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Bolek, Jeffrey E.

doi:10.1023/a:1023810608949

Cited by 29 publications

(4 citation statements)

References 5 publications

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“…It may be that gait training with biofeedback, initiated at an early age, would be most effective in developing and learning improved SMC. With direct biofeedback, children with CP are able to alter muscle activations during gait (Bolek, 2003; Dursun et al, 2004). In combination with our results, these studies highlight the potential adaptability of gait in children with CP.…”

Section: Discussionmentioning

confidence: 99%

Muscle Synergies in Response to Biofeedback-Driven Gait Adaptations in Children With Cerebral Palsy

et al. 2019

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BackgroundChildren with cerebral palsy (CP) often show impaired selective motor control (SMC) that induces limitations in motor function. Children with CP can improve aspects of pathological gait in an immediate response to visual biofeedback. It is not known, however, how these gait adaptations are achieved at the neural level, nor do we know the extent of SMC plasticity in CP.AimInvestigate the underlying SMC and changes that may occur when gait is adapted with biofeedback.MethodsTwenty-three ambulatory children with CP and related (hereditary) forms of spastic paresis (Aged: 10.4 ± 3.1, 6–16 years, M: 16/F: 9) were challenged with real-time biofeedback to improve step length, knee extension, and ankle power while walking on an instrumented treadmill in a virtual reality environment. The electromyograms of eight superficial muscles of the leg were analyzed and synergies were further decomposed using non-negative matrix factorization (NNMF) using 1 to 5 synergies, to quantify SMC. Total variance accounted for (tVAF) was used as a measure of synergy complexity. An imposed four synergy solution was investigated further to compare similarity in weightings and timing patterns of matched paired synergies between baseline and biofeedback trials.ResultsDespite changes in walking pattern, changes in synergies were limited. The number of synergies required to explain at least 90% of muscle activation increased significantly, however, the change in measures of tVAF1 from baseline (0.75 ± 0.08) were less than ±2% between trials. In addition, within-subject similarity of synergies to baseline walking was high (>0.8) across all biofeedback trials.ConclusionThese results suggest that while gait may be adapted in an immediate response, SMC as quantified by synergy analysis is perhaps more rigidly impaired in CP. Subtle changes in synergies were identified; however, it is questionable if these are clinically meaningful at the level of an individual. Adaptations may be limited in the short term, and further investigation is essential to establish if long term training using biofeedback leads to adapted SMC.

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Section: Discussionmentioning

confidence: 99%

Muscle Synergies in Response to Biofeedback-Driven Gait Adaptations in Children With Cerebral Palsy

et al. 2019

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“…Early reports suggest that EMG biofeedback of triceps surae muscle activity during gait may be efficacious in improving gait symmetry in children with CP [31]. A preliminary study showed that two children diagnosed with CP who used EMG biofeedback demonstrated improved toe clearance during the swing phase of gait and a newly learned ability to recruit and relax the anterior tibialis [32]. Dursun and colleagues [33] also evaluated the effectiveness of biofeedback treatment on gait function in children with CP.…”

Section: Physiological Biofeedbackmentioning

confidence: 99%

Biofeedback in rehabilitation

Giggins

Persson

Caulfield

2013

Journal of NeuroEngineering and Rehabilitation

486

324

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This paper reviews the literature relating to the biofeedback used in physical rehabilitation. The biofeedback methods used in rehabilitation are based on biomechanical measurements and measurements of the physiological systems of the body. The physiological systems of the body which can be measured to provide biofeedback are the neuromuscular system, the respiratory system and the cardiovascular system. Neuromuscular biofeedback methods include electromyography (EMG) biofeedback and real-time ultrasound imaging (RTUS) biofeedback. EMG biofeedback is the most widely investigated method of biofeedback and appears to be effective in the treatment of many musculoskeletal conditions and in post cardiovascular accident (CVA) rehabilitation. RTUS biofeedback has been demonstrated effective in the treatment of low back pain (LBP) and pelvic floor muscle dysfunction. Cardiovascular biofeedback methods have been shown to be effective in the treatment of a number of health conditions such as hypertension, heart failure, asthma, fibromyalgia and even psychological disorders however a systematic review in this field has yet to be conducted. Similarly, the number of large scale studies examining the use of respiratory biofeedback in rehabilitation is limited. Measurements of movement, postural control and force output can be made using a number of different devices and used to deliver biomechanical biofeedback. Inertial based sensing biofeedback is the most widely researched biomechanical biofeedback method, with a number of studies showing it to be effective in improving measures of balance in a number of populations. Other types of biomechanical biofeedback include force plate systems, electrogoniometry, pressure biofeedback and camera based systems however the evidence for these is limited. Biofeedback is generally delivered using visual displays, acoustic or haptic signals, however more recently virtual reality (VR) or exergaming technology have been used as biofeedback signals. VR and exergaming technology have been primarily investigated in post-CVA rehabilitation, however, more recent work has shown this type of biofeedback to be effective in improving exercise technique in musculoskeletal populations. While a number of studies in this area have been conducted, further large scale studies and reviews investigating different biofeedback applications in different clinical populations are required.

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“…Although EMG biofeedback techniques appear promising, there is limited and contradictory evidence about their effectiveness in musculoskeletal and neurological rehabilitation [ 24 , 25 , 26 ]. However, studies that tried to assess the effectiveness of EMG biofeedback did not use this technique in combination with robotic rehabilitation platforms [ 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 ].…”

Section: Introductionmentioning

confidence: 99%

Interaction with a Hand Rehabilitation Exoskeleton in EMG-Driven Bilateral Therapy: Influence of Visual Biofeedback on the Users’ Performance

Cisnal

Gordaliza

Pérez-Turiel

et al. 2023

Sensors

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The effectiveness of EMG biofeedback with neurorehabilitation robotic platforms has not been previously addressed. The present work evaluates the influence of an EMG-based visual biofeedback on the user performance when performing EMG-driven bilateral exercises with a robotic hand exoskeleton. Eighteen healthy subjects were asked to perform 1-min randomly generated sequences of hand gestures (rest, open and close) in four different conditions resulting from the combination of using or not (1) EMG-based visual biofeedback and (2) kinesthetic feedback from the exoskeleton movement. The user performance in each test was measured by computing similarity between the target gestures and the recognized user gestures using the L2 distance. Statistically significant differences in the subject performance were found in the type of provided feedback (p-value 0.0124). Pairwise comparisons showed that the L2 distance was statistically significantly lower when only EMG-based visual feedback was present (2.89 ± 0.71) than with the presence of the kinesthetic feedback alone (3.43 ± 0.75, p-value = 0.0412) or the combination of both (3.39 ± 0.70, p-value = 0.0497). Hence, EMG-based visual feedback enables subjects to increase their control over the movement of the robotic platform by assessing their muscle activation in real time. This type of feedback could benefit patients in learning more quickly how to activate robot functions, increasing their motivation towards rehabilitation.

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Untitled

Cited by 29 publications

References 5 publications

Muscle Synergies in Response to Biofeedback-Driven Gait Adaptations in Children With Cerebral Palsy

Muscle Synergies in Response to Biofeedback-Driven Gait Adaptations in Children With Cerebral Palsy

Biofeedback in rehabilitation

Interaction with a Hand Rehabilitation Exoskeleton in EMG-Driven Bilateral Therapy: Influence of Visual Biofeedback on the Users’ Performance

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