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Showing 1491 to 1500 of 1686 articles

Encoding physiological signals as images for affective state recognition using convolutional neural networks.

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
Affective state recognition based on multiple modalities of physiological signals has been a hot research topic. Traditional methods require designing hand-crafted features based on domain knowledge, which is time-consuming and has not achieved a sat...
Support Vector Machine Humans Emotions Neural Networks, Computer
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Predicting local field potentials with recurrent neural networks.

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
We present a Recurrent Neural Network using LSTM (Long Short Term Memory) that is capable of modeling and predicting Local Field Potentials. We train and test the network on real data recorded from epilepsy patients. We construct networks that predic...
Epilepsy Humans Databases, Factual Neural Networks, Computer Sensitivity and Specificity
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Application of cross-correlated delay shift rule in spiking neural networks for interictal spike detection.

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
This study proposes a Cross-Correlated Delay Shift (CCDS) supervised learning rule to train neurons with associated spatiotemporal patterns to classify spike patterns. The objective of this study was to evaluate the feasibility of using the CCDS rule...
Neural Networks, Computer Humans Machine Learning Epilepsy Action Potentials Algorithms Neurons Electroencephalography Models, Theoretical
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Support vectors machine classification of surface electromyography for non-invasive naturally controlled hand prostheses.

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
The scientific researches in human rehabilitation techniques have continually evolved to offer again the mobility and freedom lost to disability. Many systems managed by myoelectric signals intended to mimic the movement of the human arm still have r...
Support Vector Machine Signal Processing, Computer-Assisted Prostheses and Implants Hand Humans Databases, Factual Electromyography Forearm
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Heart beat characterization from ballistocardiogram signals using extended functions of multiple instances.

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
A multiple instance learning (MIL) method, extended Function of Multiple Instances (eFUMI), is applied to ballistocardiogram (BCG) signals produced by a hydraulic bed sensor. The goal of this approach is to learn a personalized heartbeat "concept" fo...
Heart Rate Uncertainty Transducers Ballistocardiography Humans Machine Learning
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Fall risk probability estimation based on supervised feature learning using public fall datasets.

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
Risk of falling is considered among major threats for elderly population and therefore started to play an important role in modern healthcare. With recent development of sensor technology, the number of studies dedicated to reliable fall detection sy...
Supervised Machine Learning Probability Accidental Falls Models, Statistical Algorithms Humans Risk Assessment
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An unsupervised learning for robust cardiac feature derivation from PPG signals.

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
We propose here derivation algorithms for physiological parameters like beat start point, systolic peak, pulse duration, peak-to-peak distance related to heart rate, dicrotic minima, diastolic peak from Photoplethysmogram (PPG) signals robustly. Our ...
Signal Processing, Computer-Assisted Heart Rate Photoplethysmography Unsupervised Machine Learning Systole Diastole Humans Algorithms
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Vessel extraction in X-ray angiograms 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 Aug 1, 2016
Coronary artery disease (CAD) is the most common type of heart disease which is the leading cause of death all over the world. X-ray angiography is currently the gold standard imaging technique for CAD diagnosis. These images usually suffer from low ...
Humans Neural Networks, Computer Tomography, X-Ray Computed X-Rays Coronary Artery Disease Learning Coronary Vessels Coronary Angiography
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A deep convolutional neural network for bleeding detection in Wireless Capsule Endoscopy images.

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
Wireless Capsule Endoscopy (WCE) is a standard non-invasive modality for small bowel examination. Recently, the development of computer-aided diagnosis (CAD) systems for gastrointestinal (GI) bleeding detection in WCE image videos has become an activ...
Capsule Endoscopy Gastrointestinal Hemorrhage Neural Networks, Computer Humans Diagnosis, Computer-Assisted
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Fetal facial standard plane recognition via very deep convolutional networks.

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
The accurate recognition of fetal facial standard plane (FFSP) (i.e., axial, coronal and sagittal plane) from ultrasound (US) images is quite essential for routine US examination. Since the labor-intensive and subjective measurement is too time-consu...
Humans Neural Networks, Computer Face Pattern Recognition, Automated Fetus Learning Ultrasonography, Prenatal
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