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Background: It has not been established how electromyographic (EMG) data of masticatory muscles can estimate bite force (BF) during daily activities at home, such as eating and bruxism, utilising the EMG-BF correlation.
Objective: This study aimed to investigate the relationship between actual BF and BF estimated using corresponding EMG data and additional information on BF and EMG measured on a separate day.
Methods: Participants were 16 volunteers. The unilateral masseteric EMG was recorded during clenching tasks at 10 levels of force up to maximum voluntary clenching (MVC) twice on separate days (Day 1, Day 2). BF was simultaneously measured using a pressure-sensitive occlusal film. The regression equation between the BF and EMG amplitude was calculated on Day 1. Estimated BF on Day 2 was calculated using information on the EMG amplitude on Day 2 (EMG-amp), Day 1 BF at the MVC, and Day 1 regression equation.
Results: Actual value of BF showed a small correlation coefficient with EMG-amp, whereas strong correlations were observed with the estimated values additionally using information of Day 1 BF at the MVC. The estimated BF additionally using information of Day 1 regression equation adjusted by the ratio of EMG at the MVC on Day 1 to that of Day 2 showed the smallest error, indicating the power to estimate BF using corresponding EMG data became further improved.
Conclusions: The obtained findings suggest the possibility of the clinical method estimating BF using corresponding EMG data with the additional information of EMG and BF on a separate day.
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http://dx.doi.org/10.1111/joor.70055 | DOI Listing |
ACS Sens
September 2025
State Key Laboratory of Advanced Fiber Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China.
High-fidelity biosignal monitoring is essential for daily health tracking and the diagnosis of chronic diseases. However, developing bioelectrodes capable of withstanding repeated use and mechanical deformation on wet tissue surfaces remains a significant challenge. Here, we present a robust and ultrathin bioelectrode (RUB), featuring a mechanically heterogeneous architecture and a thickness of ∼3 μm.
View Article and Find Full Text PDFBiosens Bioelectron
September 2025
UCD Centre for Biomedical Engineering, University College Dublin, Belfield, Dublin, 4, Ireland; School of Mechanical & Materials Engineering, University College Dublin, Belfield, Dublin, 4, Ireland. Electronic address:
Surface electromyography (sEMG) is the measurement of the electrical activity of muscle and is extensively used in fundamental research and across many applications in health and sport. Conventional surface electrode technology can suffer from poor signal quality, particularly when used outside the laboratory, requires careful skin preparation prior to electrode application, and can be challenging when used for long-term recording. These limitations have challenged the translation of sEMG to widespread clinical application.
View Article and Find Full Text PDFIEEE Trans Cybern
September 2025
Sleep is essential for maintaining human health and quality of life. Analyzing physiological signals during sleep is critical in assessing sleep quality and diagnosing sleep disorders. However, manual diagnoses by clinicians are time-intensive and subjective.
View Article and Find Full Text PDFJ Oral Rehabil
September 2025
Center for Advanced Oral Medicine, Hokkaido University Hospital, Sapporo, Japan.
Background: It has not been established how electromyographic (EMG) data of masticatory muscles can estimate bite force (BF) during daily activities at home, such as eating and bruxism, utilising the EMG-BF correlation.
Objective: This study aimed to investigate the relationship between actual BF and BF estimated using corresponding EMG data and additional information on BF and EMG measured on a separate day.
Methods: Participants were 16 volunteers.
Mov Disord
September 2025
Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.
Background: The hallmark feature of tremor is rhythmicity, which can be quantified using power spectral density (PSD) analysis. However, tremor exhibits considerable variability, ranging from highly regular to more irregular patterns. Similarly, rhythmicity in myoclonus varies, but it typically manifests as arrhythmic jerks.
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