Posts Tagged post stroke
More than 1.5 million people suffer a stroke in Europe per year and more than 70% of stroke survivors experience limited functional recovery of their upper limb, resulting in diminished quality of life. Therefore, interventions to address upper-limb impairment are a priority for stroke survivors and clinicians. While a significant body of evidence supports the use of conventional treatments, such as intensive motor training or constraint-induced movement therapy, the limited and heterogeneous improvements they allow are, for most patients, usually not sufficient to return to full autonomy. Various innovative neurorehabNIBSilitation strategies are emerging in order to enhance beneficial plasticity and improve motor recovery. Among them, robotic technologies, brain-computer interfaces, or noninvasive brain stimulation (NIBS) are showing encouraging results. These innovative interventions, such as NIBS, will only provide maximized effects, if the field moves away from the “one-fits all” approach toward a “patient-tailored” approach. After summarizing the most commonly used rehabilitation approaches, we will focus on and highlight the factors that limit its widespread use in clinical settings. Subsequently, we will propose potential biomarkers that might help to stratify stroke patients in order to identify the individualized optimal therapy. We will discuss future methodological developments, which could open new avenues for poststroke rehabilitation, toward more patient-tailored precision medicine approaches and pathophysiologically motivated strategies.
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[ARTICLE] Brain regions important for recovery after severe post-stroke upper limb paresis – Full Text
Background The ability to predict outcome after stroke is clinically important for planning treatment and for stratification in restorative clinical trials. In relation to the upper limbs, the main predictor of outcome is initial severity, with patients who present with mild to moderate impairment regaining about 70% of their initial impairment by 3 months post-stroke. However, in those with severe presentations, this proportional recovery applies in only about half, with the other half experiencing poor recovery. The reasons for this failure to recover are not established although the extent of corticospinal tract damage is suggested to be a contributory factor. In this study, we investigated 30 patients with chronic stroke who had presented with severe upper limb impairment and asked whether it was possible to differentiate those with a subsequent good or poor recovery of the upper limb based solely on a T1-weighted structural brain scan.
Methods A support vector machine approach using voxel-wise lesion likelihood values was used to show that it was possible to classify patients as good or poor recoverers with variable accuracy depending on which brain regions were used to perform the classification.
Results While considering damage within a corticospinal tract mask resulted in 73% classification accuracy, using other (non-corticospinal tract) motor areas provided 87% accuracy, and combining both resulted in 90% accuracy.
Conclusion This proof of concept approach highlights the relative importance of different anatomical structures in supporting post-stroke upper limb motor recovery and points towards methodologies that might be used to stratify patients in future restorative clinical trials.
Stroke is one of the the most common causes of physical disability worldwide and about 80% of stroke survivors experience impairment of movement on one side of the body.1 Hand and arm impairment in particular is often persistent, disabling and a major contributor to reduced quality of life.2 The main predictor of long-term outcome of upper limb function is the level of initial impairment.3 This can be quantified as the proportional recovery rule which states that by 3 months, patients with stroke will recover about 70% of the initial upper limb motor impairment that has been observed on day 3 post-stroke.4–6 The prediction works extremely well for those presenting with mild to moderate upper limb impairment, but in only about half of those with initially severe upper limb impairment.4–6 In the other half, patients do worse than predicted, that is, there is a failure of proportional recovery. A key question then is, what is the difference between patients with stroke matched for initial severity who go on and have different recovery trajectories? The answer to this will point to the factors that are important for the dynamic process of recovery independent from the causes of initial impairment.
One possibility is the anatomy of the damage may be different in each group. A number of recent studies have proposed that the corticospinal tract (CST) plays a decisive role in this categorical difference7–11 as cortical reorganisation for improved motor function ultimately requires access for cortical motor areas to muscles. However, CST lesion load correlates with initial motor impairment,12 which is the major predictor of long-term outcome. It is therefore reasonable to ask how much CST lesion load can improve prediction of long-term outcome over and above initial severity. Furthermore, most of the patients involved in these studies had suffered from subcortical stroke and recent work has suggested that taking account of cortical damage after stroke can improve prediction of the motor clinical consequences.13 14
In this study, we investigated 30 patients with chronic stroke with a range of lesion locations (cortical and/or subcortical involvement) known to have presented with severe initial upper limb impairment but who had gone on to have quite different recovery trajectories. We applied a support vector machine approach to data representing lesion likelihood derived from structural T1-weighted MRI to answer the following questions. First, how accurately can patients with stroke with severe initial upper limb impairment be classified as having either good or poor recovery using only data extracted from whole brain structural MRI? Second, which brain regions contribute most to the classification? The results have the potential to transform how prediction of long-term upper limb outcome after stroke is achieved in routine clinical practice in future. The ability to easily and accurately predict outcome with standard clinical neuroimaging would have important implications for planning of treatment but also for stratification in future trials of restorative therapies.15[…]
Objective: To assess, the duration of treatment effect for incobotulinumtoxinA treatment intervals using a pooled analysis of 2 phase 3 clinical studies in upper-limb post-stroke spasticity (ULPSS).
Background: The efficacy and safety of incobotulinumtoxinA in ULPSS has been confirmed in 2 phase 3 studies. Study 0410 included a randomized placebo-controlled period and an open-label extension (OLEX). OLEX reinjection intervals were flexible (≥12 week intervals with doses ≤400U). Study 3001 included fixed 12-week treatment intervals (TIs). In study 0410, investigators and subjects mutually determined the need for re-injection on the basis of pre-specified criteria (eg, Ashworth scale scores, investigator’s clinical impression).
Design/Methods: All TIs between 2 consecutive incobotulinumtoxinA injections were included, except TIs prior to the end of study visit and those with doses <300U. Outliers and factors other than a medical need for re-injection (eg, visit scheduling) were accounted for using duration thresholds applied during the analysis; the number of subjects with ≥1 TI above a threshold was calculated.
Results: A total of 347/437 incobotulinumtoxinA TIs met the inclusion criteria (range of re-injection intervals observed: 9–49 weeks). Over half (54.8%) of the re-injections were administered at week ≥14. The mean incobotulinumtoxinA TI was 15.46 weeks (standard devation: 4.63 weeks). A majority of subjects (59.1%) had ≥1 TI with re-injection at week ≥16; 33.1% of subjects had 1, 22.1% had 2 and 3.9% had 3. Many subjects (42.5%) had ≥1 TI with re-injection at week ≥18.
Conclusions: These results demonstrate variability in the duration of treatment effect, which supports the use of flexible and individualized dosing intervals for the treatment of ULPSS. The duration of treatment effect was ≥14 weeks after most treatments; however, a considerable proportion of patients experienced effects lasting up to 20 weeks.
[Thesis] Ubiquitous and Wearable Computing Solutions for Enhancing Motor Rehabilitation of the Upper Extremity Post-Stroke
Coffey, Aodhan L. (2016) Ubiquitous and Wearable Computing Solutions for Enhancing Motor Rehabilitation of the Upper Extremity Post-Stroke. PhD thesis, National University of Ireland Maynooth.
A stroke is the loss of brain function caused by a sudden interruption in the blood supply of the brain. The extent of damage caused by a stroke is dependent on many factors such as the type of stroke, its location in the brain, the extent of oxygen deprivation and the criticality of the neural systems affected. While stroke is a non-cumulative disease, it is nevertheless a deadly pervasive disease and one of the leading causes of death and disability worldwide. Those fortunate enough to survive stroke are often left with some form of serious long-term disability. Weakness or paralysis on one side of the body, or in an individual limb is common after stroke. This affects independence and can greatly limit quality of life.
Stroke rehabilitation represents the collective effort to heal the body following stroke and to return the survivor to as normal a life as possible. It is well established that rehabilitation therapy comprising task-specific, repetitive, prolonged movement training with learning is an effective method of provoking the necessary neuroplastic changes required which ultimately lead to the recovery of function after stroke. However, traditional means of delivering such treatments are labour intensive and constitute a significant burden for the therapist limiting their ability to treat multiple patients. This makes rehabilitation medicine a costly endeavour that may benefit from technological contributions. As such, stroke has severe social and economic implications, problems exasperated by its age related dependencies and the rapid ageing of our world. Consequently these factors are leading to a rise in the number living with stroke related complications. This is increasing the demand for post stroke rehabilitation services and places an overwhelming amount of additional stress on our already stretched healthcare systems.
Therefore, new innovative solutions are urgently required to support the efforts of healthcare professionals in an attempt to alleviate this stress and to ultimately improve the quality of care for stroke survivors. Recent innovations in computer and communication technology have lead to a torrent of research into ubiquitous, pervasive and distributed technologies, which might be put to great use for rehabilitative purpose. Such technology has great potential utility to support the rehabilitation process through the delivery of complementary, relatively autonomous rehabilitation therapy, potentially in the comfort of the patient’s own home.
This thesis describes concerted work to improve the current state and future prospects of stroke rehabilitation, through investigations which explore the utility of wearable, ambient and ubiquitous computing solutions for the development of potentially transformative healthcare technology. Towards this goal, multiple different avenues of the rehabilitation process are explored, tackling the full chain of processes involved in motor recovery, from brain to extremities. Subsequently, a number of cost effective prototype devices for use in supporting the ongoing rehabilitation process were developed and tested with healthy subjects, a number of open problems were identified and highlighted, and tentative solutions for home-based rehabilitation were put forward. It is envisaged that the use of such technology will play a critical role in abating the current healthcare crisis and it is hoped that the ideas presented in this thesis will aid in the progression and development of cost effective, efficacious rehabilitation services, accessible and affordable to all in need.
[ARTICLE] Effect of early use of AbobotulinumtoxinA after stroke on spasticity progression: Protocol for a randomised controlled pilot study in adult subjects with moderate to severe upper limb spasticity (ONTIME pilot) – Full Text
Approximately 15 million people suffer a stroke annually, up to 40% of which may develop spasticity, which can result in impaired limb function, pain and associated involuntary movements affecting motor control.
Robust clinical data on spasticity progression, associated symptoms development and functional impairment is scarce. Additionally, maximal duration of muscle tone reduction following botulinum toxin type A (BoNT-A) injections remains undetermined. The ONTIME pilot study aims to explore these issues and evaluate whether abobotulinumtoxinA 500 U (Dysport®; Ipsen) administered intramuscularly within 12 weeks following stroke delays the appearance or progression of symptomatic (disabling) upper limb spasticity (ULS).
ONTIME is a 28-week, phase 4, randomised, double-blind, placebo-controlled, exploratory pilot study initiated at four centres across Malaysia, the Philippines, Singapore and Thailand. Subjects (n = 42) with moderate to severe ULS (modified Ashworth scale [MAS] score ≥2) in elbow flexors or pronators, wrist flexors, or finger flexors will be recruited. Subjects will be randomised 2:1 to abobotulinumtoxinA 500 U or placebo (single dose 2–12 weeks after first-ever stroke).
Primary efficacy will be measured by time between initial injection and visit at which reinjection criteria (MAS score ≥2 in the primary targeted muscle group and appearance or reappearance of symptomatic ULS) are met. Follow-up visits will be 4-weekly to a maximum of 28 weeks.
This pilot study will facilitate the design and sample size calculation of further confirmatory studies, and is expected to provide insights into the optimal management of post-stroke patients, including timing of BoNT-A therapy and follow-up duration.
An estimated 15 million people suffer a stroke annually ; of whom, up to 40% develop post-stroke spasticity, a state of velocity-dependent increase in tonic stretch reflexes (‘muscle tone’) with exaggerated tendon jerks  most commonly affecting upper limbs ; ; ;  ; . Post-stroke spasticity impedes active and passive functioning of affected limb(s), impairs activities of daily living and requires long-term treatment; associated healthcare costs are up to four-fold greater than for stroke survivors without spasticity . Furthermore, spasticity may involve pain and involuntary movements, interfering with dressing, gait, balance and walking speed, and can disrupt rehabilitation . Without functional improvement, secondary musculoskeletal complications such as contractures and deformity may develop .
Data on the proportion of patients with post-stroke spasticity developing disability are scarce. One survey (N = 140) reported a prevalence of 17% spasticity and 4% disabling spasticity with a year . Upper limb involvement and age <65 years were associated with disabling spasticity in this study . In other studies, over a third of individuals developed spasticity within a year, including 20% with severe spasticity  ; , suggesting higher rates of disabling spasticity than those reported by Lundström et al. .
Studies evaluating the timeframe for developing spasticity symptoms post-stroke are also few, with small cohorts (around 100 patients), but suggest the prevalence and severity of spasticity increases within a year post-stroke ; ; ; ;  ; . Certain studies indicate that spasticity symptoms and muscle tone changes are apparent in up to 25% of stroke victims within 2 weeks ;  ; . One study reported increased muscle tone as an early risk factor for developing severe disabling spasticity, particularly if it affected more than two joints, or was associated with a modified Ashworth scale (MAS) score ≥2 in one affected joint within 6 weeks post-stroke . Indeed, spasticity may persist , and the severity of upper limb spasticity (ULS) may increase over time, most commonly affecting anti-gravity muscles, during the first 2 weeks and at 3 months post-stroke .
AbobotulinumtoxinA is an effective focal intervention for reducing ULS  and coupled with neurorehabilitation is recommended in standard clinical practice  ; . Treatment with botulinum toxin A (BoNT-A) is generally delayed in post-stroke spasticity until patients show clinical signs of increased muscle tone, usually about 3 months following stroke , despite evidence that symptoms begin much earlier.
Recent studies aimed to evaluate whether earlier post-stroke treatment with BoNT-A may prevent disabling spasticity development ;  ;  and demonstrate that BoNT-A administered within 3 months provides sustained improvement in muscle tone. However, there is a paucity of robust clinical data on spasticity progression timeframes, associated symptom development, functional impairment, and maximal duration of muscle tone reduction with BoNT-A.
The ONTIME pilot study explores these foregoing issues to establish whether treatment with abobotulinumtoxinA (Dysport®) within 2–12 weeks post-stroke might delay symptomatic or disabling spasticity development, and to assess the duration of this effect. Importantly, this study incorporates composite measure of active and passive functionality, involuntary movements and pain.
Continue —> Effect of early use of AbobotulinumtoxinA after stroke on spasticity progression: Protocol for a randomised controlled pilot study in adult subjects with moderate to severe upper limb spasticity (ONTIME pilot)
[Master Thesis] A smart brace to support spasticity management in post-stroke rehabilitation – Full Text PDF
A smart brace to support spasticity management in poststroke rehabilitation
This report covers the design of a product to help stroke survivors who are suffering from chronic spasticity manage their everyday activities. In the Netherlands alone, 44.000 people suffer from a Cerebro-Vascular Accident (CVA) each year. A CVA, more commonly known as a stroke, results in brain trauma with afflictions such as paralysis, fatigue and spasticity. It is possible to recover some, if not all, motor function though intensive physiotherapy, which requires long-term stay at a rehabilitation clinic in severe cases. Due to limited room and staff, only 12% of stroke survivors end up rehabilitating in a clinic. The remaining survivors are sent home, and will to travel to the clinic 3-5 times per week for therapy as part of the outpatient rehabilitation. Adjuvo Motion, a young start-up, aims to improve the situation of stroke survivors by bringing the rehabilitation centre to their home through the Adjuvo Platform, which allows them to perform exercises in the context of virtual tasks. They proposed an assignment to extend their product portfolio with a Range of Motion assessment device that is suited for those suffering from spasticity. Spasticity occurs in roughly 60% of stroke survivors with varying degrees of intensity. It is caused by the damaged parts of the brain sending conflicting signals to the muscles, causing them to contract. This inhibits the survivor’s ability to perform daily tasks, but can be solved temporarily with stretching exercises. A solution to compensate for these spastic forces using a passive-assist device was proposed at the start of this project. The project was divided into four stages: Analysis, Synthesis, Embodiment and Evaluation. During the Analysis stage, interviews with a Physiotherapist and stroke survivor and literature studies regarding anatomy, the state of the art and relevant technologies were used to create a framework for the design of a smart passive-assist glove. Looking at competing products, there is a demand for passive assist and Range of Motion assessment functionalities, yet a combination of these in a single device is not yet present in the market. During the Synthesis stage, the design problem of the passive assist device was split into three groups: Orthoses; the connections to the body, Passive Assist; the compensation medium, and RoM measurement; the sensing mechanism(s). These three groups were further split into sub-problems, the solutions to which were compiled into a Morphological Chart. By combining the solution within this chart, three promising concept designs were created: One upgrade to the existing sensor glove, one full integration of sensing and passive assist, and one passive assist glove with removeable sensors. To evaluate these concepts, eight criteria were established and weighted with the help of a physiotherapist. In order to create an objective assessment, the criteria were kept strictly quantitative and the three designs were first scored against the Raphael Smart Glove by Neofect using early prototypes. These scores were then used to evaluate the designs relative to each other, which resulted in an overall higher score for the concept with separable electronics. Making the sensor part of the brace removeable allowed the product to be used during daily life as well as physiotherpy exercises, and proved a key benefit in keeping the product clean. Based on the chosen design, four iterations of prototypes were made, which were tested with healthy subject. During this stage, it became clear that flex sensors are be best suited to create a range of motion assessment for spastic stroke patients, since it is less important to know how well they perform a task, and more important to know if they can actually perfrom it. Based on a quantified use case, the four sub-assemblies; the Wrist Wrap, Finger Modules and Sensor Module, and their connections were materialized in the Embodiment design stage. When selecting production methods, the main challenge was a small batch size of 1000 units, which made conventional techniques for mass production, such as Injection Molding, less attractive. This stage ended in an assesment of the product’s production price and durability: The product would cost €250 to make, and would last for 2.5 years before the Velcro connection on the Wrist Wrap would become too weak to sustain the spasticity forces. In the Evaluation stage, the product was evaluated on the seven most important requirements established during the analysis stage. For several of these, a user test was performed, again with healthy subject. While the Adjuvo Auxilius passed most theoretical requirements, the user tests on healthy subjects could not be used to draw any conclusions regarding its effectiveness on spastic stroke patients. However, since the product’s working principle is based on that of existing spasticity compensation products, the prediction is that the Auxilius will be an effective therapy supplement. The result of this project is the Adjuvo Auxilius; a spasticity-compensation glove with modular sensors, which can be added to allow virtual (stretching) exercises through the Adjuvo Motion’s platform. The results of these exercises are used to create a remote assessment of the patients motor skills, and to adjust the therapy if needed.
[THESIS] Returning to driving post-stroke: Identifying key factors for best practice decision making over the recovery trajectory -Full text PDF
The purpose of this thesis is to examine the process of returning to driving post-stroke in order to contribute to best practice decision making. A decision tree is suggested to build patient-centred procedures for returning to driving along the post-stroke recovery trajectory.
Part one reviews literature on the return to driving process post-stroke and identifies gaps in knowledge. The stroke recovery trajectory’s three main phases of recovery (acute, rehabilitation and community care) are outlined and act as a framework for the thesis structure. Part two of the thesis describes five separate but related studies carried out to address the research gaps identified.
The first study is a qualitative study that examines attitudes and perceptions of stroke survivors from one to 16 weeks post-stroke. Independence was found to be the primary motivator in stroke survivors’ decisions about fitness to drive. However, during the acute phase stroke survivors were focused on their physical recovery, not returning to driving. Study participants had little knowledge of return to driving procedures or legislation, despite information being available. Gender differences were apparent in factors affecting the return to driving decision making.
The second study examines the psychometric property of practice effect on the Useful Field of View (UFOV, Ball & Owsley, 1993) a pre-driving screening assessment. UFOV scores have been found to be associated with on-road driving assessment scores (George & Crotty, 2010) and used in medical recommendations. Study participants were all stroke survivors with a control group performing the UFOV at three months and assessment group at one, two and three months post-stroke. Findings suggest there was no practice effect in relation to a single three month post-stroke time point. Timing of reassessment was also examined.
The third study examined self-perceived driving confidence measured by the Adelaide Driving Self Efficacy Scale (ADSES, George et al., 2007; George & Crotty, 2010) and driving habits. Results indicated there was a significant statistical association between low self-perceived driving confidence and lower kilometres driven per week, reduce driving scope, driving closer to home and avoiding challenging driving situations.
The fourth study explored self-perceived driving confidence of post-stroke drivers and their non-stroke, aged-matched driving peers measured by the ADSES. No difference was found, suggesting once stroke survivors have returned to driving they have the same levels of selfperceived driving confidence and potential driving scope as their non-stroke driving peers.
The final study focused on decisions to relinquish a driver’s licence among the older Australian general population and used a novel Discrete Choice Experiment (DCE) methodological approach. A general population was used to establish a norm with which future research on specific chronic conditions such as stroke could make comparison. Recommendation of General Practitioners’ (GPs), participants’ local doctors was found to be the primary influencing factor in the decision of older Australians to relinquish their driver’s licence. Advice from family and friends, age and crash risk in the next year were also influencing factors. The costs and availability of public transport options were not influencing factors.
The last chapter of this thesis is the Discussion section which identifies the common themes emerging along with limitations and recommendations for future research directions.
[ARTICLE] When Does Return of Voluntary Finger Extension Occur Post-Stroke? A Prospective Cohort Study – Full Text
Objectives: Patients without voluntary finger extension early post-stroke are suggested to have a poor prognosis for regaining upper limb capacity at 6 months. Despite this poor prognosis, a number of patients do regain upper limb capacity. We aimed to determine the time window for return of voluntary finger extension during motor recovery and identify clinical characteristics of patients who, despite an initially poor prognosis, show upper limb capacity at 6 months post-stroke.
Methods: Survival analysis was used to assess the time window for return of voluntary finger extension (Fugl-Meyer Assessment hand sub item finger extension≥1). A cut-off of ≥10 points on the Action Research Arm Test was used to define return of some upper limb capacity (i.e. ability to pick up a small object). Probabilities for regaining upper limb capacity at 6 months post-stroke were determined with multivariable logistic regression analysis using patient characteristics.
Results: 45 of the 100 patients without voluntary finger extension at 8 ± 4 days post-stroke achieved an Action Research Arm Test score of ≥10 points at 6 months. The median time for regaining voluntary finger extension for these recoverers was 4 weeks (lower and upper percentile respectively 2 and 8 weeks). The median time to return of VFE was not reached for the whole group (N = 100). Patients who had moderate to good lower limb function (Motricity Index leg≥35 points), no visuospatial neglect (single-letter cancellation test asymmetry between the contralesional and ipsilesional sides of <2 omissions) and sufficient somatosensory function (Erasmus MC modified Nottingham Sensory Assessment≥33 points) had a 0.94 probability of regaining upper limb capacity at 6 months post-stroke.
Conclusions: We recommend weekly monitoring of voluntary finger extension within the first 4 weeks post-stroke and preferably up to 8 weeks. Patients with paresis mainly restricted to the upper limb, no visuospatial neglect and sufficient somatosensory function are likely to show at least some return of upper limb capacity at 6 months post-stroke.
Voluntary finger extension (VFE) is an important early predictor of recovery of upper limb capacity at 6 months post-stroke[1;2]. Patients without VFE within the first days post-stroke have been suggested to have a poor prognosis for regaining some upper limb capacity at 6 months[1–3]. Absence of VFE reflects the loss of functional corticospinal tract integrity, acknowledging that the hand muscles are almost solely innervated by contralateral corticospinal pathways. Indirect bilateral innervation of the hand muscles by the reticulospinal tract may also contribute to hand motor control after stroke. However, it remains unclear if the reticulospinal system can influence the digital extensor muscles of the paretic hand.
Despite an initially poor prognosis, some patients without VFE within the first days after stroke do regain upper limb capacity at 6 months. In view of the lack of evidence-based therapies for patients without VFE[7;8], this return of VFE seems most likely to be driven by spontaneous neurobiological processes such as alleviation of diaschisis. Unfortunately, the clinical characteristics as well as the optimal time window for recovery of VFE are unknown, due to lack of prospective cohort studies in which patients are assessed serially at fixed times post-stroke[10;11]. More knowledge regarding this time window is important for future prognostic algorithm development. Up till now, the most optimal timing and added value of neurophysiological and neuroimaging measurements with respect to clinical measurements like VFE are unclear.
The aims of the present study were therefore (1) to determine the clinical time window for return of VFE in ischemic stroke patients without VFE in the first days post-stroke, and (2) to identify clinical characteristics for the return of some upper limb capacity in these patients within the first 6 months after stroke. We hypothesized that return of VFE would occur within the purported time window of spontaneous neurobiological recovery between 0 and 10 weeks after stroke onset[10;12]. We also hypothesized that patients with lesions affecting upper limb function who exhibit no other neurological impairments such as visuospatial neglect and somatosensory dysfunction would have a high probability of regaining some upper limb capacity at 6 months[13–15].
In this paper, modeling of the arm rehabilitation device using system identification technique is presented.
Patients who have post-stroke may lose control of their upper limb. If they are treated with effective rehabilitation training, the patients can restore their upper limb motion functions and working abilities. These rehabilitation devices are used to recover the movement of arm after stroke. Robot assisted therapy systems need three elements which are algorithms, robot hardware and computer system. An accurate system modelling is crucially important to represent the system well. Inaccurate model could diminish the overall control system later on.
The objective of this work is to development mathematical modeling of the arm rehabilitation device by using System Identification from experimental data. Several transfer functions are evaluated in order to choose the best performances that represent the system. It must show a good criteria based on the best fitness percentage, stability of the location of poles and zero and also the frequency response characteristics. The derived model is validated via simulation for stability analysis. It is expected that a stable model with an acceptable level of accuracy would be developed for further control system design.
From neuronal to muscular disability, the field of rehabilitation robotics has been working to find ways to increase the efficacy of treatment options that therapists provide on a daily basis. There are numerous systems of robot therapy that have been devised and studied in order to achieve this. It is the aim of this paper to focus on the rehabilitation strategies for upper limb motor control—post-stroke, the clinical effectiveness of said treatments along with data analysis methods, and summarize the road ahead in the field. Additionally, proposed methods not yet considered and tested will be discussed, including further integration of virtual reality.