Purpose Surface electromyography (sEMG) is often used for biofeedback during swallowing rehabilitation. However, commercially available sEMG electrodes are not optimized for the head and neck area, have rigid form, and are mostly available in large medical centers. We developed an ultrathin, soft, and flexible sEMG patch, specifically designed to conform to the submental anatomy and which will be ultimately incorporated into a telehealth system. To validate this first-generation sEMG patch, we compared its safety, efficiency, and signal quality in monitoring submental muscle activity with that of widely used conventional sEMG electrodes. Method A randomized crossover design was used to compare the experimental sEMG patch with conventional (snap-on) sEMG electrodes. Participants completed the same experimental protocol with both electrodes in counterbalanced order. Swallow trials included five trials of 5- and 10-ml water. Comparisons were made on (a) signal-related factors: signal-to-noise ratio (SNR), baseline amplitude, normalized mean amplitude, and sEMG burst duration and (b) safety/preclinical factors: safety/adverse effects, efficiency of electrode placement, and satisfaction/comfort. Noninferiority and equivalence tests were used to examine signal-related factors. Paired tests and descriptive statistics were used to examine safety/preclinical factors. Results Forty healthy adults participated (24 women, = 67.5 years). Signal-related factors: SNR of the experimental patch was not inferior to the SNR of the conventional electrodes ( < .0056). Similarly, baseline amplitude obtained with the experimental patch was not inferior to that obtained with conventional electrodes ( < .0001). Finally, normalized amplitude values were equivalent across swallows (5 ml: < .025; 10 ml: < .0012), and sEMG burst duration was also equivalent (5 ml: < .0001; 10 ml: < .0001). Safety/preclinical factors: The experimental patch resulted in fewer mild adverse effects. Participant satisfaction was higher with the experimental patch ( = .0476, = 0.226). Conclusions Our new wearable sEMG patch is equivalent with widely used conventional sEMG electrodes in terms of technical performance. In addition, our patch is safe, and healthy older adults are satisfied with it. With lessons learned from the current COVID-19 pandemic, efforts to develop optimal swallowing telerehabilitation devices are more urgent than ever. Upon further validation, this new technology has the potential to improve rehabilitation and telerehabilitation efforts for patients with dysphagia. Supplemental Material https://doi.org/10.23641/asha.12915509.
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http://dx.doi.org/10.1044/2020_JSLHR-20-00171 | DOI Listing |
J Neuroeng Rehabil
December 2024
School of Information Science and Technology, Fudan University, Shanghai, 200433, China.
For surface electromyography (sEMG) based human-machine interaction systems, accurately recognizing the users' gesture intent is crucial. However, due to the existence of subject-specific components in sEMG signals, subject-specific models may deteriorate when applied to new users. In this study, we hypothesize that in addition to subject-specific components, sEMG signals also contain pattern-specific components, which is independent of individuals and solely related to gesture patterns.
View Article and Find Full Text PDFJ Neurophysiol
January 2025
Center for Neural Basis of Cognition, University of Pittsburgh and Carnegie Mellon University, Pittsburgh, Pennsylvania, United States.
Surface electromyography (sEMG) is useful for studying muscle function and controlling prosthetics, but cross talk from nearby muscles often limits its effectiveness. High-density surface EMG (HD-sEMG) improves spatial resolution, allowing for the isolation of M-waves in the densely packed forearm muscles. This study assessed HD-sEMG for localizing M-waves and evaluated the impact of spatial filters on cross talk reduction.
View Article and Find Full Text PDFSensors (Basel)
December 2024
EXOForce Robotics, Arlington, VA 22209, USA.
Freezing of gait (FOG) is a disabling yet poorly understood paroxysmal gait disorder affecting the vast majority of patients with Parkinson's disease (PD) as they reach advanced stages of the disorder. Falling is one of the most disabling consequences of a FOG episode; it often results in injury and a future fear of falling, leading to diminished social engagement, a reduction in general fitness, loss of independence, and degradation of overall quality of life. Currently, there is no robust or reliable treatment against FOG in PD.
View Article and Find Full Text PDFCureus
November 2024
Department of Respiratory Medicine and Allergology, Showa University School of Medicine, Tokyo, JPN.
Introduction Surface electromyography (sEMG), a widely used noninvasive technique for assessing muscle activity, measures muscle activity during swallowing. However, changes in the activity of each swallowing-related muscle, depending on the materials swallowed, remain unclear. Therefore, we investigated changes in muscle activity in the submandibular region using a seven-channel sEMG when swallowing different materials.
View Article and Find Full Text PDFComput Biol Med
December 2024
School of Electronic and Electrical Engineering, Kyungpook National University, Daegu, South Korea. Electronic address:
This paper introduces the Spatio-Temporal Cross Network (STCNet), a novel deep learning architecture tailored for robust hand gesture recognition in surface electromyography (sEMG) across multiple subjects. We address the challenges associated with the inter-subject variability and environmental factors such as electrode shift and muscle fatigue, which traditionally undermine the robustness of gesture recognition systems. STCNet integrates a convolutional-recurrent architecture with a spatio-temporal block that extracts features over segmented time intervals, enhancing both spatial and temporal analysis.
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