AIMC Topic: Wakefulness

Clear Filters Showing 1 to 10 of 42 articles

Personalized machine learning models for noninvasive hypoglycemia detection in people with type 1 diabetes using a smartwatch: Insights into feature importance during waking and sleeping times.

PloS one Jun 25, 2025
Hypoglycemia is a major challenge for people with diabetes. Therefore, glycemic monitoring is an important aspect of diabetes management. However, current methods such as finger pricking and continuous glucose monitoring systems (CGMS) are invasive, ...
Female Young Adult Adult Male Humans Machine Learning Algorithms Hypoglycemia Wakefulness Blood Glucose Self-Monitoring Sleep Middle Aged Wearable Electronic Devices Blood Glucose Diabetes Mellitus, Type 1
View on PubMed DOI

Leveraging advanced graph neural networks for the enhanced classification of post anesthesia states to aid surgical procedures.

PloS one Apr 25, 2025
Anesthesia plays a pivotal role in modern surgery by facilitating controlled states of unconsciousness. Precise control is crucial for safe and pain-free surgeries. Monitoring anesthesia depth accurately is essential to guide anesthesiologists, optim...
Humans Neural Networks, Computer Machine Learning Anesthesia Graph Neural Networks Algorithms Brain Wakefulness
View on PubMed DOI

Neural models for detection and classification of brain states and transitions.

Communications biology Apr 11, 2025
Exploring natural or pharmacologically induced brain dynamics, such as sleep, wakefulness, or anesthesia, provides rich functional models for studying brain states. These models allow detailed examination of unique spatiotemporal neural activity patt...
Brain Animals Male Rats Models, Neurological Neural Networks, Computer Wakefulness Algorithms Sleep Cerebral Cortex
View on PubMed DOI

Classification of speech arrests and speech impairments during awake craniotomy: a multi-databases analysis.

International journal of computer assisted radiology and surgery Dec 9, 2024
PURPOSE: Awake craniotomy presents a unique opportunity to map and preserve critical brain functions, particularly speech, during tumor resection. The ability to accurately assess linguistic functions in real-time not only enhances surgical precision...
Aged Adult Brain Neoplasms Male Humans Female Speech Disorders Middle Aged Deep Learning Wakefulness Craniotomy
View on PubMed DOI

Predictive Factors Driving Positive Awake Test in Carotid Endarterectomy Using Machine Learning.

Annals of vascular surgery Nov 22, 2024
BACKGROUND: Positive neurologic awake testing during the carotid cross-clamping may be present in around 8% of patients undergoing carotid endarterectomy (CEA). The present work aimed to assess the accuracy of an artificial intelligence (AI)-powered ...
Endarterectomy, Carotid Risk Assessment Case-Control Studies Intraoperative Neurophysiological Monitoring Treatment Outcome Predictive Value of Tests Wakefulness Carotid Stenosis Neurologic Examination Aged Aged, 80 and over Male Middle Aged Female Reproducibility of Results Risk Factors Humans Machine Learning Decision Support Techniques Retrospective Studies
View on PubMed DOI

Attention-based CNN-BiLSTM for sleep state classification of spatiotemporal wide-field calcium imaging data.

Journal of neuroscience methods Aug 14, 2024
BACKGROUND: Wide-field calcium imaging (WFCI) with genetically encoded calcium indicators allows for spatiotemporal recordings of neuronal activity in mice. When applied to the study of sleep, WFCI data are manually scored into the sleep states of wa...
Attention Neural Networks, Computer Animals Male Image Processing, Computer-Assisted Wakefulness Sleep Sleep Stages Mice Mice, Inbred C57BL Electroencephalography Calcium Brain
View on PubMed DOI

Automatic Sleep Stage Classification Using Nasal Pressure Decoding Based on a Multi-Kernel Convolutional BiLSTM Network.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jul 17, 2024
Sleep quality is an essential parameter of a healthy human life, while sleep disorders such as sleep apnea are abundant. In the investigation of sleep and its malfunction, the gold-standard is polysomnography, which utilizes an extensive range of var...
Sleep Stages Nose Sleep, REM Wakefulness Neural Networks, Computer Humans Pressure Adult Algorithms Polysomnography Male Female Deep Learning Young Adult Healthy Volunteers
View on PubMed DOI

Derivative Method to Detect Sleep and Awake States through Heart Rate Variability Analysis Using Machine Learning Algorithms.

Sensors (Basel, Switzerland) Jul 3, 2024
Sleep disorders can have harmful consequences in both the short and long term. They can lead to attention deficits, as well as cardiac, neurological and behavioral repercussions. One of the most widely used methods for assessing sleep disorders is po...
Adult Male Heart Rate Wakefulness Machine Learning Humans Sleep Algorithms Polysomnography Female Young Adult
View on PubMed DOI

Estimating vigilance from the pre-work shift sleep using an under-mattress sleep sensor.

Journal of sleep research Jan 7, 2024
Predicting vigilance impairment in high-risk shift work occupations is critical to help to reduce workplace errors and accidents. Current methods rely on multi-night, often manually entered, sleep data. This study developed a machine learning model f...
Arousal Shift Work Schedule Humans Male Wakefulness Machine Learning Psychomotor Performance Female Sleep Young Adult Adult
View on PubMed DOI

Real-Time Deep Learning-Based Drowsiness Detection: Leveraging Computer-Vision and Eye-Blink Analyses for Enhanced Road Safety.

Sensors (Basel, Switzerland) Jul 17, 2023
Drowsy driving can significantly affect driving performance and overall road safety. Statistically, the main causes are decreased alertness and attention of the drivers. The combination of deep learning and computer-vision algorithm applications has ...
Wakefulness Computers Deep Learning Blinking Automobile Driving Sleep Stages
View on PubMed DOI
Popular Topics
Recent Journals