Bibliographic searches identified 14 controlled and uncontrolled outcome evaluations of biofeedback-based treatments for temporomandibular disorders published since 1978. This literature includes two randomized controlled trials (RCTs) of each of three types of biofeedback treatment: (1) surface electromyographic (SEMG) training of the masticatory muscles, (2) SEMG training combined with adjunctive cognitive-behavioral therapy (CBT) techniques, and (3) biofeedback-assisted relaxation training (BART). A detailed review of these six RCTs, supplemented with information from non-RCT findings, was conducted to determine the extent to which each type of intervention met treatment efficacy criteria promulgated by the Association for Applied Psychophysiology and Biofeedback (AAPB). We conclude that SEMG training with adjunctive CBT is an efficacious treatment for temporomandibular disorders and that both SEMG training as the sole intervention and BART are probably efficacious treatments. We discuss guidelines for designing and reporting research in this area and suggest possible directions for future studies.
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http://dx.doi.org/10.1007/s10484-005-8420-5 | DOI Listing |
Gait Posture
December 2024
Engineering Research Center of the Ministry of Education for Intelligent Rehabilitation Equipment and Detection Technologies, Hebei University of Technology, Tianjin 300401, PR China; Hebei Key Laboratory of Robot Sensing and Human-robot Interaction, Hebei University of Technology, Tianjin 300401, PR China; School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, PR China. Electronic address:
Background: Gait feature recognition is crucial to improve the efficiency and coordination of exoskeleton assistance. The recognition methods based on surface electromyographic (sEMG) signals are popular. However, the recognition accuracy of these methods is poor due to ignoring the correlation of the time series of sEMG signals.
View Article and Find Full Text PDFAnn Agric Environ Med
December 2024
Department of Rehabilitation, Medical University of Warsaw, Warsaw, Poland.
Introduction And Objective: Surface electromyography (sEMG) measurements are a valid method for sublesional muscle activity following spinal cord injury (SCI). In the literature there are few reports evaluating the effect of robotic assisted gait training (RAGT) on the sEMG properties change in SCI patients. The aim of this study was to evaluate the influence of RAGT on observed change of sEMG, and in 64 incomplete SCI patients in the sub-acute stage in relation to functional scales.
View Article and Find Full Text PDFSci Rep
December 2024
School of Smart Health, Chongqing Polytechnic University of Electronic Technology, Chongqing, 401331, China.
In the field of rehabilitation, although deep learning have been widely used in multitype gesture recognition via surface electromyography (sEMG), their higher algorithmic complexity often leads to low computationally inefficient, which compromise their practicality. To achieve more efficient multitype recognition, We propose the Residual-Inception-Efficient (RIE) model, which integrates Inception and efficient channel attention (ECA). The Inception, which is a multiscale fusion convolutional module, is adopted to enhance the ability to extract sEMG features.
View Article and Find Full Text PDFJ Electromyogr Kinesiol
December 2024
School of Information Science and Technology, Dalian Maritime University, Linghai Road 1, Dalian, Liaoning Province 116026, China. Electronic address:
This study proposed a U-Net based partial convolutional time-domain model for a real-time high-density surface electromyography (HD-sEMG) decomposition. The model combines U-Net and a separation block containing partial convolution, aiming to efficiently identify motor units (MUs) without preprocessing. The proposed U-Net based network was trained by the HD-sEMG signals with innervation pulse trains (IPTs) labels, and the results are compared between different step sizes, noises, and model structures under the sliding time window with 120 sampling points.
View Article and Find Full Text PDFFront Rehabil Sci
December 2024
Sri Padmavathi Medical College for Women, Tirupati, India.
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