AIMC Topic: Pulse

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Determining the appropriate amount of anesthetic gas using DWT and EMD combined with neural network.

Journal of medical systems Dec 4, 2014
The spectrum of EEG has been studied to predict the depth of anesthesia using variety of signal processing methods up to date. Those standard models have used the full spectrum of EEG signals together with the systolic-diastolic pressure and pulse va...
Blood Pressure Electroencephalography Signal Processing, Computer-Assisted Heart Rate Time Factors Algorithms Dose-Response Relationship, Drug Female Male Aged Middle Aged Humans Neural Networks, Computer Sevoflurane Anesthetics, Inhalation Pulse Wavelet Analysis Methyl Ethers
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Evaluating the Sensitivity of Resting-State BOLD Variability to Age and Cognition after Controlling for Motion and Cardiovascular Influences: A Network-Based Approach.

Cerebral cortex (New York, N.Y. : 1991) Oct 1, 2020
Recent functional magnetic resonance imaging (fMRI) studies report that moment-to-moment variability in the BOLD signal is related to differences in age and cognition and, thus, may be sensitive to age-dependent decline. However, head motion and/or c...
Humans Motion Artifacts Pulse Aged, 80 and over Body Mass Index Image Processing, Computer-Assisted Magnetic Resonance Imaging Female Brain Mapping Adult Cognition Aging Male Aged Blood Pressure Machine Learning Middle Aged Brain
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Evaluation of Facial Pulse Signals using Deep Neural Net Models.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
The reliable measurement of the pulse rate using remote photoplethysmography (PPG) is very important for many medical applications. In this paper we present how deep neural networks (DNNs) models can be used in the problem of PPG signal classificatio...
Face Pulse Neural Networks, Computer Algorithms Photoplethysmography Signal Processing, Computer-Assisted Humans
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Convolutional Recurrent Neural Networks to Characterize the Circulation Component in the Thoracic Impedance during Out-of-Hospital Cardiac Arrest.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Pulse detection during out-of-hospital cardiac arrest remains challenging for both novel and expert rescuers because current methods are inaccurate and time-consuming. There is still a need to develop automatic methods for pulse detection, where the ...
Humans Neural Networks, Computer Cardiopulmonary Resuscitation Out-of-Hospital Cardiac Arrest Electric Impedance Pulse
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Multiple sensors-based kernel machine learning in smart environment.

The Review of scientific instruments Jan 1, 2017
Sensor-based monitoring systems use multiple sensors to identify high-level information based on the events that take place in a monitored environment. Identification and health care are important tasks in the smart environment. This paper presents a...
Dermatoglyphics Pattern Recognition, Automated Pulse Humans Algorithms Health Status Machine Learning
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Monitoring and detecting atrial fibrillation using wearable technology.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
Atrial fibrillation (AFib) is diagnosed by analysis of the morphological and rhythmic properties of the electrocardiogram. It was recently shown that accurate detection of AFib is possible using beat-to-beat interval variations. This raises the quest...
Accelerometry Pulse Photoplethysmography Retrospective Studies Heart Rate Signal Processing, Computer-Assisted Electrocardiography Humans Monitoring, Ambulatory Reproducibility of Results Atrial Fibrillation Algorithms
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