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Anesthesia

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Patient-Specific Classification of ICU Sedation Levels From Heart Rate Variability.

Critical care medicine
OBJECTIVE: To develop a personalizable algorithm to discriminate between sedation levels in ICU patients based on heart rate variability.

The characteristic patterns of neuronal avalanches in mice under anesthesia and at rest: An investigation using constrained artificial neural networks.

PloS one
Local perturbations within complex dynamical systems can trigger cascade-like events that spread across significant portions of the system. Cascades of this type have been observed across a broad range of scales in the brain. Studies of these cascade...

Multi-neuron intracellular recording in vivo via interacting autopatching robots.

eLife
The activities of groups of neurons in a circuit or brain region are important for neuronal computations that contribute to behaviors and disease states. Traditional extracellular recordings have been powerful and scalable, but much less is known abo...

An artificial neural network model for prediction of hypoxemia during sedation for gastrointestinal endoscopy.

The Journal of international medical research
OBJECTIVE: This study was designed to assess clinical predictors of hypoxemia and develop an artificial neural network (ANN) model for prediction of hypoxemia during sedation for gastrointestinal endoscopy examination.

Monitoring the level of hypnosis using a hierarchical SVM system.

Journal of clinical monitoring and computing
Monitoring level of hypnosis is a major ongoing challenge for anesthetists to reduce anesthetic drug consumption, avoiding intraoperative awareness and prolonged recovery. This paper proposes a novel automated method for accurate assessing of the lev...

Use of Multiple EEG Features and Artificial Neural Network to Monitor the Depth of Anesthesia.

Sensors (Basel, Switzerland)
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 depth of anesthesia (DoA). In this study, we propose a method that combine...

Design and Implementation of a Machine Learning Based EEG Processor for Accurate Estimation of Depth of Anesthesia.

IEEE transactions on biomedical circuits and systems
Accurate monitoring of the depth of anesthesia (DoA) is essential for intraoperative and postoperative patient's health. Commercially available electroencephalograph (EEG)-based DoA monitors are recommended only for certain anesthetic drugs and speci...

Autonomous Systems in Anesthesia: Where Do We Stand in 2020? A Narrative Review.

Anesthesia and analgesia
As most of us are aware, almost every facet of our society is becoming, for better or worse, progressively more technology-dependent. Technological advancement has made autonomous systems, also known as robots, an integral part of our life in several...