Posts Tagged UE

[Abstract + References] Effect of Virtual Reality Rehabilitation Program with RAPAEL Smart Glove on Stroke Patient’s Upper Extremity Functions and Activities of Daily Living

Abstract

Purpose : This study examined the effects of a virtual reality rehabilitation program on stroke patients’ upper extremity functions and activities of daily living (ADL).

Methods : The subjects were equally and randomly divided into an experimental group (n=16) to whom a virtual reality rehabilitation program was applied and a control group (n=16) who received traditional occupational therapy. The intervention was applied five times per week, 30 minutes per each time, for six weeks. Jebsen-Taylor hand function test was conducted and the subjects’ Manual Function Test was measured to examine their upper extremity functions before and after the treatment intervention, and a Korean version of modified Barthel index was calculated to look at their activities of daily living.

Results : After the intervention, the upper extremity functions and activities of daily living of the participants in both groups significantly improved (p<.05). However, the improvements in these parameters among the participants in the virtual reality rehabilitation program were significantly greater than those in the control group (p>.05).

Conclusion : The virtual reality rehabilitation program is a stable and reliable intervention method for enhancing the upper limb functions and activities of daily living of stroke patients.

References

  1. Wolf SL, Lecraw DE, Barton LA, et al(1989). Forced use of hemiplegic upper extremities to reverse the effect of learned nonuse among chronic stroke and head-injured patients. Exp Neurol, 104(2), 125-132. https://doi.org/10.1016/S0014-4886(89)80005-6
  2. Yang NY, Park HS, Yoon TH, et al(2018). Effectiveness of motion-based virtual reality training(Joystim) on cognitive function and activities of daily living in patients with stroke. J Rehabil Welfare Eng & Ass Tech, 12(1), 10-19.
  3. Van Peppen RP, Kwakkel G, Wood-Dauphinee S, et al(2004). The impact of physical therapy on functional outcomes after stroke: what’s the evidence. Clin Rehabil, 18(8), 833-862. https://doi.org/10.1191/0269215504cr843oa
  4. Winstein CJ, Wolf SL, Dromerick AW, et al(2016). Effect of a task-oriented rehabilitation program on upper extremity recovery following motor stroke: the ICARE randomized clinical trial. J Am Med Assoc, 315(6), 571-581. https://doi.org/10.1001/jama.2016.0276
  5. Asher IE(1996). Occupational therapy assessment tools: An annotated index. 2nd ed, Bethesda, MD: American Occupational Therapy Association, pp.310-315.
  6. Bae WJ, Kam KY(2017). Effects of immersive virtual reality intervention on upper extremity function in post-stroke patients. J Korean Soc Integrative Med, 5(3), 1-9. https://doi.org/10.15268/KSIM.2017.5.3.001
  7. Baek SW(2017). Effect of mirror therapy with functional electrical stimulation on upper extremity function and activities of daily living performance in chronic stage stroke patients. Graduate school of Yonsei University, Republic of Korea, Master’s thesis.
  8. Broeren J, Rydmark M, Sunnerhagen KS(2004). Virtual reality and haptics as a training device for movement rehabilitation after stroke: a single-case study. Arch Phys Med Rehabil, 85(8), 1247-1250. https://doi.org/10.1016/j.apmr.2003.09.020
  9. Cheng X, Zhou Y, Zuo C, et al(2011). Design of an upper limb rehabilitation robot based on medical theory. Procedia Eng, 15, 688-692. https://doi.org/10.1016/j.proeng.2011.08.128
  10. Dault MC, de Haart M, Geurts AC, et al(2003). Effects of visual center of pressure feedback on postural control in young and elderly healthy adults and in stroke patients. Hum Mov Sci, 22(3), 221-236. https://doi.org/10.1016/S0167-9457(03)00034-4
  11. Hong WJ(2015). Short-term effect of robot-assisted therapy on arm reaching in subacute stroke patients. Graduate school of Yonsei University, Republic of Korea, Master’s thesis.
  12. Jebsen RH, Taylor NE, Trieschmann RB, et al(1969). An objective and standardized test of hand function. Arch Phys Med Rehabil, 50(6), 311-319.
  13. Kim YG(2015). The effect on korean virtual reality rehabilitation system(VREHAT) in balance, upper extremity function and activities of daily living(ADL) in brain injury. J Rehabil Res, 19(2), 257-276.
  14. Kim JH(2011). The effects of training using virtual reality games on stroke patients’ functional recovery. Graduate school of Dongshin University, Republic of Korea, Master’s thesis.
  15. Kim JH, Kim IS, Han TR(2007). New scoring system for Jebsen hand function test. Ann Rehabil Med, 31(6), 623-629.
  16. Kwakkel G, Kollen BJ, Krebs HI(2008). Effects of robot-assisted therapy on upper limb recovery after stroke: a systematic review. Neurorehabil Neural Repair, 22(2), 111-121. https://doi.org/10.1177/1545968307305457
  17. Lee HM(2013). Effects of virtual reality based viode game and rehabilitation exercise on the balance and activities of daily living of chronic stroke patients. J Korean Soc Phys Med, 8(2), 201-207. https://doi.org/10.13066/kspm.2013.8.2.201
  18. Lee SH(2009). Correlation between ACLT and FIM, MMSE-K, and MFT in stroke patients. The Journal of the Korea Contents Association, 9(9), 287-294. https://doi.org/10.5392/JKCA.2009.9.9.287
  19. Lee MJ, Koo HM(2017). The effect of virtual reality-based sitting balance training program on ability of sitting balance and activities of daily living in hemiplegic patients. J Korean Soc Integrative Med, 5(3), 11-19. https://doi.org/10.15268/KSIM.2017.5.3.011
  20. Michaelsen SM, Dannenbaum R, Levin MF(2006). Task-specific training with trunk restraint on arm recovery in stroke: randomized control trial. Stroke, 37(1), 186-192.
  21. Neofect(2016). RAPAEL smart solution manual. Neofect. Korea.
  22. Park CS, Park SW, Kim KM, et al(2005). The interrater and intrarater reliability of Korean Wolf Motor Function Test. Ann Rehabil Med, 29(3), 317-322.
  23. Peurala SH, Kantanen MP, Sjogren T, et al(2012). Effectiveness of constraint-induced movement therapy on activity and participation after stroke: a systematic review and meta-analysis of randomized controlled trials. Clin Rehabil, 26(3), 209-223. https://doi.org/10.1177/0269215511420306
  24. Prange GB, Jannink MJ, Groothuis-Oudshoorn CG, et al(2006). Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke. J Rehabil Res Dev, 43(2), 171-184. https://doi.org/10.1682/JRRD.2005.04.0076
  25. Sears ED, Chung KC(2010). Validity and responsiveness of the Jebsen-Taylor hand function test. J Hand Surg Am, 35(1), 30-37.
  26. Shah S, Vanclay F, Cooper B(1989). Improving the sensitivity of the Barthel Index for stroke rehabilitation. J Clin Epidemiol, 42(8), 703-709. https://doi.org/10.1016/0895-4356(89)90065-6
  27. Shin JH, Kim MY, Lee JY, et al(2016). Effects of virtual reality-based rehabilitation on distal upper extremity function and health-related quality of life: a single-blinded, randomized controlled trial. J Neuroeng Rehabil, 13(1), 17. https://doi.org/10.1186/s12984-016-0125-x
  28. Song CH, Seo SM, Lee KJ, et al(2011). Video game-based exercise for upper-extremity function, strength, visual perception of stroke patients. J Spe Edu & Rehabil Sci, 50(1), 155-180.
  29. Thieme H, Morkisch N, Mehrholz J, et al(2019). Mirror therapy for improving motor function after stroke. Stroke, 50(2), 26-27.

via Effect of Virtual Reality Rehabilitation Program with RAPAEL Smart Glove on Stroke Patient’s Upper Extremity Functions and Activities of Daily Living -Journal of The Korean Society of Integrative Medicine | Korea Science

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[ARTICLE] The effect of the Bobath therapy programme on upper limb and hand function in chronic stroke individuals with moderate to severe deficits – Full Text

Abstract

Background/Aims

The Bobath concept has long been used to improve postural control and limb function post-stroke, yet its effect in patients with deficits have not been clearly demonstrated. This study aimed to investigate the effect of the latest Bobath therapy programme on upper limb functions, muscle tone and sensation in chronic stroke individuals with moderate to severe deficits.

Methods

A pre–post test design was implemented. The participants were chronic stroke individuals (n=26). Home-based intervention based on the Bobath concept was administered 3 days per week for 6 weeks (20 repetitions × 3 sets per task each session). Outcome measures consisted of the Wolf Motor Function Test, Fugl-Meyer Assessment for the upper extremity, Modified Ashworth Scale, and the Revised Nottingham Sensory Assessment. Data were analysed using the Wilcoxon Signed rank test.

Results

Almost all items of the Wolf Motor Function Test and the Fugl-Meyer Assessment for the upper extremity demonstrated statistically significant differences post-intervention. Finger flexor muscle tone and stereognosis were also significantly improved.

Conclusions

The 6-week Bobath therapy programme could improve upper limb function and impairments in chronic stroke individuals with moderate to severe deficits. Its effects were also demonstrated in improving muscle tone and cortical sensation.

INTRODUCTION

Stroke is a global public health problem that leads to significant disabilities (World Health Organization, 2014). After discharge from a hospital, patients who have experienced stroke return to the community and many do not have access to physical therapy. Around 65% of patients who had experienced a stroke were unable to use their hemiparetic upper limb (Bruce and Dobkin, 2005). Those with moderate to severe arm deficits have difficulty in reaching to grasp, delay in time to maximal grip aperture, prolonged movement time, and a lack of accuracy (Michaelsen et al, 2009). A number of interventions have been proven to be effective in improving upper limb function post-stroke. However, there is little evidence of the effectiveness of these interventions for those with severe deficits.

The therapy programme based on the Bobath concept has been shown to improve upper limb function in individuals who have experienced chronic stroke (Huseyinsinoglu et al, 2012Carvalho et al, 2018). The Bobath concept has been in evolution and the present clinical framework incorporates the integration of postural control and quality of task performance, selective movement, and the role of sensory information to promote normal movement pattern. Therapeutic activities involved movement facilitation together with patient’s active participation in practice to improve motor learning; nevertheless, implementation time varied across studies (Vaughan-Graham et al, 2009Vaughan-Graham and Cott, 2016).

Among the few studies of patients with chronic stroke, none focused on the rehabilitation of patients with different degrees of deficit severity in the community. Moreover, previous studies using the Bobath concept were all conducted in clinical settings (Platz et al, 2005Huseyinsinoglu et al, 2012).[…]

 

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[Abstract] Home-based upper extremity stroke therapy using a multi-user virtual reality environment: a randomized trial

Abstract

Objective

To compare participation and subjective experience of participants in both home-based multi-user VR therapy and home-based single-user VR therapy.

Design

Crossover, randomized trial

Setting

Initial training and evaluations occurred in a rehabilitation hospital; the interventions took place in participants’ homes

Participants

Stroke survivors with chronic upper extremity impairment (n=20)

Interventions

4 weeks of in-home treatment using a custom, multi-user virtual reality system (VERGE): two weeks of both multi-user (MU) and single-user (SU) versions of VERGE. The order of presentation of SU and MU versions was randomized such that participants were divided into two groups, first multi-user (FMU) and first single-user (FSU).

Main Outcome Measures

We measured arm displacement during each session (meters) as the primary outcome measure. Secondary outcome measures include: time participants spent using each MU and SU VERGE, and Intrinsic Motivation Inventory (IMI) scores. Fugl-Meyer Upper-Extremity (FMUE) score and compliance with prescribed training were also evaluated. Measures were recorded before, midway, and after the treatment. Activity and movement were measured during each training session.

Results

Arm displacement during a session was significantly affected the mode of therapy (MU: 414.6m, SU: 327.0m, p=0.019). Compliance was very high (99% compliance for MU mode and 89% for SU mode). Within a given session, participants spent significantly more time training in the MU mode than in the SU mode (p=0.04). FMUE score improved significantly across all participants (Δ3.2, p=0.001).

Conclusions

Multi-user VR exercises may provide an effective means of extending clinical therapy into the home.

via Home-based upper extremity stroke therapy using a multi-user virtual reality environment: a randomized trial – Archives of Physical Medicine and Rehabilitation

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[ARTICLE] An Exploratory Study of Predictors of Response to Vagus Nerve Stimulation Paired with Upper-Limb Rehabilitation After Ischemic Stroke – Full Text

Abstract

We have previously shown the safety and feasibility of vagus nerve stimulation (VNS) paired with upper-limb rehabilitation after ischemic stroke. In this exploratory study, we assessed whether clinical and brain MRI variables predict response to treatment. We used data from two completed randomised and blinded clinical trials (N = 35). All participants had moderate to severe upper-limb weakness and were randomised to 6-weeks intensive physiotherapy with or without VNS. Participants had 3 T brain MRI at baseline. The primary outcome was change in Fugl-Meyer Assessment, upper-extremity score (FMA-UE) from baseline to the first day after therapy completion. We used general linear regression to identify clinical and brain MRI predictors of change in FMA-UE. VNS-treated participants had greater improvement in FMA-UE at day-1 post therapy than controls (8.63 ± 5.02 versus 3.79 ± 5.04 points, t = 2.83, Cohen’s d = 0.96, P = 0.008). Higher cerebrospinal fluid volume was associated with less improvement in FMA-UE in the control but not VNS group. This was also true for white matter hyperintensity volume but not after removal of an outlying participant from the control group. Responders in the VNS group had more severe arm impairment at baseline than responders to control. A phase III trial is now underway to formally determine whether VNS improves outcomes and will explore whether these differ in people with more severe baseline upper-limb disability and cerebrovascular disease.

Introduction

Vagus nerve stimulation (VNS) paired with upper-limb rehabilitation is a potential novel treatment for arm weakness after stroke. VNS triggers release of plasticity promoting neuromodulators, such as acetylcholine and norepinephrine, throughout the cortex1. Timing this with motor training drives task-specific plasticity in the motor cortex2 and VNS paired with rehabilitative training has been shown to improve recovery in different preclinical models of stroke, both in comparison to VNS alone and rehabilitation alone3,4. These improvements were associated with synaptic reorganization of cortical motor networks and recruitment of residual motor neurons controlling the impaired forelimb5. Two clinical studies comparing VNS paired with upper-limb rehabilitation with upper-limb rehabilitation alone have shown it to be acceptably safe and feasible and that it may improve arm weakness after ischemic stroke6,7.

Arm weakness is the most common symptom of stroke and approximately half of stroke survivors with arm weakness have prolonged disability, which is associated with reduced quality of life8,9. Restoration of arm function after stroke is a priority for many stroke survivors10. However, recovery of motor function after stroke varies, so identifying factors that help predict response is important to aid patient selection and identify those most likely to respond. This is particularly true where therapies are invasive (involving surgery) and/or time consuming; VNS requires implantation of a nerve stimulator which is costly and associated with risks of anaesthesia, a small risk of infection and small risk of vocal cord palsy. There are several clinical and brain imaging markers that predict cognitive and functional recovery after stroke including age, level of impairment, white matter hyperintensity (WMH) volume, stroke lesion volume, corticospinal tract damage and blood pressure level11,12,13.

In the present study, we combined clinical and brain magnetic resonance imaging (MRI) data from our two previous randomised trials of VNS paired with rehabilitation for the upper-limb after ischemic stroke6,7. We performed exploratory analyses to assess predictors of response to VNS paired with upper-limb rehabilitation. Our goal was to identify predictive factors for further study that may help with patient selection for this promising novel therapy. […]

 

Continue —->  An Exploratory Study of Predictors of Response to Vagus Nerve Stimulation Paired with Upper-Limb Rehabilitation After Ischemic Stroke | Scientific Reports

figure1

Illustration of brain MRI measures obtained. (A) Raw FLAIR image. (B) Segmentation of white matter hyperintensities (WMH; bright red) and ischaemic stroke infarct volumes (royal blue). (C) Estimate of the left (cyan) and right (pink) corticospinal tracts. (D) Interaction between stroke lesion (dull red) and corticospinal tract (light blue) in a 3D rendering. Images A and B come from the same patient, C and D are from separate patients and all are shown in neurological (“left is left”) convention.

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[Abstract] Effects of Bihemispheric Transcranial Direct Current Stimulation on Upper Extremity Function in Stroke Patients: A randomized Double-Blind Sham-Controlled Study

Abstract

Background and Purpose

Transcranial direct current stimulation (tDCS) is a treatment used in the rehabilitation of stroke patients aiming to improve functionality of the plegic upper extremity. Currently, tDCS is not routinely used in post stroke rehabilitation. The aim of this study was to establish the effects of bihemspheric tDCS combined with physical therapy (PT) and occupational therapy (OT) on upper extremity motor function.

Methods

Thirty-two stroke inpatients were randomised into 2 groups. All patients received 15 sessions of conventional upper extremity PT and OT over 3 weeks. The tDCS group (n = 16) also received 30 minutes of bihemispheric tDCS and the sham group (n = 16) 30 minutes of sham bihemispheric tDCS simultaneously to OT. Patients were evaluated before and after treatment using the Fugl Meyer upper extremity (FMUE), functional independence measure (FIM), and Brunnstrom stages of stroke recovery (BSSR) by a physiatrist blind to the treatment group

Results

The improvement in FIM was higher in the tDCS group compared to the sham group (P = .001). There was a significant within group improvement in FMUE, FIM and BSSR in those receiving tDCS (P = .001). There was a significant improvement in FIM in the chronic (> 6months) stroke sufferers who received tDCS when compared to those who received sham tDCS and when compared to subacute stroke (3-6 months) sufferers who received tDCS/sham.

Conclusions

Upper extremity motor function in hemiplegic stroke patients improves when bihemispheric tDCS is used alongside conventional PT and OT. The improvement in functionality is greater in chronic stroke patients.

via Effects of Bihemispheric Transcranial Direct Current Stimulation on Upper Extremity Function in Stroke Patients: A randomized Double-Blind Sham-Controlled Study – ScienceDirect

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[Abstract] The effects of a robot-assisted arm training plus hand functional electrical stimulation on recovery after stroke: a randomized clinical trial

Abstract

Objective

To compare the effects of unilateral, proximal arm robot-assisted therapy combined with hand functional electrical stimulation to intensive conventional therapy for restoring arm function in subacute stroke survivors.

Design

This was a single blinded, randomized controlled trial.

Setting

Inpatient Rehabilitation University Hospital.

Participants

Forty patients diagnosed with ischemic stroke (time since stroke <8 weeks) and upper limb impairment were enrolled.

Interventions

Participants randomized to the experimental group received 30 sessions (5 sessions/week) of robot-assisted arm therapy and hand functional electrical stimulation (RAT + FES). Participants randomized to the control group received a time-matched intensive conventional therapy (ICT).

Main outcome measures

The primary outcome was arm motor recovery measured with the Fugl-Meyer Motor Assessment. Secondary outcomes included motor function, arm spasticity and activities of daily living. Measurements were performed at baseline, after 3 weeks, at the end of treatment and at 6-month follow-up. Presence of motor evoked potentials (MEPs) was also measured at baseline.

Results

Both groups significantly improved all outcome measures except for spasticity without differences between groups. Patients with moderate impairment and presence of MEPs who underwent early rehabilitation (<30 days post stroke) demonstrated the greatest clinical improvements.

Conclusions

A robot-assisted arm training plus hand functional electrical stimulation was no more effective than intensive conventional arm training. However, at the same level of arm impairment and corticospinal tract integrity, it induced a higher level of arm recovery.

 

via The effects of a robot-assisted arm training plus hand functional electrical stimulation on recovery after stroke: a randomized clinical trial – ScienceDirect

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[Abstract] The influence of virtual reality on rehabilitation of upper limbs and gait after stroke: a systematic review – Full Text PDF

Abstract

Stroke is the leading cause of functional disability in adults. Its neurovascular origin and injury location indicates the possible functional consequences. Virtual rehabilitation (VR) using patient’s motion control is a new technological tool for conventional rehabilitation, allowing patterns of movements in varied environments, involving the patient in therapy through the playful components offered by VR applications. The objective of this systematic review is to collect data regarding the influence promoted by VR in upper limb and hemiparetic gait. Full articles published between 2009 and 2015 in english were searched and selected in PubMed, Cochrane and Pedro databases. Eleven articles included (5 for VR and upper limbs; 4 for VR, gait and balance; and 2 for VR and neural mechanisms). The articles included demonstrate efficacy in VR treatment in hemiparetic patients in the variables analyzed.

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via The influence of virtual reality on rehabilitation of upper limbs and gait after stroke: a systematic review | Journal of Innovation and Healthcare Management

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[ARTICLE] A comparison of the rehabilitation effectiveness of neuromuscular electrical stimulation robotic hand training and pure robotic hand training after stroke: A randomized controlled trial – Full Text

Highlights

The rehabilitation effects of the NMES robotic hand and robotic hand were compared.

Both training systems could significantly improve the motor function of upper limb.

The NMES robot was more effective than the pure robot.

NMES applied on distal muscle could benefit the recovery in the entire upper limb.

 

Abstract

Objective

To compare the rehabilitation effects of the electromyography (EMG)-driven neuromuscular electrical stimulation (NMES) robotic hand and EMG-driven robotic hand for chronic stroke.

Methods

This study was a randomized controlled trial with a 3-month follow-up. Thirty chronic stroke patients were randomly assigned to receive 20-session upper limb training with either EMG-driven NMES robotic hand (NMES group, n = 15) or EMG-driven robotic hand (pure group, n = 15). The training effects were evaluated before and after the training, as well as 3 months later, using the clinical scores of Fugl-Meyer Assessment (FMA), Modified Ashworth Scale (MAS), Action Research Arm Test (ARAT), and Functional Independence Measure (FIM). Session-by-session EMG parameters, including the normalized EMG activation level and co-contraction indexes (CIs) of the target muscles were applied to monitor the recovery progress in muscular coordination patterns.

Results

Both groups achieved significantly increased FMA and ARAT scores (p < 0.05), and the NMES group improved more (p < 0.05). A significant improvement in MAS was obtained in the NMES group (p < 0.05) but absence in the pure group. Meanwhile, better performance could be obtained in the NMES group in releasing the EMG activation levels and CIs than the pure group across the training sessions (p < 0.05).

Conclusion

Both training systems were effective in improving the long-term distal motor functions in upper limb, where the NMES robot-assisted training achieved better voluntary motor recovery and muscle coordination and more release in muscle spasticity.

Significance

This study indicated more effective distal rehabilitation using the NMES robot than the pure robot-assisted rehabilitation.

1. Introduction

Upper limb motor deficits are common after stroke, and observed in over 80% of stroke survivors [1,2]. Various rehabilitation devices have been purposed to assist human physical therapists to provide effective long-term rehabilitation programs [[3][4][5]]. Among them, rehabilitation robots and neuromuscular electrical stimulation (NMES) are most widely used in stroke rehabilitation practices. Rehabilitation robots have been recognized as efficient in such cases and could represent a cost-effective addition to conventional rehabilitation services because they provide highly intensive and repetitive training [[6][7][8][9]]. It has been reported that the integration of voluntary effort (e.g. electromyography, EMG) into robotic design could contribute significantly to motor recovery in stroke patients [6,10]. This is because an EMG-driven strategy can maximize the involvement of voluntary effort in the training, and its effectiveness at improving upper limb voluntary motor functions have been proved by many EMG-driven robot-assisted upper-limb training systems [[11][12][13]]. However, rehabilitation robots are unable to directly activate the desired muscle groups, which may only assist, or even dominate limb movement such as continuous passive motions (CPM) [14]. In addition, stroke patients usually cooperate with compensatory motions from other muscular activities to activate the target muscles, which may lead to ‘learned disuse’ [15]. However, NMES can effectively limit compensatory motions by stimulating specific muscles via cyclic electrical currents, which provides repetitive sensorimotor experiences [16]. With the advantage of precisely activating the target muscle, NMES has been reported to be effective in evoking sensory feedback, improving muscle force, and thus promoting motor function in stroke patients [17,18]. Nevertheless, training programs assisted by NMES alone are also suboptimal due to the difficulty of controlling movement trajectories and the early appearance of fatigue [19,20].

Accordingly, various NMES robot-assisted upper-limb training programs which combine these two unique techniques have been proposed to integrate the benefits and minimize the disadvantages [7,12,14,21,22]. The rehabilitation effectiveness of these combined systems has been investigated and reported to be effective in improving motor recovery. Several studies have compared the training outcomes of NMES robot-assisted training and other training programs. For example, Qian et al. [22] reported that NMES-robot-assisted upper-limb training could achieve better motor outcomes when compared with conventional therapies for subacute stroke patients. Meanwhile, another study which compared the training effects between robot-aided training with NMES and robot-aided training solely using the InMotion ARM™ Robot in the subacute period demonstrated that the active ranges of motion of the NMES robot-training group were significantly higher compared with the robot-training group [23]. Coincidentally, investigations into applications in chronic stroke patients have also been carried out. For instance, Hu et al. [14] proposed an EMG-driven NMES robot system for wrist training; this combined device improved muscle activation levels related to the wrist and reduced compensatory muscular activities at the elbow, while these training outcomes were absent for the EMG-driven robot-assisted training alone. Indeed, a similar study by another research group also achieved better rehabilitation outcomes on some clinical assessments using the combined system compared to robot-assisted therapy alone [21].

In the literature, most studies on current rehabilitation devices combining the NMES and robotic systems targeted the elbow and wrist joints [7,[21][22][23]], while very few focused on the hand and fingers [24]. In addition, a comparison of the training effects for hand rehabilitation between the NMES robot and other hand rehabilitation devices has not yet been adequately conducted. Indeed, the primary upper-limb disability post-stroke is the loss of hand function, and rehabilitation of the distal joints after stroke is much more difficult than the motor recovery of the proximal joints due to the compensatory motions from the proximal joints [25]. Hence, developing effective rehabilitation devices to minimize compensatory movements for hand motor recovery is especially meaningful for stroke rehabilitation. In our previous work, we developed an EMG-driven NMES robotic hand and suggested it for use in hand rehabilitation after stroke [26]. Our device provides fine control of hand movements and activates the target muscles selectively for finger extension/flexion, and its feasibility and effectiveness have been verified by a single group trial [12]. However, whether the long-term rehabilitation effect of this EMG-driven NMES robotic hand is comparable or even better than other hand rehabilitation devices are still unclear and need to be investigated quantitively. Therefore, the objective of this study is to compare the training effects of hand rehabilitation assisted by an NMES robotic hand and by a pure robotic hand though a randomized controlled trial with a 3-month follow-up (3MFU).

2. Methodology

2.1. Participants

This work was approved by the Human Subjects Ethics Sub-Committee of the Hong Kong Polytechnic University. A total of 53 stroke survivors were screened for the training from local districts. 30 participants with chronic stroke satisfied the following inclusion criteria: (1) The participants were at least 6 months after the onset of a singular and unilateral brain lesion due to stroke, (2) both the metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joints could be extended to 180° passively, (3) muscle spasticity during extension at the finger joints and the wrist joint was below 3 as measured by the Modified Ashworth Scale (MAS) [27], ranged from 0 (no increase in muscle tone) to 4 (affected part rigid), (4) detectable voluntary EMG signals from the driving muscle on the affected side (three times of the standard deviation (SD) above the EMG baseline), and (5) no visual deficit and able to understand and follow simple instructions as assessed by the Mini-Mental State Examination (MMSE > 21) [28].

This work involved a randomized controlled trial with a 3-month follow-up (3MFU). The potential participants were first told that the training program they would receive could be either NMES robotic hand training or pure robotic hand training, and all recruited participants submitted their written consent before randomization. Then, the recruited participants were randomly assigned into two groups according to a computer-based random number generator, i.e., the computer program generated either “1” (denoting the NMES robotic hand training group) or “2” (the pure robotic hand group) with an equal probability of 0.5 (Matlab, 2017, Mathworks, Inc.). Fig. 1 shows the Consolidated Standards of Reporting Trials flowchart of the training program.

Fig. 1

Fig. 1. The consolidated standards of reporting trials flowchart of the experimental design.

2.2. Interventions

For both groups, each participant was invited to attend a 20-session robotic hand training with an intensity of 3–5 sessions/week, completed within 7 consecutive weeks. The training setup of both groups is shown in Fig. 2. This robotic hand training system can assist with finger extension and flexion of the paretic limb for patients after stroke. In this work, real-time voluntary EMG detected from the abductor pollicis brevis (APB) and extensor digitorum (ED) muscles were used to control the respective hand closing and opening movements, and the threshold level of each motion phase was set at three times the SD above the EMG baseline at resting state [12]. For example, during the motions of finger flexion, once the EMG activation level of the APB muscle reached a preset threshold, the robotic hand would provide mechanical assistance for hand closing. Similarly, during the motions of finger extension, the robotic hand would assist with hand opening when the EMG activation level of the ED muscle reached a preset threshold. For the NMES robot group, synchronized support from the NMES and the robot were both provided. The NMES electrode pair (30 mm diameter; Axelgaard Corp., Fallbrook, CA, USA) was attached over the ED muscle to provide stimulation during finger extension. The outputs of NMES were square pulses with a constant amplitude of 70 V, a stimulation frequency of 40 Hz, and a manually adjustable pulse width in the range 0–300 μs. Before the training, the pulse width was set at the minimum intensity, which achieved a fully extended position of the fingers in each patient. During the training, NMES would be triggered by the EMG from the ED muscle first and then provided stimulation to the ED muscle to assist hand-opening motions for the entire phase of finger extension, while no assistance from NMES was provided during finger flexion to avoid the possible increase of finger spasticity after stimulation [29]. For the pure robot group, the difference between the two groups was that no NMES was applied in the pure robot group. A detailed account of the working principles of the robotic hand have been described in our previous work [12,30,31].

Fig. 2

Fig. 2. The experimental setup of the robotic hand training: (A) pure robotic hand group; (B) neuromuscular electrical stimulation (NMES) robotic hand group.

 […]

 

Continue —-> A comparison of the rehabilitation effectiveness of neuromuscular electrical stimulation robotic hand training and pure robotic hand training after stroke: A randomized controlled trial – ScienceDirect

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[Abstract] Robot-Assisted Arm Training in Chronic Stroke: Addition of Transition-to-Task Practice

Abstract

Background. Robot-assisted therapy provides high-intensity arm rehabilitation that can significantly reduce stroke-related upper extremity (UE) deficits. Motor improvement has been shown at the joints trained, but generalization to real-world function has not been profound.

Objective. To investigate the efficacy of robot-assisted therapy combined with therapist-assisted task training versus robot-assisted therapy alone on motor outcomes and use in participants with moderate to severe chronic stroke-related arm disability.

Methods. This was a single-blind randomized controlled trial of two 12-week robot-assisted interventions; 45 participants were stratified by Fugl-Meyer (FMA) impairment (mean 21 ± 1.36) to 60 minutes of robot therapy (RT; n = 22) or 45 minutes of RT combined with 15 minutes therapist-assisted transition-to-task training (TTT; n = 23). The primary outcome was the mean FMA change at week 12 using a linear mixed-model analysis. A subanalysis included the Wolf Motor Function Test (WMFT) and Stroke Impact Scale (SIS), with significance P <.05.

Results. There was no significant 12-week difference in FMA change between groups, and mean FMA gains were 2.87 ± 0.70 and 4.81 ± 0.68 for RT and TTT, respectively. TTT had greater 12-week secondary outcome improvements in the log WMFT (-0.52 ± 0.06 vs -0.18 ± 0.06; P = .01) and SIS hand (20.52 ± 2.94 vs 8.27 ± 3.03; P = .03).

Conclusion. Chronic UE motor deficits are responsive to intensive robot-assisted therapy of 45 or 60 minutes per session duration. The replacement of part of the robotic training with nonrobotic tasks did not reduce treatment effect and may benefit stroke-affected hand use and motor task performance.

 

via Robot-Assisted Arm Training in Chronic Stroke: Addition of Transition-to-Task Practice. – PubMed – NCBI

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