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[ARTICLE] Upper Extremity Function Assessment Using a Glove Orthosis and Virtual Reality System – Full Text
Hand motor control deficits following stroke can diminish the ability of patients to participate in daily activities. This study investigated the criterion validity of upper extremity (UE) performance measures automatically derived from sensor data during manual practice of simulated instrumental activities of daily living (IADLs) within a virtual environment. A commercial glove orthosis was specially instrumented with motion tracking sensors to enable patients to interact, through functional UE movements, with a computer-generated virtual world using the SaeboVR software system. Fifteen stroke patients completed four virtual IADL practice sessions, as well as a battery of gold-standard assessments of UE motor and hand function. Statistical analysis using the nonparametric Spearman rank correlation reveals high and significant correlation between virtual world-derived measures and the gold-standard assessments. The results provide evidence that performance measures generated during manual interactions with a virtual environment can provide a valid indicator of UE motor status.
Virtual world-based games, when combined with human motion sensing, can enable a neurorehabilitation patient to engage in realistic occupations that involve repetitive practice of functional tasks (Adams et al., 2018). An important component of such a system is the ability to automatically track patient movements and use those data to produce indices related to movement quality (Adams et al., 2015). Before these technology-derived measures can be considered relevant to clinical outcomes, criterion validity must be established. If validated, measures of virtual task performance may reasonably be interpreted as reflective of real-world functional status.
The objective of the study described in this article was to investigate the criterion validity of upper extremity (UE) performance measures automatically derived from sensor data collected during practice of simulated instrumental activities of daily living (IADLs) in a virtual environment. A commercially available SaeboGlove orthosis (SaeboGlove, 2018) was specially instrumented to enable tracking of finger and thumb movements. This instrumented glove was employed with an enhanced version of the Kinect sensor-based SaeboVR software system (SaeboVR, 2018) to enable employment of the hand, elbow, and shoulder in functional interactions with a virtual world. Performance measures were automatically generated during patient use through a combination of arm tracking data from the Kinect and the glove’s finger and thumb sensors. The primary investigational objective was to determine whether performance indices produced by this system for practice of virtual IADLs are valid indicators of a stroke patient’s UE motor status.
Previous investigations into combining hand tracking with video games to animate UE therapy have produced evidence for the efficacy of such interventions. A recent study compared a 15-session hand therapy intervention using a smart glove system and video games with a usual care regimen (Jung et al., 2017). Stroke patients using the smart glove system realized greater gains in Wolf Motor Function Test (WMFT) score compared with dosage-balanced conventional therapy. Another study investigating a similar glove-based device found significantly greater improvements in Fugl-Meyer and Box and Blocks test results for stroke patients who performed 15 sessions that included the technology-aided therapy compared with subjects receiving traditional therapy only (Carmeli, Peleg, Bartur, Elbo, & Vatine, 2011). An instrumented glove has also been used to support video game therapy that incorporates gripping-like movements and thumb-finger opposition (Chan et al., 2014).
Past research into the use of human motion tracking (sometimes referred to as motion capture) technologies for assessment of UE function has produced encouraging results. One group of researchers compared naturalistic point-to-point reaching movements with standardized reaching movements embedded in a virtual reality system, and established concurrent validity between the two (Schaefer & Hengge, 2016). An investigation involving a device that incorporates handgrip strength and pinch force measurement into virtual reality exercises provided support for system use as an objective evaluation of hand function, and for the potential of replacing conventional goniometry and dynamometry (Nica, Brailescu, & Scarlet, 2013). In another study, researchers employed a Kinect sensor in a software system that attempts to emulate a subset of the Fugl-Meyer Upper Extremity (FMUE) assessment (Kim, Cho, Baek, Bang, & Paik, 2016). Pearson correlation analysis between the Kinect-derived scores and traditionally administered FMUE test results for 41 hemiparetic stroke patients revealed a high correlation. Previous research involving the SaeboVR system established a moderate and statistically significant correlation between virtual IADL performance scores and the WMFT (Adams et al., 2015). Due to limitations of the Kinect optical tracking system, this previous work involving the SaeboVR system did not include tracking of grasp-release manual interactions with virtual objects (Adams et al., 2018). The present research addresses this limitation by fusing data from the Kinect sensor with data from finger- and wrist-mounted sensors on the SaeboGlove orthosis to reconstruct the kinematic pose of the patient’s UE.
The use of an assistive glove orthosis in the present work fills an important clinical need. Inability to bring the hand and wrist into a neutral position due to weakness and/or lack of finger extension can prevent participation in occupation-oriented functional practice (Lang, DeJong, & Beebe, 2009). A common technique to enable stroke patients to achieve a functional hand position (and thus participate in rehabilitation) is a dynamic splint that supports finger and/or wrist extension. When larger forces are necessary (e.g., to overcome abnormal muscle tone), an outrigger-type splint may be employed. For patients with no more than mild hypertonicity, a lower-profile device such as the SaeboGlove orthosis (SaeboGlove, 2018) can be used. Employment of an assistive glove orthosis in the context of virtual IADLs practice thus addresses some of the leading causes of hand motor control deficits following stroke and their adverse impact on ability to participate in daily activities (Kamper, Fischer, Cruz, & Rymer, 2006; Ng, Tsang, Kwong, Tse, & Wong, 2011).
Candidates were recruited from a population of stroke patients receiving in-patient rehabilitation care, outpatient rehabilitation, or who had been previously discharged from rehabilitative care at the UVA Encompass Health Rehabilitation Hospital (Charlottesville, VA, USA). Table 1 includes the study characteristics. Of 17 patients enrolled in the study, 15 completed the protocol. One subject dropped out due to unrelated illness. A second subject was disenrolled due to an inability to adequately express an understanding of consent during re-verification at the beginning of the first post-consent study session.
|Age, years, median (range)||67 (25-83)|
|Time since stroke onset in months, median (range)||12 (1-72)|
|Sex, M/F, n (%)||10 (59)/7 (41)|
|Race category, Black/White, n (%)||3 (18)/14 (82)|
|Ethnic category, Hispanic/non-Hispanic, n (%)||0 (0)/17 (100)|
|Side of hemiplegia, L/R, n (%)||10 (59)/7 (41)|
|Affected side dominance, dominant/nondominant, n (%)||9 (53)/8 (47)|
All study activities were conducted under the auspices of the University of Virginia Institutional Review Board for Health Sciences Research (IRB-HSR). All study sessions took place in a private room within the UVA Encompass Health outpatient clinic between October 20, 2017, and February 9, 2018. Licensed Occupational Therapists trained in study procedures and registered with the IRB-HSR were responsible for all patient contact, recruitment, consent, and protocol administration.
Verification of inclusion/exclusion criteria was through a three-step process including an initial medical record review prior to recruitment, verbal confirmation prior to administration of consent, and an evaluation screen conducted by a study therapist following consent. Inclusion criteria included history of stroke with hemiplegia, ongoing stroke-related hand impairment, sufficient active finger flexion at the metacarpal phalangeal joint in at least one finger to be detected by visual observation by a study therapist, antigravity strength at the elbow to at least 45° of active flexion, antigravity shoulder strength to at least 30° each in active flexion and abduction/adduction, and 15° in active shoulder rotation from an upright seated position. Participants had visual acuity with corrective lenses of 20/50 or better and were able to understand and follow verbal directions. The study excluded patients with visual field deficit in either eye that would impair ability to view the computer monitor and/or with hemispatial neglect that would impair an individual’s ability to process and perceive visual stimuli. The study also excluded individuals with motor limb apraxia, significant muscle spasticity, or contractures of the muscles, joints, tendons, ligaments, or skin that would restrict normal UE movement.
A commercial SaeboGlove orthosis was fitted with wrist and finger motion sensors to permit tracking of finger joint angles during grasp-release interactions with a virtual environment. The instrumented glove orthosis is shown in Figure 1. The sensors were attached to the existing tensioner band hooks on the dorsal side of each glove finger. An electronics enclosure mounted to the palmar side of the SaeboGlove’s plastic wrist splint processes the sensor data and transmits information to a personal computer (PC) that hosts the modified SaeboVR software. Data from both the SaeboGlove-integrated sensors and from a Kinect sensor were used by a custom motion capture algorithm, which employs a human UE kinematics model to produce real-time estimates of arm, wrist, and finger joint angles.
[Abstract] A Review on Surface Electromyography-Controlled Hand Robotic Devices Used for Rehabilitation and Assistance in Activities of Daily Living
Spinal cord injuries, traumas, natural aging, and strokes are the main causes of arm impairment or even a chronic disability for an increasing part of the population. Therefore, robotic devices can be essential tools to help individuals afflicted with hand deficit with the activities of daily living in addition to the possibility of restoring hand functions by rehabilitation. Because the surface electromyography (sEMG) control paradigm has recently emerged as an interesting intention control method in devices applied to rehabilitation, the concentration in this study has been devoted to sEMG-controlled hand robotic devices, including gloves and exoskeletons that are used for rehabilitation and for assistance in daily activities.
Materials and Methods
A brief description is given to the previous reviews and studies that have surveyed the robotic devices used for rehabilitation; a comparison is conducted among these studies with respect to the targeted part of the body and the device’s control method. Important issues about controlling by sEMG signal are accentuated, and a review of sEMG-controlled hand robotic devices is presented with an abbreviated description for each endeavor. Some criteria related to sEMG control are specifically emphasized, for instance, the muscles used for control, the number of sEMG channels, and the type of sEMG sensor used.
It is noted that most of the sEMG-based controls for the devices included in this study have used the nonpattern recognition scheme due to the weak sEMG signals and abnormal pattern of muscle activation for stroke patients. In addition to sEMG-based control, additional control paradigms have been used in many of the listed robotic devices to increase the efficacy of the system; this cooperation is required because of the difficulty in dealing with the sEMG signals of stroke patients. Most of the listed studies have conducted the experiments on a healthy subject to evaluate the efficacy of the systems, whereas the studies that have recruited stroke patients for system assessment were predominately using additional control schemes.
This article highlights the important issues about the sEMG control method and accentuates the weaknesses associated with this type of control to assist researchers in overcoming problems that impede sEMG-controlled robotic devices to be feasible and practical tools for people afflicted with hand impairment.
[Abstract] Robotic-assisted therapy with bilateral practice improves task and motor performance in the upper extremities of chronic stroke patients: A randomised controlled trial.
Task-specific repetitive training, a usual care in occupational therapy practice, and robotic-aided rehabilitation with bilateral practice are used to improve upper limb motor and task performance. The difference in effects of two strategies requires exploration. This study compared the impact of robotic-assisted therapy with bilateral practice (RTBP) and usual task-specific training facilitated by therapists on task and motor performance for stroke survivors.
Forty-three community-dwelling stroke survivors (20 males; 23 females; 53.3 ± 13.1 years; post-stroke duration 14.2 ± 10.9 months) were randomised into RTBP and usual care. All participants received a 10-minute per-protocol sensorimotor stimulation session prior to interventions as part of usual care. Primary outcome was different in the amount of use (AOU) and quality of movement (QOM) on the Motor Activity Log (MAL) scale at endpoint. Secondary outcomes were AOU and QOM scores at follow-up, and pre-post and follow-up score differences on the Fugl-Meyer Assessment (FMA) and surface electromyography (sEMG). Friedman and Mann-Whitney U tests were used to calculate difference.
There were no baseline differences between groups. Both conditions demonstrated significant within-group improvements in AOU-MAL and FMA scores following treatment (P < 0.05) and improvements in FMA scores at follow-up (P < 0.05). The training-induced improvement in AOU (30.0%) following treatment was greater than the minimal detectable change (16.8%) in the RTBP group. RTBP demonstrated better outcomes in FMA wrist score (P = 0.003) and sEMG of wrist extensor (P = 0.043) following treatment and in AOU (P < 0.001), FMA total score (P = 0.006), FMA wrist score (P < 0.001) and sEMG of wrist extensor (P = 0.017) at follow-up compared to the control group. Control group boost more beneficial effects on FMA hand score (P = 0.049) following treatment.
RTBP demonstrated superior upper limb motor and task performance outcomes compared to therapists-facilitated task training when both were preceded by a 10-minute sensorimotor stimulation session.
[Abstract + References] Effect of Virtual Reality Rehabilitation Program with RAPAEL Smart Glove on Stroke Patient’s Upper Extremity Functions and Activities of Daily Living
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.
- 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
- 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.
- 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
- 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
- Asher IE(1996). Occupational therapy assessment tools: An annotated index. 2nd ed, Bethesda, MD: American Occupational Therapy Association, pp.310-315.
- 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
- 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.
- 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
- 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
- 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
- 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.
- 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.
- 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.
- 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.
- Kim JH, Kim IS, Han TR(2007). New scoring system for Jebsen hand function test. Ann Rehabil Med, 31(6), 623-629.
- 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
- 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
- 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
- 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
- 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.
- Neofect(2016). RAPAEL smart solution manual. Neofect. Korea.
- 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.
- 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
- 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
- Sears ED, Chung KC(2010). Validity and responsiveness of the Jebsen-Taylor hand function test. J Hand Surg Am, 35(1), 30-37.
- 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
- 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
- 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.
- 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
[Abstract] Commercial video games in the rehabilitation of patients with sub-acute stroke: a pilot study
Stroke generates dependence on the patients due to the various impairments associated. The use of low-cost technologies for neurological rehabilitation may be beneficial for the treatment of these patients.
To determine whether combined treatment using a semi-immersive virtual reality protocol to an interdisciplinary rehabilitation approach, improve balance and postural control, functional independence, quality of life, motivation, self-esteem and adherence to intervention in stroke patients in subacute stage.
PATIENTS AND METHODS:
A longitudinal prospective study with pre and post-intervention evaluation was carried out. Fourteen were recruited at La Fuenfria Hospital (Spain) and completed the intervention. Experimental intervention was performed during eight weeks in combination with conventional treatment of physiotherapy and occupational therapy. Each session was increased in time and intensity, using commercial video games linked to Xbox 360° videoconsole and Kinect sensor.
There were statistical significant improvements in modified Rankin scale (p = 0.04), baropodometry (load distribution, p = 0.03; support surface, p = 0.01), Barthel Index (p = 0.01), EQ-5D Questionnaire (p = 0.01), motivation (p = 0.02), self-esteem (p = 0.01) and adherence to the intervention (p = 0.02).
An interdisciplinary rehabilitation approach supplemented with semi-immersive virtual reality seems to be useful for improving balance and postural control, functional independence in basic activities of daily living, quality of life, as well as motivation and self-esteem, with excellent adherence. This intervention modality could be adopted as a therapeutic tool in neurological rehabilitation of stroke patients in subacute stage.
[Abstract] The wearable hand robot: supporting impaired hand function in activities of daily living and rehabilitation
New developments, based on the concept of wearable soft-robotic devices, make it possible to support impaired hand function during the performance of daily activities and intensive task-specific training. The ironHand and HandinMind systems are examples of such novel wearable soft-robotic systems that have been developed in the ironHand and HandinMind projects. Both systems are developed to provide grip support during a wide range of daily activities. The ironHand system consists of a 3-finger wearable soft-robotic glove, tailored to older adults with a variety of physical age-related hand function limitations. The HandinMind system consists of a 5-finger wearable soft-robotic glove, dedicated towards application in stroke. In both cases, the wearable soft-robotic system could be connected to a computer with custom software to train specific aspects of hand function in a motivating game-like environment with multiple levels of difficulty. By adding the game environment, an assistive device is transformed into a dedicated training device.
[Abstract] Electromechanical and robot‐assisted arm training for improving activities of daily living, arm function, and arm muscle strength after stroke
Electromechanical and robot‐assisted arm training devices are used in rehabilitation, and may help to improve arm function after stroke.
To assess the effectiveness of electromechanical and robot‐assisted arm training for improving activities of daily living, arm function, and arm muscle strength in people after stroke. We also assessed the acceptability and safety of the therapy.
We searched the Cochrane Stroke Group’s Trials Register (last searched January 2018), the Cochrane Central Register of Controlled Trials (CENTRAL) (the Cochrane Library 2018, Issue 1), MEDLINE (1950 to January 2018), Embase (1980 to January 2018), CINAHL (1982 to January 2018), AMED (1985 to January 2018), SPORTDiscus (1949 to January 2018), PEDro (searched February 2018), Compendex (1972 to January 2018), and Inspec (1969 to January 2018). We also handsearched relevant conference proceedings, searched trials and research registers, checked reference lists, and contacted trialists, experts, and researchers in our field, as well as manufacturers of commercial devices.
Randomised controlled trials comparing electromechanical and robot‐assisted arm training for recovery of arm function with other rehabilitation or placebo interventions, or no treatment, for people after stroke.
Data collection and analysis
Two review authors independently selected trials for inclusion, assessed trial quality and risk of bias, used the GRADE approach to assess the quality of the body of evidence, and extracted data. We contacted trialists for additional information. We analysed the results as standardised mean differences (SMDs) for continuous variables and risk differences (RDs) for dichotomous variables.
We included 45 trials (involving 1619 participants) in this update of our review. Electromechanical and robot‐assisted arm training improved activities of daily living scores (SMD 0.31, 95% confidence interval (CI) 0.09 to 0.52, P = 0.0005; I² = 59%; 24 studies, 957 participants, high‐quality evidence), arm function (SMD 0.32, 95% CI 0.18 to 0.46, P < 0.0001, I² = 36%, 41 studies, 1452 participants, high‐quality evidence), and arm muscle strength (SMD 0.46, 95% CI 0.16 to 0.77, P = 0.003, I² = 76%, 23 studies, 826 participants, high‐quality evidence). Electromechanical and robot‐assisted arm training did not increase the risk of participant dropout (RD 0.00, 95% CI ‐0.02 to 0.02, P = 0.93, I² = 0%, 45 studies, 1619 participants, high‐quality evidence), and adverse events were rare.
People who receive electromechanical and robot‐assisted arm training after stroke might improve their activities of daily living, arm function, and arm muscle strength. However, the results must be interpreted with caution although the quality of the evidence was high, because there were variations between the trials in: the intensity, duration, and amount of training; type of treatment; participant characteristics; and measurements used.
Plain language summary
Electromechanical‐assisted training for improving arm function and disability after stroke
To assess the effects of electromechanical and robot‐assisted arm training for improving arm function in people who have had a stroke.
More than two‐thirds of people who have had a stroke have difficulties with reduced arm function, which can restrict a person’s ability to perform everyday activities, reduce productivity, limit social activities, and lead to economic burden. Electromechanical and robot‐assisted arm training uses specialised machines to assist rehabilitation in supporting shoulder, elbow, or hand movements. However, the role of electromechanical and robot‐assisted arm training for improving arm function after stroke is unclear.
We identified 45 trials (involving 1619 participants) up to January 2018 and included them in our review. Twenty‐four different electromechanical devices were described in the trials, which compared electromechanical and robot‐assisted arm training with a variety of other interventions. Participants were between 21 to 80 years of age, the duration of the trials ranged from two to 12 weeks, the size of the trials was between eight and 127 participants, and the primary outcome (activities of daily living: the most important target variable measured) differed between the included trials.
Electromechanical and robot‐assisted arm training improved activities of daily living in people after stroke, and function and muscle strength of the affected arm. As adverse events, such as injuries and pain, were seldom described, these devices can be applied as a rehabilitation tool, but we still do not know when or how often they should be used.
Quality of the evidence
The quality of the evidence was high.
[Abstract + References] A Wearable Hand Neuroprosthesis for Hand Rehabilitation After Stroke: Preliminary Results of the RETRAINER S2 Randomized Controlled Trial – Conference paper
Stroke is the main cause of permanent and complex long-term disability in adults. RETRAINER S2 is a system able to recover and support person’s ability to perform Activities of Daily Living (ADL) in early stage after stroke. The system is based on exercises for hand and wrist performed using Neuro Muscular Electrical Stimulation (NMES). This work describes the preliminary results of a multi-center Randomized Controlled Trial (RCT) aimed at evaluating effectiveness of the system. The preliminary results were calculated on 18 patients who completed the protocol. Data is promising, the RETRANER S2 system seems to be a good tool for stroke rehabilitation. Data confirms also a general good usability of the system.
[Book Chapter] SOFT ROBOTIC GLOVE FOR COMBINED ASSISTANCE AND REHABILITATION DURING ACTIVITIES OF DAILY LIVING – The Encyclopedia of Medical Robotics
The human hand plays an important role in the manipulation and exploration of the environment. Unfortunately, when disease or injury impedes hand function, the consequences are numerous including disrupting quality of life, independence, and financial stability. In this chapter, we present the development of a soft robotic glove designed to support basic hand function. The glove uses soft fluidic actuators programmed to apply assistive forces to support the range of motion of a human hand. More specifically, we present a method of fabrication and characterization of these soft actuators as well as consider an approach for controlling the glove. This analysis concludes with results from preliminary human subjects testing where glove performance was evaluated on a healthy and an impaired subject.