A novel hybrid machine learning classification for the detection of bruxism patients using physiological signals
Featured Application 1. The hybrid machine learning (HML) classifier can easily classify the
subjects (healthy and bruxism), sleep stages (w and REM), and both with high accuracy. 2 …
subjects (healthy and bruxism), sleep stages (w and REM), and both with high accuracy. 2 …
Sleep bruxism detection using decision tree method by the combination of C4-P4 and C4-A1 channels of scalp EEG
Lack of sleep causes many sleep disorders such as nocturnal frontal lobe epilepsy,
narcolepsy, bruxism, sleep apnea, insomnia, periodic limb movement disorder, and rapid …
narcolepsy, bruxism, sleep apnea, insomnia, periodic limb movement disorder, and rapid …
Use of electromyographic and electrocardiographic signals to detect sleep bruxism episodes in a natural environment
Diagnosis of bruxism is difficult since not all contractions of masticatory muscles during
sleeping are bruxism episodes. In this paper, we propose the use of both EMG and ECG …
sleeping are bruxism episodes. In this paper, we propose the use of both EMG and ECG …
Prognosis of sleep bruxism using power spectral density approach applied on EEG signal of both EMG1-EMG2 and ECG1-ECG2 channels
Bruxism is a sleep syndrome, in which individual involuntarily grinding and clenching the
teeth. If sleep does not complete properly, then it generates many disorders such as …
teeth. If sleep does not complete properly, then it generates many disorders such as …
Short time frequency analysis of theta activity for the diagnosis of bruxism on EEG sleep record
Sleep is the important part of the living organism. If the normal humans do not sleep properly
so its generate many diseases. Bruxism is a neurological or sleep syndrome. Its individuals …
so its generate many diseases. Bruxism is a neurological or sleep syndrome. Its individuals …
Detection, treatment planning, and genetic predisposition of bruxism: a systematic mapping process and network visualization technique
Background: Lack of sleep generates many disorders and bruxism is one of them. It has
affected almost 31% of the world population. Aim: The purpose of this paper is to determine …
affected almost 31% of the world population. Aim: The purpose of this paper is to determine …
Portable and wearable electromyographic devices for the assessment of sleep bruxism and awake bruxism: A literature review
T Yamaguchi, S Mikami, M Maeda, T Saito… - CRANIO®, 2023 - Taylor & Francis
Objective The current state of portable/wearable electromyographic (EMG) devices for
assessment of bruxism was reviewed. Methods A search of full-text articles relevant to …
assessment of bruxism was reviewed. Methods A search of full-text articles relevant to …
An automatic sleep disorder detection based on EEG cross-frequency coupling and random forest model
Objective. Sleep disorders are medical disorders of a subject's sleep architecture and based
on their severity, they can interfere with mental, emotional and physical functioning. The …
on their severity, they can interfere with mental, emotional and physical functioning. The …
Support vector machine and simple recurrent network based automatic sleep stage classification of fuzzy kernel
Recently, sleep disorder is taken as a serious issue in people living. Normally people
cerebrum passes through variety of static physiological steps or changes for the duration of …
cerebrum passes through variety of static physiological steps or changes for the duration of …
Automated identification of sleep disorders using wavelet-based features extracted from electrooculogram and electromyogram signals
M Sharma, J Darji, M Thakrar, UR Acharya - Computers in biology and …, 2022 - Elsevier
Sleep is imperative for a healthy life as it rejuvenates memory, cognitive performance, cell
repair and eliminates waste from the muscles. Sleep-related disorders such as insomnia …
repair and eliminates waste from the muscles. Sleep-related disorders such as insomnia …