Consciousness and complexity: a consilience of evidence

S Sarasso, AG Casali, S Casarotto… - Neuroscience of …, 2021 - academic.oup.com
Over the last years, a surge of empirical studies converged on complexity-related measures
as reliable markers of consciousness across many different conditions, such as sleep …

Artificial intelligence and its clinical application in Anesthesiology: a systematic review

S Lopes, G Rocha, L Guimarães-Pereira - Journal of Clinical Monitoring …, 2024 - Springer
Purpose Application of artificial intelligence (AI) in medicine is quickly expanding. Despite
the amount of evidence and promising results, a thorough overview of the current state of AI …

EEG-based emotion analysis using non-linear features and ensemble learning approaches

MM Rahman, AK Sarkar, MA Hossain… - Expert Systems with …, 2022 - Elsevier
Recognition of emotions based on electroencephalography (EEG) has become one of the
most emerging topics for healthcare, education system, knowledge sharing, gaming, and …

Use of multiple EEG features and artificial neural network to monitor the depth of anesthesia

Y Gu, Z Liang, S Hagihira - Sensors, 2019 - mdpi.com
The electroencephalogram (EEG) can reflect brain activity and contains abundant
information of different anesthetic states of the brain. It has been widely used for monitoring …

Characteristics of EEG microstate sequences during propofol-induced alterations of brain consciousness states

Z Liu, L Si, W Xu, K Zhang, Q Wang… - … on Neural Systems …, 2022 - ieeexplore.ieee.org
Monitoring the consciousness states of patients and ensuring the appropriate depth of
anesthesia (DOA) is critical for the safe implementation of surgery. In this study, a high …

Driving fatigue detecting based on EEG signals of forehead area

Z Mu, J Hu, J Yin - International Journal of Pattern Recognition and …, 2017 - World Scientific
This study examined whether prefrontal brain region electroencephalography (EEG) can be
used to detect driver's fatigue. The participants were 13 healthy university students with …

EEG signals analysis using multiscale entropy for depth of anesthesia monitoring during surgery through artificial neural networks

Q Liu, YF Chen, SZ Fan, MF Abbod… - … methods in medicine, 2015 - Wiley Online Library
In order to build a reliable index to monitor the depth of anesthesia (DOA), many algorithms
have been proposed in recent years, one of which is sample entropy (SampEn), a commonly …

Reliable sleep staging of unseen subjects with fusion of multiple EEG features and RUSBoost

R Jain, RA Ganesan - Biomedical Signal Processing and Control, 2021 - Elsevier
Extensive experiments have been carried out in this study to classify sleep EEG from three
different standard databases–Sleep EDF, DREAMS and Expanded sleep EDF databases …

Information-based classification of electroencephalography (EEG) signals for healthy adolescents and adolescents with symptoms of Schizophrenia

H Namazi - Fluctuation and Noise Letters, 2020 - World Scientific
Analysis of the brain activity is the major research area in human neuroscience. Besides
many works that have been conducted on analysis of brain activity in case of healthy …

Comparison of deep learning algorithms in predicting expert assessments of pain scores during surgical operations using analgesia nociception index

WH Jean, P Sutikno, SZ Fan, MF Abbod, JS Shieh - Sensors, 2022 - mdpi.com
There are many surgical operations performed daily in operation rooms worldwide.
Adequate anesthesia is needed during an operation. Besides hypnosis, adequate analgesia …