AIMC Topic:
Signal Processing, Computer-Assisted

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Multimodal Assessment of Parkinson's Disease: A Deep Learning Approach.

IEEE journal of biomedical and health informatics Aug 23, 2018
Parkinson's disease is a neurodegenerative disorder characterized by a variety of motor symptoms. Particularly, difficulties to start/stop movements have been observed in patients. From a technical/diagnostic point of view, these movement changes can...
Male Female Gait Analysis Parkinson Disease Aged Handwriting Middle Aged Speech Signal Processing, Computer-Assisted Aged, 80 and over Deep Learning ROC Curve Gait Humans Image Processing, Computer-Assisted Databases, Factual
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Analyzing single-lead short ECG recordings using dense convolutional neural networks and feature-based post-processing to detect atrial fibrillation.

Physiological measurement Aug 23, 2018
OBJECTIVE: The prevalence of atrial fibrillation (AF) in the general population is 0.5%-1%. As AF is the most common sustained cardiac arrhythmia that is associated with an increased morbidity and mortality, its timely diagnosis is clinically desirab...
Humans Neural Networks, Computer Electrocardiography Signal Processing, Computer-Assisted Atrial Fibrillation
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Sleep-wake classification via quantifying heart rate variability by convolutional neural network.

Physiological measurement Aug 20, 2018
OBJECTIVE: Fluctuations in heart rate are intimately related to changes in the physiological state of the organism. We exploit this relationship by classifying a human participant's wake/sleep status using his instantaneous heart rate (IHR) series.
Female Adult Male Humans Neural Networks, Computer Healthy Volunteers Databases, Factual Wakefulness Sleep Electrocardiography Signal Processing, Computer-Assisted Heart Rate
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Developing a Three- to Six-State EEG-Based Brain-Computer Interface for a Virtual Robotic Manipulator Control.

IEEE transactions on bio-medical engineering Aug 17, 2018
OBJECTIVE: We develop an electroencephalography (EEG)-based noninvasive brain-computer interface (BCI) system having short training time (15 min) that can be applied for high-performance control of robotic prosthetic systems.
Self-Help Devices Neural Prostheses Humans Signal Processing, Computer-Assisted Brain-Computer Interfaces Female Young Adult Adult Male Robotics Electroencephalography
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Densely connected convolutional networks for detection of atrial fibrillation from short single-lead ECG recordings.

Journal of electrocardiology Aug 10, 2018
The development of new technology such as wearables that record high-quality single channel ECG, provides an opportunity for ECG screening in a larger population, especially for atrial fibrillation screening. The main goal of this study is to develop...
Neural Networks, Computer Algorithms Electrocardiography Signal Processing, Computer-Assisted Atrial Fibrillation Humans
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Multiscaled Fusion of Deep Convolutional Neural Networks for Screening Atrial Fibrillation From Single Lead Short ECG Recordings.

IEEE journal of biomedical and health informatics Aug 7, 2018
Atrial fibrillation (AF) is one of the most common sustained chronic cardiac arrhythmia in elderly population, associated with a high mortality and morbidity in stroke, heart failure, coronary artery disease, systemic thromboembolism, etc. The early ...
Humans Electrocardiography Neural Networks, Computer Signal Processing, Computer-Assisted Algorithms Atrial Fibrillation ROC Curve
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Label-Free Biomolecule Detection in Physiological Solutions With Enhanced Sensitivity Using Graphene Nanogrids FET Biosensor.

IEEE transactions on nanobioscience Aug 6, 2018
Recently, graphene nanogrid sensor has been reported to be capable of sub-femtomolar sensing of Hepatitis B (Hep-B) surface antigen in buffer. However, for such low concentration of Hep-B in serum, it has been observed during real-time operation that...
Humans Graphite Neural Networks, Computer Signal Processing, Computer-Assisted Biosensing Techniques Hepatitis B Surface Antigens Limit of Detection Models, Chemical Equipment Design
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Modeling brain dynamic state changes with adaptive mixture independent component analysis.

NeuroImage Aug 4, 2018
There is a growing interest in neuroscience in assessing the continuous, endogenous, and nonstationary dynamics of brain network activity supporting the fluidity of human cognition and behavior. This non-stationarity may involve ever-changing formati...
Data Interpretation, Statistical Electroencephalography Signal Processing, Computer-Assisted Adult Models, Theoretical Unsupervised Machine Learning Wakefulness Cerebral Cortex Sleep Stages Humans
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Automatic recognition of arrhythmia based on principal component analysis network and linear support vector machine.

Computers in biology and medicine Aug 4, 2018
Electrocardiogram (ECG) classification is an important process in identifying arrhythmia, and neural network models have been widely used in this field. However, these models are often disrupted by heartbeat noise and are negatively affected by skewe...
Databases, Factual Electrocardiography Support Vector Machine Signal Processing, Computer-Assisted Arrhythmias, Cardiac Humans Neural Networks, Computer
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A New Approach on HCI Extracting Conscious Jaw Movements Based on EEG Signals Using Machine Learnings.

Journal of medical systems Aug 4, 2018
Machine computer interfaces (MCI) are assistive technologies enabling paralyzed peoples to control and communicate their environments. This study aims to discover and represents a new approach on MCI using left/right motions of voluntary jaw movement...
Humans Machine Learning Algorithms Jaw Signal Processing, Computer-Assisted Brain-Computer Interfaces Movement Support Vector Machine Principal Component Analysis Electroencephalography
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