Recovery of Proprioception in the Upper Extremity by Robotic Mirror Therapy: a Clinical Pilot Study for Proof of Concept

Nam, Hyung Seok; Koh, Sukgyu; Beom, Jaewon; Kim, Yoon Jae; Park, Jang Woo; Koh, Eun Sil; Chung, Sun Gun; Kim, Sung‐Wan

doi:10.3346/jkms.2017.32.10.1568

Cited by 9 publications

(8 citation statements)

References 38 publications

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“…The studies mainly assess the effect of virtual reality (65%; n = 49) [ 8 , 16 , 21 – 23 , 28 – 32 , 37 – 43 , 45 – 48 , 50 – 53 , 57 – 59 , 61 – 65 , 67 , 69 , 72 – 74 , 77 – 80 , 82 , 84 – 89 ] and robotic system (23%; n= 17) [ 7 , 12 , 25 , 26 , 34 , 49 , 54 – 56 , 60 , 66 , 70 , 71 , 75 , 76 , 81 , 83 ] ( Table 8 ). The names of the devices evaluated in the different studies are as follows: Bi-Manu-Track, BioPatRec, Dulex-II, HapticMASTER, Mirror Image Movement Enabler (MIME), Neuromotus, Picdae Robot, Pictogram round (Orange Foundation), TheraMem, Trinus Virtual Reality, Virtual Reality-based Mirror Visual Feedback, VR-Mirror (MedICLab), and YouRehab.…”

Section: Resultsmentioning

confidence: 99%

Do Robotics and Virtual Reality Add Real Progress to Mirror Therapy Rehabilitation? A Scoping Review

Darbois

Guillaud

Pinsault

2018

Rehabilitation Research and Practice

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Background Mirror therapy has been used in rehabilitation for multiple indications since the 1990s. Current evidence supports some of these indications, particularly for cerebrovascular accidents in adults and cerebral palsy in children. Since 2000s, computerized or robotic mirror therapy has been developed and marketed. Objectives To map the extent, nature, and rationale of research activity in robotic or computerized mirror therapy and the type of evidence available for any indication. To investigate the relevance of conducting a systematic review and meta-analysis on these therapies. Method Systematic scoping review. Searches were conducted (up to May 2018) in the Cochrane Library, Google Scholar, IEEE Xplore, Medline, Physiotherapy Evidence Database, and PsycINFO databases. References from identified studies were examined. Results In sum, 75 articles met the inclusion criteria. Most studies were publicly funded (57% of studies; n = 43), without disclosure of conflict of interest (59% of studies; n = 44). The main outcomes assessed were pain, satisfaction on the device, and body function and activity, mainly for stroke and amputees patients and healthy participants. Most design studies were case reports (67% of studies; n = 50), with only 12 randomized controlled trials with 5 comparing standard mirror therapy versus virtual mirror therapy, 5 comparing second-generation mirror therapy versus conventional rehabilitation, and 2 comparing other interventions. Conclusion Much of the research on second-generation mirror therapy is of very low quality. Evidence-based rationale to conduct such studies is missing. It is not relevant to recommend investment by rehabilitation professionals and institutions in such devices.

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Section: Resultsmentioning

confidence: 99%

Do Robotics and Virtual Reality Add Real Progress to Mirror Therapy Rehabilitation? A Scoping Review

Darbois

Guillaud

Pinsault

2018

Rehabilitation Research and Practice

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“…Despite limited clinical uptake for the treatment of post-stroke proprioception, some potentially promising evidence comes from experimental interventions [ 12 ]. These studies, which are limited and only conducted in small samples, have been shown to increase proprioceptive acuity following stroke using a variety of treatment methods [ 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 ]. Many of these studies have utilized alternative treatments such as robotic therapy [ 57 , 59 , 60 , 63 ] including robotic mirror therapy [ 65 ] and assisted movement with enhanced sensation [ 58 ] but have also included more traditional tactile and proprioceptive discrimination training [ 56 ].…”

Section: Discussionmentioning

confidence: 99%

Clinical, Neuroimaging and Robotic Measures Predict Long-Term Proprioceptive Impairments following Stroke

et al. 2023

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Proprioceptive impairments occur in ~50% of stroke survivors, with 20–40% still impaired six months post-stroke. Early identification of those likely to have persistent impairments is key to personalizing rehabilitation strategies and reducing long-term proprioceptive impairments. In this study, clinical, neuroimaging and robotic measures were used to predict proprioceptive impairments at six months post-stroke on a robotic assessment of proprioception. Clinical assessments, neuroimaging, and a robotic arm position matching (APM) task were performed for 133 stroke participants two weeks post-stroke (12.4 ± 8.4 days). The APM task was also performed six months post-stroke (191.2 ± 18.0 days). Robotics allow more precise measurements of proprioception than clinical assessments. Consequently, an overall APM Task Score was used as ground truth to classify proprioceptive impairments at six months post-stroke. Other APM performance parameters from the two-week assessment were used as predictive features. Clinical assessments included the Thumb Localisation Test (TLT), Behavioural Inattention Test (BIT), Functional Independence Measure (FIM) and demographic information (age, sex and affected arm). Logistic regression classifiers were trained to predict proprioceptive impairments at six months post-stroke using data collected two weeks post-stroke. Models containing robotic features, either alone or in conjunction with clinical and neuroimaging features, had a greater area under the curve (AUC) and lower Akaike Information Criterion (AIC) than models which only contained clinical or neuroimaging features. All models performed similarly with regard to accuracy and F1-score (>70% accuracy). Robotic features were also among the most important when all features were combined into a single model. Predicting long-term proprioceptive impairments, using data collected as early as two weeks post-stroke, is feasible. Identifying those at risk of long-term impairments is an important step towards improving proprioceptive rehabilitation after a stroke.

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“…P2 reported limitations on proprioceptive feedback in her phantom limb, notably including her thumb metacarpal phalangeal joint. Additional practice ( 21 ) or enhanced training strategies ( 55 ) could potentially resolve this issue. However, improved feedback mechanisms ( 56 – 59 ) may be necessary for some patients to realize the full potential of improved motor control.…”

Section: Discussionmentioning

confidence: 99%

Surgically Implanted Electrodes Enable Real-Time Finger and Grasp Pattern Recognition for Prosthetic Hands

Vaskov

North

et al. 2020

Preprint

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Currently available prosthetic hands are capable of actuating anywhere from five to 30 degrees of freedom (DOF). However, grasp control of these devices remains unintuitive and cumbersome. To address this issue, we propose directly extracting finger commands from the neuromuscular system via electrodes implanted in residual innervated muscles and regenerative peripheral nerve interfaces (RPNIs). Two persons with transradial amputations had RPNIs created by suturing autologous free muscle grafts to their transected median, ulnar, and dorsal radial sensory nerves. Bipolar electrodes were surgically implanted into their ulnar and median RPNIs and into their residual innervated muscles. The implanted electrodes recorded local electromyography (EMG) with Signal-to-Noise Ratios ranging from 23 to 350 measured across various movements. In a series of single-day experiments, participants used a high speed pattern recognition system to control a virtual prosthetic hand in real-time. Both participants were able to transition between 10 pseudo-randomly cued individual finger and wrist postures in the virtual environment with an average online accuracy of 86.5% and latency of 255 ms. When the set was reduced to five grasp postures, average metrics improved to 97.9% online accuracy and 135 ms latency. Virtual task performance remained stable across untrained static arm positions while supporting the weight of the prosthesis. Participants also used the high speed classifier to switch between robotic prosthetic grips and complete a functional performance assessment. These results demonstrate that pattern recognition systems can use the high-quality EMG afforded by intramuscular electrodes and RPNIs to provide users with fast and accurate grasp control.

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Recovery of Proprioception in the Upper Extremity by Robotic Mirror Therapy: a Clinical Pilot Study for Proof of Concept

Cited by 9 publications

References 38 publications

Do Robotics and Virtual Reality Add Real Progress to Mirror Therapy Rehabilitation? A Scoping Review

Do Robotics and Virtual Reality Add Real Progress to Mirror Therapy Rehabilitation? A Scoping Review

Clinical, Neuroimaging and Robotic Measures Predict Long-Term Proprioceptive Impairments following Stroke

Surgically Implanted Electrodes Enable Real-Time Finger and Grasp Pattern Recognition for Prosthetic Hands

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