[Possibility of optimizing respiratory response using biofeedback].
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Biofeedback is a technique of increasing importance in the field of rehabilitation. Several studies have been published in which biofeedback was utilized in gait training of stroke patients. A variety of electronic and non-electronic biofeedback approaches have been used. Joint position biofeedback was preferred in this study as it requires concentration only on the joint position. The purpose of this study was to show the effectiveness of Joint Position Biofeedback training in controlling genu recurvatum in adult stroke.< >
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Biofeedback systems have been developing rapidly in recent years as rehabilitation methods for hemiplegic stroke patients. To investigate the value of such systems for the rehabilitation of these patients, we complemented the Useful and Ultimate Rehabilitation System PARKO (UR-System-PARKO) with a biofeedback system that had an A-B-A-B design, to see if together, patients saw more improvement in a shorter timespan in the control of the extensor muscles in their hands. The biofeedback system was tested without therapist participation. We evaluated the effectiveness of each training trial by recording electromyography (EMG) signals for the extensor and flexor digitorum muscles. By comparing the EMG values from each trial, we were able to conclude that the training with the UR-System-PARKO became more effective when the biofeedback system was applied. This also demonstrated that, by using a biofeedback system, it would be possible for stroke hemiplegic patients to conduct highly efficient self-rehabilitation.
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This paper discusses and reviews the use of biofeedback techniques in various gait training applications, focusing particularly on the use of joint position biofeedback. The potential benefits of this approach are illustrated in a controlled case study using applied behavior analysis methodology. A standardized physical therapy regimen was compared with an identical treatment phase which included the addition of joint position feedback. Results suggest that biofeedback techniques are useful as an adjunct to physical therapy with stroke patients.
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Real-time gait biofeedback is a promising rehabilitation strategy for improving biomechanical deficits in walking patterns of post-stroke individuals. Because wearable sensor technologies are creating avenues for novel applications of gait biofeedback, including use in tele-health, there is a need to evaluate the state of the current evidence regarding the effectiveness of biofeedback for post-stroke gait training. The objectives of this review are to: (1) evaluate the current state of biofeedback literature pertaining to post-stroke gait training; and (2) determine future research directions related to gait biofeedback in context of evolving technologies. Our overall goal was to determine whether gait biofeedback is effective at improving stroke gait deficits while also probing why and for whom gait biofeedback may be an efficacious treatment modality. Our literature review showed that the effects of gait biofeedback on post-stroke walking dysfunction are promising but are inconsistent in methodology and therefore results. We summarize sources of methodological heterogeneity in previous literature, such as inconsistencies in feedback target, feedback mode, dosage, practice structure, feedback structure, and patient characteristics. There is a need for larger-sample studies that directly compare different feedback parameters, employ more uniform experimental designs, and evaluate characteristics of potential responders. However, as these uncertainties in existing literature are resolved, the application of gait biofeedback has potential to extend neurorehabilitation clinicians' cues to individuals with post-stroke gait deficits during ambulation in clinical, home, and community settings, thereby increasing the quantity and quality of skilled repetitions during task-oriented stepping training. In addition to identifying gaps in previous research, we posit that future research directions should comprise an amalgam of mechanism-focused and clinical research studies, to develop evidence-informed decision-making guidelines for gait biofeedback strategies that are tailored to individual-specific gait and sensorimotor impairments. Wearable sensor technologies have the potential to transform gait biofeedback and provide greater access and wider array of options for clinicians while lowering rehabilitation costs. Novel sensing technologies will be particularly valuable for telehealth and home-based stepping exercise programs. In summary, gait biofeedback is a promising intervention strategy that can enhance efficacy of post-stroke gait rehabilitation in both clinical and tele-rehabilitation settings and warrants more in-depth research.
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Бұл зерттеужұмысындaКaно моделітурaлы жәнеоғaн қaтыстытолықмәліметберілгенжәнеуниверситетстуденттерінебaғыттaлғaн қолдaнбaлы (кейстік)зерттеужүргізілген.АхметЯссaуи университетініңстуденттеріүшін Кaно моделіқолдaнылғaн, олaрдың жоғaры білімберусaпaсынa қоятынмaңыздытaлaптaры, яғнисaпaлық қaжеттіліктері,олaрдың мaңыздылығытурaлы жәнесaпaлық қaжеттіліктерінеқaтыстыөз университетінқaлaй бaғaлaйтындығытурaлы сұрaқтaр қойылғaн. Осы зерттеудіңмaқсaты АхметЯсaуи университетіндетуризмменеджментіжәнеқaржы бaкaлaвриaт бaғдaрлaмaлaрыныңсaпaсынa қaтыстыстуденттердіңқaжеттіліктерінaнықтaу, студенттердіңқaнaғaттaну, қaнaғaттaнбaу дәрежелерінбелгілеу,білімберусaпaсын aнықтaу мен жетілдіружолдaрын тaлдaу болыптaбылaды. Осы мaқсaтқaжетуүшін, ең aлдыменКaно сaуaлнaмaсы түзіліп,116 студенткеқолдaнылдыжәнебілімберугежәнеоның сaпaсынa қaтыстыстуденттердіңтaлaптaры мен қaжеттіліктерітоптықжұмыстaрaрқылыaнықтaлды. Екіншіден,бұл aнықтaлғaн тaлaптaр мен қaжеттіліктерКaно бaғaлaу кестесіменжіктелді.Осылaйшa, сaпa тaлaптaры төрт сaнaтқa бөлінді:болуытиіс, бір өлшемді,тaртымдыжәнебейтaрaп.Соңындa,қaнaғaттaну мен қaнaғaттaнбaудың мәндеріесептелдіжәнестуденттердіңқaнaғaттaну мен қaнaғaттaнбaу деңгейлерінжоғaрылaту мен төмендетудеосытaлaптaр мен қaжеттіліктердіңрөліaйқын aнықтaлды.Түйінсөздер:сaпa, сaпaлық қaжеттіліктер,білімберусaпaсы, Кaно моделі.
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Objectives Gait training interventions that target paretic propulsion induce improvements in walking speed and function in individuals post-stroke. Previously, we demonstrated that able-bodied individuals increase propulsion unilaterally when provided real-time biofeedback targeting anterior ground reaction forces (AGRF). The purpose of this study was to, for the first time, investigate short-term effects of real-time AGRF gait biofeedback training on post-stroke gait. Methods Nine individuals with post-stroke hemiparesis (6 females, age = 54 ± 12.4 years 39.2 ± 24.4 months post-stroke) completed three 6-minute training bouts on an instrumented treadmill. During training, visual and auditory biofeedback were provided to increase paretic AGRF during terminal stance. Gait biomechanics were evaluated before training, and during retention tests conducted 2, 15, and 30 minutes post-training. Primary dependent variables were paretic and non-paretic peak AGRF; secondary variables included paretic and non-paretic peak trailing limb angle, plantarflexor moment, and step length. In addition to evaluating the effects of biofeedback training on these dependent variables, we compared effects of a 6-minute biofeedback training bout to a non-biofeedback control condition. Results Compared to pre-training, significantly greater paretic peak AGRFs were generated during the 2, 15, and 30-minute retention tests conducted after the 18-minute biofeedback training session. Biofeedback training induced no significant effects on the non-paretic leg. Comparison of a 6-minute biofeedback training bout with a speed-matched control bout without biofeedback demonstrated a main effect for training type, with greater peak AGRF generation during biofeedback. Discussion Our results suggest that AGRF biofeedback may be a feasible and promising gait training strategy to target propulsive deficits in individuals post-stroke.
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Hemiparesis
Stroke
Rowing
Treadmill
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