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Showing 1241 to 1250 of 1686 articles

Novel Deep Convolutional Neural Network for Cuff-less Blood Pressure Measurement Using ECG and PPG Signals.

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
Cuff-less blood pressure (BP) is a potential method for BP monitoring because it is undisturbed and continuous monitoring. Existing cuff-less estimation methods are easily influenced by signal noise and non-ideal signal morphology. In this study we p...
Blood Pressure Determination Photoplethysmography Electrocardiography Blood Pressure Humans Neural Networks, Computer
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An Electrocardiogram Delineator via Deep Segmentation Network.

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
Electrocardiogram (ECG) delineation is a process to detect multiple characteristic points, which contain critical diagnostic information about cardiac diseases. We treat the ECG delineation task as an one-dimensional segmentation problem, and propose...
Arrhythmias, Cardiac Deep Learning Neural Networks, Computer Electrocardiography Databases, Factual Humans
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A Deep Learning Method to Detect Atrial Fibrillation Based on Continuous Wavelet Transform.

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
Atrial fibrillation (AF) is one of the most common arrhythmias. The automatic AF detection is of great clinical significance but at the same time it remains a big problem to researchers. In this study, a novel deep learning method to detect AF was pr...
Humans Neural Networks, Computer Atrial Fibrillation Wavelet Analysis Deep Learning Electrocardiography
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A Robust Machine Learning Architecture for a Reliable ECG Rhythm Analysis during CPR.

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
Chest compressions delivered during cardiopulmonary resuscitation (CPR) induce artifacts in the ECG that may make the shock advice algorithms (SAA) of defibrillators inaccurate. There is evidence that methods consisting of adaptive filters that remov...
Artifacts Cardiopulmonary Resuscitation Out-of-Hospital Cardiac Arrest Defibrillators Humans Sensitivity and Specificity Machine Learning Electrocardiography Algorithms
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PPGnet: Deep Network for Device Independent Heart Rate Estimation from Photoplethysmogram.

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
Photoplethysmogram (PPG) is increasingly used to provide monitoring of the cardiovascular system under ambulatory conditions. Wearable devices like smartwatches use PPG to allow long-term unobtrusive monitoring of heart rate in free-living conditions...
Humans Signal Processing, Computer-Assisted Deep Learning Monitoring, Ambulatory Wearable Electronic Devices Models, Cardiovascular Heart Rate Photoplethysmography Artifacts Algorithms Computer Simulation
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Improved A-phase Detection of Cyclic Alternating Pattern Using Deep Learning.

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
In recent years, machine learning algorithms have become increasingly popular for analyzing biomedical signals. This includes the detection of cyclic alternating pattern (CAP) in electroencephalography recordings. Here, we investigate the performance...
Electroencephalography Algorithms Deep Learning Humans Neural Networks, Computer
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A joint-feature learning-based voice conversion system for dysarthric user based on deep learning technology.

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
Dysarthria speakers suffer from poor communication, and voice conversion (VC) technology is a potential approach for improving their speech quality. This study presents a joint feature learning approach to improve a sub-band deep neural network-based...
Speech Production Measurement Self-Help Devices Dysarthria Humans Speech Intelligibility Voice Deep Learning
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Deep Learning Techniques for Improving Digital Gait Segmentation.

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
Wearable technology for the automatic detection of gait events has recently gained growing interest, enabling advanced analyses that were previously limited to specialist centres and equipment (e.g., instrumented walkway). In this study, we present a...
Humans Algorithms Deep Learning Wearable Electronic Devices Parkinson Disease Reproducibility of Results Case-Control Studies Gait Analysis Gait Foot Wavelet Analysis
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Fusion of End-to-End Deep Learning Models for Sequence-to-Sequence Sleep Staging.

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
Sleep staging, a process of identifying the sleep stages associated with polysomnography (PSG) epochs, plays an important role in sleep monitoring and diagnosing sleep disorders. We present in this work a model fusion approach to automate this task. ...
Computer Simulation Deep Learning Humans Sleep Wake Disorders Sleep Stages Polysomnography
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2D Wavelet Scalogram Training of Deep Convolutional Neural Network for Automatic Identification of Micro-Scale Sharp Wave Biomarkers in the Hypoxic-Ischemic EEG of Preterm Sheep.

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
We have recently demonstrated that micro-scale Sharp waves in the first few hours EEG of asphyxiated preterm fetal sheep models are the reliable prognostic biomarkers for Hypoxic-Ischemic Encephalopathy (HIE). Higher number of sharp waves within the ...
Animals Wavelet Analysis Electroencephalography Hypothermia, Induced Neural Networks, Computer Sheep Hypoxia-Ischemia, Brain Biomarkers Signal Processing, Computer-Assisted Animals, Newborn
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