Results 101 to 110 of about 2,670,505 (246)
Advancements in Machine Learning for Microrobotics in Biomedicine
Microrobotics is an innovative technology with great potential for noninvasive medical interventions. However, controlling and imaging microrobots pose significant challenges in complex environments and in living organisms. This review explores how machine learning algorithms can address these issues, offering solutions for adaptive motion control and ...
Amar Salehi+6 more
wiley +1 more source
On the Variability of Chaos Indices in Sleep EEG Signals [PDF]
Previous researches revealed the chaotic and nonlinear nature of EEG signal. In this paper we inspected the variability of chaotic indices of the sleep EEG signal such as largest Lyapunov exponent, mutual information, correlation dimension and minimum embedding dimension among different subjects, conditions and sleep stages.
arxiv
The Buckled, Ultrasoft, Crack‐based, Large strain, EpiDermal (BUCKLED) sensor is a flexible, ultrasensitive wearable strain sensor designed to precisely measure subtle skin deformations. By utilizing a buckled structure to enhance compliance integrating crack‐based sensing mechanisms, it improves accuracy in applications like respiratory monitoring ...
Jingoo Lee+9 more
wiley +1 more source
Overview of clinical trial protocols for behavioral insomnia in infants
Objective: to describe the overview of clinical trial protocols for behavioral insomnia in infants. Methods: an analytical study that reviewed protocols registered with the International Clinical Trials Registry Platform between August and September ...
Rayanne Branco dos Santos Lima+2 more
doaj +2 more sources
Multimodal Sleep Stage and Sleep Apnea Classification Using Vision Transformer: A Multitask Explainable Learning Approach [PDF]
Sleep is an essential component of human physiology, contributing significantly to overall health and quality of life. Accurate sleep staging and disorder detection are crucial for assessing sleep quality. Studies in the literature have proposed PSG-based approaches and machine-learning methods utilizing single-modality signals.
arxiv
SLEEPNET: Automated Sleep Staging System via Deep Learning [PDF]
Sleep disorders, such as sleep apnea, parasomnias, and hypersomnia, affect 50-70 million adults in the United States (Hillman et al., 2006). Overnight polysomnography (PSG), including brain monitoring using electroencephalography (EEG), is a central component of the diagnostic evaluation for sleep disorders.
arxiv
Background & Aim: This study aimed at comparing efficacy of cognitive behavioral therapy, Zolpidem 10 mg, and waiting list group on illness perception and sleep efficiency in individuals with chronic insomnia disorder.
Behzad Salmani, Jaafar Hasani
doaj
MSSC-BiMamba: Multimodal Sleep Stage Classification and Early Diagnosis of Sleep Disorders with Bidirectional Mamba [PDF]
Monitoring sleep states is essential for evaluating sleep quality and diagnosing sleep disorders. Traditional manual staging is time-consuming and prone to subjective bias, often resulting in inconsistent outcomes. Here, we developed an automated model for sleep staging and disorder classification to enhance diagnostic accuracy and efficiency ...
arxiv
An unsupervised transfer learning algorithm for sleep monitoring [PDF]
Objective: To develop multisensor-wearable-device sleep monitoring algorithms that are robust to health disruptions affecting sleep patterns. Methods: We develop an unsupervised transfer learning algorithm based on a multivariate hidden Markov model and Fisher's linear discriminant analysis, adaptively adjusting to sleep pattern shift by training on ...
arxiv
Introduction: Patients with cancer may have many complications involving their psychosomatic systems, such as sleep disturbance, depression, and anxiety. Thus, many research studies were conducted to reduce these complications.
Maryam Shahrokhi+6 more
doaj