stiffness for Rehabilitation of Neurologically Impaired Hand Function | Robotics and AI


, , , , , , , , ,

Leave a comment

[WEB SITE] Brain-Machine Interface Shows Potential for Hand Paralysis – Rehab Managment

Published on

The use of a brain-machine interface shows potential for helping to restore function in stroke patients with hand paralysis, according to a study of healthy adults published in the Journal of Neuroscience.

According to the study, researchers note that the brain-machine interface, which is designed to combine brain stimulation with a robotic device that controls hand movement, increases the output of pathways connecting the brain and spinal cord.

Researchers Alireza Gharabaghi and colleagues asked participants to imagine opening their hand without actually making any movement while their hand was placed in a device that passively opened and closed their fingers as it received the necessary input from their brain activity. Stimulating the hand area of the motor cortex at the same time, but not after, the robotic device initiated hand movement increased the strength of the neural signal, most likely by harnessing the processing power of additional neurons in the corticospinal tract, explains a media release from the Society for Neuroscience.

However, the signal decreased when participants were not required to imagine moving their hand. Delivering brain stimulation and robotic motor feedback simultaneously during rehabilitation may therefore be beneficial for patients who have lost voluntary muscle control, the release continues.

[Source(s): Society for Neuroscience]

via Brain-Machine Interface Shows Potential for Hand Paralysis – Rehab Managment

, , , , , , , , ,

Leave a comment

[ARTICLE] Does motivation matter in upper-limb rehabilitation after stroke? ArmeoSenso-Reward: study protocol for a randomized controlled trial – Full Text



Fifty percent of all stroke survivors remain with functional impairments of their upper limb. While there is a need to improve the effectiveness of rehabilitative training, so far no new training approach has proven to be clearly superior to conventional therapy. As training with rewarding feedback has been shown to improve motor learning in humans, it is hypothesized that rehabilitative arm training could be enhanced by rewarding feedback. In this paper, we propose a trial protocol investigating rewards in the form of performance feedback and monetary gains as ways to improve effectiveness of rehabilitative training.


This multicentric, assessor-blinded, randomized controlled trial uses the ArmeoSenso virtual reality rehabilitation system to train 74 first-ever stroke patients (< 100 days post stroke) to lift their impaired upper limb against gravity and to improve the workspace of the paretic arm. Three sensors are attached to forearm, upper arm, and trunk to track arm movements in three-dimensional space while controlling for trunk compensation. Whole-arm movements serve as input for a therapy game. The reward group (n = 37) will train with performance feedback and contingent monetary reward. The control group (n = 37) uses the same system but without monetary reward and with reduced performance feedback. Primary outcome is the change in the hand workspace in the transversal plane. Standard clinical assessments are used as secondary outcome measures.


This randomized controlled trial will be the first to directly evaluate the effect of rewarding feedback, including monetary rewards, on the recovery process of the upper limb following stroke. This could pave the way for novel types of interventions with significantly improved treatment benefits, e.g., for conditions that impair reward processing (stroke, Parkinson’s disease).


After stroke, 50% of survivors are left with impairments in arm function [12], which is associated with reduced health-related quality of life [3]. While there is evidence for a positive correlation between therapy dose and functional recovery [456], a higher therapy dose is challenging to implement, as it usually leads to an increase in costs commonly not covered by health insurances. However, when dose is matched, most randomized controlled trials introducing new types of rehabilitative interventions (e.g., robot-assisted therapy [7]) failed to show a superior effect compared to standard therapy. Thus, the need for improving therapy effectiveness remains. In search for elements of effective therapy, we hypothesize that performance feedback and monetary rewards can improve effectiveness.

It has been shown that reward enhances procedural [8] and motor-skill learning [910] and has a positive effect on motor adaptation [11]. Rewards mainly improve retention of motor skills and motor adaptations [91011]. This effect was not explained by training duration (dose) as rewarded and non-rewarded groups underwent similar training schedules [891011]. In a functional magnetic resonance imaging (fMRI) study, Widmer et al. reported that adding monetary rewards after good performance leads to better consolidation and higher ventral striatum activation than knowledge of performance alone [10]. The striatum is a key locus of reward processing [12], and its activity was shown to be increased by both intrinsic and extrinsic reward [13]. Being a brain structure that receives substantial dopaminergic input from the midbrain, ventral striatal activity can be seen as a surrogate marker for dopaminergic activity in the substantia nigra/ventral tegmental area [14]. In rodents, Hosp et al. found that dopaminergic projections from the midbrain also terminate directly in the primary motor cortex (M1) [15]. Dopamine in M1 is necessary for long-term potentiation of certain cortico-cortical connections and successful motor-skill learning [16]. As mechanisms of motor learning are also thought to play a role in motor recovery [17], rehabilitative interventions may benefit from neuroplasticity enhanced by reward.

Here, we describe a trial protocol to test the effect of enhanced feedback and reward on arm rehabilitation after stroke at matched training dose (time and intensity). We use the ArmeoSenso, a standardized virtual reality (VR)-based training system [18] that is delivered in two versions for two different study groups, one version with and one without reward and enhanced performance feedback. […]


Continue —> Does motivation matter in upper-limb rehabilitation after stroke? ArmeoSenso-Reward: study protocol for a randomized controlled trial | Trials | Full Text

Fig. 2a Healthy subject using the ArmeoSenso training system. b Arm workspace assessment: gray cubic voxels arranged in the transverse plane reflecting 10 cm × 10 cm active workspace relative to the patient’s trunk

, , , , , , , , ,

Leave a comment

[ARTICLE] Effects of somatosensory electrical stimulation on motor function and cortical oscillations – Full Text



Few patients recover full hand dexterity after an acquired brain injury such as stroke. Repetitive somatosensory electrical stimulation (SES) is a promising method to promote recovery of hand function. However, studies using SES have largely focused on gross motor function; it remains unclear if it can modulate distal hand functions such as finger individuation.


The specific goal of this study was to monitor the effects of SES on individuation as well as on cortical oscillations measured using EEG, with the additional goal of identifying neurophysiological biomarkers.


Eight participants with a history of acquired brain injury and distal upper limb motor impairments received a single two-hour session of SES using transcutaneous electrical nerve stimulation. Pre- and post-intervention assessments consisted of the Action Research Arm Test (ARAT), finger fractionation, pinch force, and the modified Ashworth scale (MAS), along with resting-state EEG monitoring.


SES was associated with significant improvements in ARAT, MAS and finger fractionation. Moreover, SES was associated with a decrease in low frequency (0.9-4 Hz delta) ipsilesional parietomotor EEG power. Interestingly, changes in ipsilesional motor theta (4.8–7.9 Hz) and alpha (8.8–11.7 Hz) power were significantly correlated with finger fractionation improvements when using a multivariate model.


We show the positive effects of SES on finger individuation and identify cortical oscillations that may be important electrophysiological biomarkers of individual responsiveness to SES. These biomarkers can be potential targets when customizing SES parameters to individuals with hand dexterity deficits. Trial registration: NCT03176550; retrospectively registered.


Despite recent advances in rehabilitation, a substantial fraction of stroke patients continue to experience persistent upper-limb deficits [1]. At best, up to 1 out of 5 patients will recover full arm function, while 50% will not recover any functional use of the affected arm. [2] Improvement in upper limb function specifically depends on sensorimotor recovery of the paretic hand [3]. Yet, there remains a lack of effective therapies readily available to the patient with acquired brain injury for recovery of hand and finger function; a systematic review found that conventional repetitive task training may not be consistently effective for the upper extremity [4]. It is thus critical to explore inexpensive and scalable approaches to restore hand and finger dexterity, reduce disability and increase participation after stroke and other acquired brain injuries.

Sensory threshold somatosensory electrical stimulation (SES) is a promising therapeutic modality for targeting hand motor recovery [5]. It is known to be a powerful tool to focally modulate sensorimotor cortices in both healthy and chronic stroke participants [5678]. Devices such as transcutaneous nerve stimulation (TENS) units can deliver SES and are commercially available, inexpensive, low risk, and easily applied in the home setting [9]. Previous studies have demonstrated short-term and long-term improvements in hand function after SES [5101112131415]. However, the effect of SES on regaining the ability to selectively move a given digit independently from other digits (i.e. finger fractionation) has not been investigated. Poor finger individualization is an important therapeutic target because it is commonly present even after substantial recovery and may account for chronic hand dysfunction [16]. Further, it is unclear if SES is associated with compensatory or restorative mechanisms. Prior studies have largely relied on relatively subjective clinical evaluations of impairment, such as the Fugl-Meyer Assessment, or timed and task-based assessments, such as the Jebson-Taylor Hand Function Test. Biomechanical analyses, on the other hand, can provide important objective and quantitative evidence of improvement in neurologic function and normative motor control [1718]. Therefore, we aimed to determine not only the functional effects, but also the kinematic effects, of SES on chronic hand dysfunction.

Simultaneously, it should be noted that although SES can potentially be an effective therapy, not all individuals who are administered SES experience positive effects. While improvement levels as high as 31–36% compared to baseline function have been reported, [1119] about half of one cohort demonstrated minimal or no motor performance improvement after a single session of SES [15]. One method to shed more light on this discrepancy is to identify neurophysiological biomarkers associated with motor responses to SES. Neurophysiological biomarkers are increasingly used to predict treatment effects [2021]. Although some studies have examined biomarkers associated with treatment-induced motor recovery, to our knowledge none have been performed for SES [2223]. A recent study using electroencephalography (EEG) found that changes in patterns of connectivity predicted motor recovery after stroke [24]. At present, little is known about the effect of peripheral neuromodulation on EEG activity, how existing neural dynamics interacts with peripheral stimulation, and whether this interaction is associated with improvements in motor function. Associating EEG activity with treatment response may also provide mechanistic insight regarding the effects of SES on neural plasticity. EEG activity can also potentially be used as a cost-effective real-time metric of the time-varying efficacy of SES. This novel application of EEG information may help tailor treatment efforts while reducing the variability in outcome.

The main goal of this pilot study was to evaluate both changes in finger fractionation in response to SES and identify the associated neural biomarkers through analyses of EEG dynamics. Outcomes from this study have potential in designing targeted SES therapy based on neural biomarkers to modulate and improve hand function after acquired brain injury such as stroke (e.g. enrollment in long-term studies of the efficacy of SES).


Continue —>  Effects of somatosensory electrical stimulation on motor function and cortical oscillations | Journal of NeuroEngineering and Rehabilitation | Full Text

Fig. 1a Schematic representation of the method used for calculating the FCI. The participant is instructed to flex only the index finger as much as possible without flexing the other digits. b FCI is defined mathematically as the angle traversed by the middle finger (digit A) divided by the angle tranversed by the index finger (digit B) relative to the horizontal starting position. c Statistically significant change in mean fractionation from baseline to immediately after peripheral nerve stimulation. Fractionation improvement is indicated by a decrease in finger coupling index (FCI)


, , , , , , , , , , ,

Leave a comment

[Abstract+References] Does Stroke Rehabilitation Really Matter? Part A: Proportional Stroke Recovery in the Rat


Background. In human upper-limb stroke, initial level of functional impairment or corticospinal tract injury can accurately predict the degree of poststroke recovery, independent of rehabilitation practices. This proportional recovery rule implies that current rehabilitation practices may play little or no role in brain repair, with recovery largely a result of spontaneous biological recovery processes.

Objective. The present study sought to determine if similar biomarkers predict recovery of poststroke function in rats, indicating that an endogenous biological recovery process might be preserved across mammalian species.

Methods. Using a cohort of 593 male Sprague-Dawley rats, we predicted poststroke change in pellet retrieval in the Montoya staircase-reaching task based on initial impairment alone. Stratification of the sample into “fitters” and “nonfitters” of the proportional recovery rule using hierarchical cluster analysis allowed identification of distinguishing characteristics of these subgroups.

Results. Approximately 30% of subjects were identified as fitters of the rule. These rats showed recovery in proportion to their initial level of impairment of 66% (95% CI = 62%-70%). This interval overlaps with those of multiple human clinical trials. A number of variables, including less severe infarct volumes and initial poststroke impairments distinguished fitters of the rule from nonfitters.

Conclusions. These findings suggest that proportional recovery is a cross-species phenomenon that can be used to uncover biological mechanisms contributing to stroke recovery.

1. Prabhakaran, S, Zarahn, E, Riley, C. Inter-individual variability in the capacity for motor recovery after ischemic stroke. Neurorehabil Neural Repair. 2008;22:6471Google ScholarLink
2. Winters, C, van Wegen, EEH, Daffertshofer, A, Kwakkel, G. Generalizability of the proportional recovery model for the upper extremity after an ischemic stroke. Neurorehabil Neural Repair. 2015;29:614622Google ScholarLinkISI
3. Byblow, WD, Stinear, CM, Barber, PA, Petoe, MA, Ackerley, SJ. Proportional recovery after stroke depends on corticomotor integrity. Ann Neurol. 2015;78:848859Google ScholarCrossrefMedline
4. Feng, W, Wang, J, Chhatbar, PY. Corticospinal tract lesion load: an imaging biomarker for stroke motor outcomes. Ann Neurol. 2015;78:860870Google ScholarCrossrefMedline
5. Stinear, CM, Byblow, WD, Ackerley, SJ, Smith, MC, Borges, VM, Barber, PA. Proportional motor recovery after stroke: implications for trial design. Stroke. 2017;48:795798Google ScholarCrossrefMedline
6. Smith, MC, Byblow, WD, Barber, PA, Stinear, CM. Proportional recovery from lower limb motor impairment after stroke. Stroke. 2017;48:14001403Google ScholarCrossrefMedline
7. Winters, C, van Wegen, EEH, Daffertshofer, A, Kwakkel, G. Generalizability of the maximum proportional recovery rule to visuospatial neglect early poststroke. Neurorehabil Neural Repair. 2017;31:334342Google ScholarLink
8. Lazar, RM, Minzer, B, Antoniello, D, Festa, JR, Krakauer, JW, Marshall, RS. Improvement in aphasia scores after stroke is well predicted by initial severity. Stroke. 2010;41:14851488Google ScholarCrossrefMedline
9. Krakauer, JW, Marshall, RS. The proportional recovery rule for stroke revisited. Ann Neurol. 2015;78:845847Google ScholarCrossrefMedline
10. Gladstone, DJ, Danells, CJ, Black, SE. The Fugl-Meyer assessment of motor recovery after stroke: a critical review of its measurement properties. Neurorehabil Neural Repair. 2002;16:232240Google ScholarLink
11. Carmichael, ST. Rodent models of focal stroke: size, mechanism, and purpose. NeuroRx. 2005;2:396409Google ScholarCrossrefMedline

via Does Stroke Rehabilitation Really Matter? Part A: Proportional Stroke Recovery in the RatNeurorehabilitation and Neural Repair – Matthew Strider Jeffers, Sudhir Karthikeyan, Dale Corbett, 2018

, , , , , , , , ,

Leave a comment

[ARTICLE] Robotic Arm with Brain – Computer Interfacing – Full Text PDF


Brain Computer Interfaces (BCI), is a modern technology which is currently revolutionizing the field of signal processing. BCI helped in the evolution of a new world where man and computer had never been so close. Advancements in cognitive neuro-sciences facilitated us with better brain imaging techniques and thus interfaces between machines and the human brain became a reality. Electroencephalography (EEG), which is the measurement and recording of electric signals using sensors arrayed across the scalp can be used for applications like prosthetic devices, applications in warfare, gaming, virtual reality and robotics upon signal conditioning and processing.

This paper is entirely based on Brain-Computer Interface with an objective of actuating a robotic arm with the help of device commands derived from EEG signals. This system unlike any other existing technology is purely non-invasive in nature, cost effective and is one of its kinds that can serve various requirements such as prosthesis. This paper suggests a low cost system implementation that can even serve as a reliable substitute for the existing technologies of prosthesis like BIONICS. […]

via Robotic Arm with Brain – Computer Interfacing – ScienceDirect

, , , , , , , , , , ,

Leave a comment

[ARTICLE] Innovative STRoke Interactive Virtual thErapy (STRIVE) online platform for community-dwelling stroke survivors: a randomised controlled trial protocol – Full Text


Introduction The STRoke Interactive Virtual thErapy (STRIVE) intervention provides community-dwelling stroke survivors access to individualised, remotely supervised progressive exercise training via an online platform. This trial aims to determine the clinical efficacy of the STRIVE intervention and its effect on brain activity in community-dwelling stroke survivors.

Methods and analysis In a multisite, assessor-blinded randomised controlled trial, 60 stroke survivors >3 months poststroke with mild-to-moderate upper extremity impairment will be recruited and equally randomised by location (Melbourne, Victoria or Launceston, Tasmania) to receive 8 weeks of virtual therapy (VT) at a local exercise training facility or usual care. Participants allocated to VT will perform 3–5 upper limb exercises individualised to their impairment severity and preference, while participants allocated to usual care will be asked to maintain their usual daily activities. The primary outcome measures will be upper limb motor function and impairment, which will be assessed using the Action Research Arm Test and Upper Extremity Fugl-Meyer, respectively. Secondary outcome measures include upper extremity function and spasticity, as measured by the box and block test and Modified AshworthScale, respectively, and task-related changes in bilateral sensorimotor cortex haemodynamics during hand reaching and wrist extension movements as measured by functional near-infrared spectroscopy. Quality of life will be measured using the Euro-Quality of Life-5 Dimension-5 Level Scale, and the Motor Activity Log-28 will be used to measure use of the hemiparetic arm. All measures will be assessed at baseline and immediately postintervention.

Ethics and dissemination The study was approved by the Deakin University Human Research Ethics Committee in May 2017 (No. 2017–087). The results will be disseminated in peer-reviewed journals and presented at major international stroke meetings.

Trial registration number ACTRN12617000745347; Pre-results.


Stroke is one of the leading causes of adult disability in Western countries,1 and for many stroke survivors, upper extremity (UE) paresis makes performing activities of daily living (ADLs) difficult. Up to 60% of community-dwelling stroke survivors live with severe motor impairments of the shoulders, elbows and/or wrists that significantly impacts their functional capacity and quality of life.2 Improved UE function is considered a rehabilitation priority after stroke,3 yet optimal recovery of arm function is poor.2 4 A large majority of stroke survivors experience a lack of support and access to rehabilitative services once they are discharged into the community,5 6 which can compromise their recovery. While most recovery occurs in the first weeks to months after stroke, improvements in function can still be experienced beyond this period.7

The use of virtual reality as a therapy, which is characterised by the participant being immersed in, and interacting with, a computer-generated environment,8 is emerging as an efficacious treatment for UE impairment after stroke.9 10 Online virtual therapy (VT) systems can provide the fundamental elements needed for motor skill development; they can be individually tailored, involve many task-specific repetitions that are increasingly challenging in response to participant improvement and feedback can be embedded in the system. The enriched environment offered by VT is thought to be effective in training problem solving and functional task performance11 and can potentially increase participant engagement compared with non-VT rehabilitation platforms.12

Online VT systems have the potential to address the lack of community-based rehabilitation support experienced by stroke survivors by being affordable, accessible, user-friendly and importantly, have the ability to remotely monitor rehabilitation progress. VT systems, such as the Jintronix Rehabilitation System (Montreal, Canada) to be used in this study, can be administered affordably through commercially available products that include motion capture capabilities (eg, Microsoft Xbox Kinect V.2) and personal computers.13 Online VT systems can be easily implemented at a local community centre, which would enable patients with stroke to receive specialised treatment and monitoring remotely. Online VT platforms have been shown to be user-friendly and motivating,14 including interfaces that are engaging and easy to interact with, and software that can be run on any personal computer/device. In a Cochrane review, Laver et al 9 reported low-quality evidence suggesting VT is a more effective approach to improve arm function after stroke compared with conventional therapy.9 A recent multiple systematic review, including 10 randomised controlled trials and four systematic reviews, found VT therapy to be similar to standard rehabilitation for treatment of UE impairment and disabilities.15

To understand the effects of VT on cerebral activity in stroke rehabilitation, neuroimaging techniques such as functional MRI (fMRI) have been used previously to determine cortical reorganisation postrehabilitation.16 While fMRI is considered the gold-standard measure in neuroimaging, these techniques may be limited as they only allow for small movements to occur within the scanner that are very different from activities of daily living (ADLs). In this sense, functional near-infrared spectroscopy (fNIRS) may be a more suitable neuroimaging technique as it is able to measure changes in cerebral haemodynamic responses (ie, changes in oxyhaemoglobin and deoxyhaemoglobin (HbO2 and HHb)) in response to larger body and head movements that mimic ADLs. Previous studies have also established that cerebral haemodynamic measures from fNIRS are highly comparable with blood oxygen-level dependent signals from fMRI,17 18 which makes it a suitable surrogate to measure changes in brain activity following VT rehabilitation in people with stroke.

Given the advantages of increased accessibility to specialised treatment and monitoring that is afforded by VT, we aim to determine if an online VT system can provide efficacious UE rehabilitation for community-dwelling stroke survivors. We have chosen to focus our intervention on UE function as impaired arm function is highly common after stroke,2 which profoundly impacts the capacity to perform ADLs19 and only a small number of stroke survivors experience complete functional recovery of the UE.20 

Continue —>  Innovative STRoke Interactive Virtual thErapy (STRIVE) online platform for community-dwelling stroke survivors: a randomised controlled trial protocol | BMJ Open

Figure 2 Examples of VT therapy games that target UE mobility of the shoulders, elbows and wrists. UE, upper extremity; VT, Virtual therapy.

, , , , , , , ,

Leave a comment

[Abstract] Encouragement-induced real-world upper limb use after stroke by a tracking and feedback device: a study protocol for a multi-center, assessor-blinded, randomized controlled trial

Introduction: Retraining the paretic upper limb after stroke should be intense and specific to be effective. Hence, the best training is daily life use, which is often limited by motivation and effort. Tracking and feedback technology have the potential to encourage self-administered, context-specific training of upper limb use in the patients’ home environment. The aim of this study is to investigate post-intervention and long-term effects of a wrist-worn activity tracking device providing multimodal feedback on daily arm use in hemiparetic subjects beyond 3 months post-stroke.

Methods and Analysis: A prospective, multi-center, assessor-blinded, Phase 2 randomized controlled trial with a superiority framework. Sixty-two stroke patients will be randomized in two groups, with a 1:1 allocation ratio, stratified based on arm paresis severity (Fugl-Meyer Assessment – Upper Extremity subscale <32 and ≥32). The experimental group receives a wrist-worn activity tracking device providing multimodal feedback on daily arm use for 6 weeks. Controls wear an identical device providing no feedback. Sample size: 31 participants per group, based on a difference of 0.75±1.00 points on the Motor Activity Log – 14 Item Version, Amount of Use subscale (MAL-14 AOU), 80% power, two-sided alpha of 0.05, and a 10% attrition rate.

Outcomes: Primary outcome is the change in patient-reported amount of daily life upper limb use (MAL-14 AOU) from baseline to post-intervention. Secondary outcomes are change in upper limb motor function, upper limb capacity, global disability, patient-reported quality of daily life upper limb use, and quality of life from baseline to post-intervention and 6-week follow-up, as well as compliance and safety.

Discussion: The results of this study will show the possible efficacy of a wrist-worn tracking and feedback device on patient-reported amount of daily life upper limb use.

Ethics and Dissemination: The study is approved by the Cantonal Ethics Committees Zurich, and Northwest and Central Switzerland (BASEC-number 2017-00948) and registered in (NCT03294187) before recruitment started. This study will be carried out in compliance with the Declaration of Helsinki, ICH-GCP, ISO 14155:2011, and Swiss legal and regulatory requirements. Dissemination will include submission to a peer-reviewed journal, patient and healthcare professional magazines, and congress presentations.

via Frontiers | Encouragement-induced real-world upper limb use after stroke by a tracking and feedback device: a study protocol for a multi-center, assessor-blinded, randomized controlled trial | Neurology

, , , , , , , , ,

Leave a comment

[Conference paper] Robotic Upper Limb Rehabilitation Using Armeo®Spring for Chronic Stroke Patients at University Malaya Medical Centre (UMMC) – Abstract+References


This is a retrospective study of patients with chronic partial arm paresis post stroke who attended neurorehabilitation at University Malaya Medical Centre, Malaysia. In this study we aimed to analyze the clinical and practical outcome of robotic-assisted upper limb rehabilitation. Specifically, we analyzed the impact of therapy on motor and function of chronic stroke arm paresis through structured therapy protocol. We extended our analysis towards user acceptance in robotic-assisted rehabilitation. We applied our Armeo®Spring Therapy Protocol on stroke patients with unilateral partial upper limb paresis of more than six months duration. The outcome measures were muscle strength, spasticity and hand dexterity. Thirty three patients who fulfilled the criteria of treatment protocol attended outpatient therapy session. Fourteen patients completed the treatment protocol in which ten participants were stroke patients. This study reported statistically significant improvement in multiple joint range of motions following therapy. Although there was non progressing arm spasticity, and improved paretic hand dexterity, both latter outcomes were not statistically significant at the end of therapy.


  1. 1.
    Broeks, J.G., Lankhorst, G.J., Rumping, K., Prevo, A.J.: The long-term outcome of arm function after stroke: results of a follow-up study. Disabil. Rehabil. 21, 357–364 (1999)CrossRefGoogle Scholar
  2. 2.
    Jørgensen, H.S., Nakayama, H., Raaschou, H.O., Vive-Larsen, J., Støier, M., Olsen, T.S.: Outcome and time course of recovery in stroke. II. Time course of recovery: the Copenhagen stroke study. Arch. Phys. Med. Rehabil. 76, 406–412 (1995)CrossRefGoogle Scholar
  3. 3.
    Lo, A.C., Guarino, P.D., Richards, L.G., et al.: Robotic-assisted therapy for long term upper limb impairment in stroke. N Engl. Med. 362, 19 (2010)CrossRefGoogle Scholar
  4. 4.
    Colombo, R., Sterpi, I., Mazzone, A., Delconte, C., Pisano, F.: Robot aided neurorehabilitation in sub-acute and chronic stroke: does spontaneous recovery have limited impact on outcome? NeuroRehabilitation 33, 621–629 (2013)Google Scholar
  5. 5.
    Abdullah, H.A., Tarry, C., Lambert, C., Barreca, S., Allen, B.O.: Results of clinicians using a therapeutic robotic system in an inpatient stroke rehabilitation unit. J. NeuroEng. Rehabil. 8, 50 (2011)CrossRefGoogle Scholar
  6. 6.
    Levin, M.F., Kleim, J.A., Wolf, S.L.: What do motor “recovery” and “compensation” mean in patients following stroke? Neurorehabil. Neural Repair 23, 313–319 (2009)CrossRefGoogle Scholar
  7. 7.
    Desrosiers, J., Bravo, G., Hébert, R., Dutil, E., Mercier, L.: Validation of the box and block test as a measure of dexterity of elderly people: reliability, validity, and norms studies. Arch. Phys. Med. Rehabil. 75, 751–755 (1994)Google Scholar
  8. 8.
  9. 9.
    Dijkers, M.P., deBear, P.C., Erlandson, R.F., Kristy, K., Geer, D.M., Nichols, A.: Patient and staff acceptance of robot technology in occupational therapy: a pilot study. J. Rehabil. Res. Dev. 28(2), 33–44 (1991)CrossRefGoogle Scholar
  10. 10.
    Loureiro, R.C.V., Harwin, W.S., Nagai, K., Johnson, M.: Advances in upper limb stroke rehabilitation: a technology push. Med. Biol. Eng. Comput. 49, 1103–1111 (2011)CrossRefGoogle Scholar

via Robotic Upper Limb Rehabilitation Using Armeo®Spring for Chronic Stroke Patients at University Malaya Medical Centre (UMMC) | SpringerLink

, , , , , , , , ,

Leave a comment

[Abstract] Virtual reality for stroke rehabilitation – Review


Virtual reality and interactive video gaming have emerged as recent treatment approaches in stroke rehabilitation with commercial gaming consoles in particular, being rapidly adopted in clinical settings. This is an update of a Cochrane Review published first in 2011 and then again in 2015.

Primary objective: to determine the efficacy of virtual reality compared with an alternative intervention or no intervention on upper limb function and activity.Secondary objectives: to determine the efficacy of virtual reality compared with an alternative intervention or no intervention on: gait and balance, global motor function, cognitive function, activity limitation, participation restriction, quality of life, and adverse events.

We searched the Cochrane Stroke Group Trials Register (April 2017), CENTRAL, MEDLINE, Embase, and seven additional databases. We also searched trials registries and reference lists.

Randomised and quasi-randomised trials of virtual reality (“an advanced form of human-computer interface that allows the user to ‘interact’ with and become ‘immersed’ in a computer-generated environment in a naturalistic fashion”) in adults after stroke. The primary outcome of interest was upper limb function and activity. Secondary outcomes included gait and balance and global motor function.

Two review authors independently selected trials based on pre-defined inclusion criteria, extracted data, and assessed risk of bias. A third review author moderated disagreements when required. The review authors contacted investigators to obtain missing information.

We included 72 trials that involved 2470 participants. This review includes 35 new studies in addition to the studies included in the previous version of this review. Study sample sizes were generally small and interventions varied in terms of both the goals of treatment and the virtual reality devices used. The risk of bias present in many studies was unclear due to poor reporting. Thus, while there are a large number of randomised controlled trials, the evidence remains mostly low quality when rated using the GRADE system. Control groups usually received no intervention or therapy based on a standard-care approach.

results were not statistically significant for upper limb function (standardised mean difference (SMD) 0.07, 95% confidence intervals (CI) -0.05 to 0.20, 22 studies, 1038 participants, low-quality evidence) when comparing virtual reality to conventional therapy. However, when virtual reality was used in addition to usual care (providing a higher dose of therapy for those in the intervention group) there was a statistically significant difference between groups (SMD 0.49, 0.21 to 0.77, 10 studies, 210 participants, low-quality evidence).

when compared to conventional therapy approaches there were no statistically significant effects for gait speed or balance. Results were statistically significant for the activities of daily living (ADL) outcome (SMD 0.25, 95% CI 0.06 to 0.43, 10 studies, 466 participants, moderate-quality evidence); however, we were unable to pool results for cognitive function, participation restriction, or quality of life. Twenty-three studies reported that they monitored for adverse events; across these studies there were few adverse events and those reported were relatively mild.

We found evidence that the use of virtual reality and interactive video gaming was not more beneficial than conventional therapy approaches in improving upper limb function. Virtual reality may be beneficial in improving upper limb function and activities of daily living function when used as an adjunct to usual care (to increase overall therapy time). There was insufficient evidence to reach conclusions about the effect of virtual reality and interactive video gaming on gait speed, balance, participation, or quality of life. This review found that time since onset of stroke, severity of impairment, and the type of device (commercial or customised) were not strong influencers of outcome. There was a trend suggesting that higher dose (more than 15 hours of total intervention) was preferable as were customised virtual reality programs; however, these findings were not statistically significant.

Update of
Virtual reality for stroke rehabilitation. [Cochrane Database Syst Rev. 2015]

via Virtual reality for stroke rehabilitation. – PubMed – NCBI

, , , , , ,

Leave a comment

%d bloggers like this: