AIMC Topic: Signal Processing, Computer-Assisted

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Detection of strict left bundle branch block by neural network and a method to test detection consistency.

Physiological measurement Mar 6, 2020
OBJECTIVE: To develop an automatic algorithm to detect strict left bundle branch block (LBBB) on electrocardiograms (ECG) and propose a procedure to test the consistency of neural network detections.
Electrocardiography Signal Processing, Computer-Assisted Bundle-Branch Block Humans Neural Networks, Computer
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SeizureBank: A Repository of Analysis-ready Seizure Signal Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium Mar 4, 2020
Approximately 60 million people worldwide suffer from epileptic seizures. A key challenge in machine learning ap proaches for epilepsy research is the lack of a data resource of analysis-ready (no additional preprocessing is needed when using the dat...
Male Epilepsy Infant Seizures Data Analysis Humans Pilot Projects Data Management Adolescent Datasets as Topic Female Electroencephalography Child, Preschool Young Adult Machine Learning Signal Processing, Computer-Assisted Child
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A Residual Based Attention Model for EEG Based Sleep Staging.

IEEE journal of biomedical and health informatics Mar 3, 2020
Sleep staging is to score the sleep state of a subject into different sleep stages such as Wake and Rapid Eye Movement (REM). It plays an indispensable role in the diagnosis and treatment of sleep disorders. As manual sleep staging through well-train...
Aged Young Adult Adult Neural Networks, Computer Humans Databases, Factual Male Female Electroencephalography Middle Aged Signal Processing, Computer-Assisted Deep Learning Sleep Stages
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Automated classification of five seizure onset patterns from intracranial electroencephalogram signals.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology Mar 3, 2020
OBJECTIVE: The electroencephalographic (EEG) signals contain information about seizures and their onset location. There are several seizure onset patterns reported in the literature, and these patterns have clinical significance. In this work, we pro...
Machine Learning Brain Electroencephalography Humans Seizures Signal Processing, Computer-Assisted
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A-phase classification using convolutional neural networks.

Medical & biological engineering & computing Mar 2, 2020
A series of short events, called A-phases, can be observed in the human electroencephalogram (EEG) during Non-Rapid Eye Movement (NREM) sleep. These events can be classified in three groups (A1, A2, and A3) according to their spectral contents, and a...
Deep Learning Electroencephalography Signal Processing, Computer-Assisted Sleep Stages Young Adult Adult Male Neural Networks, Computer Female Humans
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iLoF: An intelligent Lab on Fiber Approach for Human Cancer Single-Cell Type Identification.

Scientific reports Feb 21, 2020
With the advent of personalized medicine, there is a movement to develop "smaller" and "smarter" microdevices that are able to distinguish similar cancer subtypes. Tumor cells display major differences when compared to their natural counterparts, due...
Humans Artificial Intelligence Neoplasms Cell Line, Tumor Single-Cell Analysis Optical Tweezers Image Processing, Computer-Assisted Signal Processing, Computer-Assisted Optical Fibers Probability
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Separation of HCM and LQT Cardiac Diseases with Machine Learning of Ca2+ Transient Profiles.

Methods of information in medicine Feb 20, 2020
BACKGROUND:  Modeling human cardiac diseases with induced pluripotent stem cells not only enables to study disease pathophysiology and develop therapies but also, as we have previously showed, it can offer a tool for disease diagnostics. We previousl...
Calcium Algorithms Carrier Proteins Cardiomyopathy, Hypertrophic Diagnosis, Differential Tropomyosin Signal Processing, Computer-Assisted Humans Long QT Syndrome Machine Learning
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Dynamic time warping-based transfer learning for improving common spatial patterns in brain-computer interface.

Journal of neural engineering Feb 18, 2020
OBJECTIVE: Common spatial patterns (CSP) is a prominent feature extraction algorithm in motor imagery (MI)-based brain-computer interfaces (BCIs). However, CSP is computed using sample-based covariance-matrix estimation. Hence, its performance deteri...
Databases, Factual Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces Imagination Humans Machine Learning
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ECG Authentication Hardware Design With Low-Power Signal Processing and Neural Network Optimization With Low Precision and Structured Compression.

IEEE transactions on biomedical circuits and systems Feb 17, 2020
Biometrics such as facial features, fingerprint, and iris are being used increasingly in modern authentication systems. These methods are now popular and have found their way into many portable electronics such as smartphones, tablets, and laptops. F...
Humans Neural Networks, Computer Algorithms Biometry Wearable Electronic Devices Electrocardiography Signal Processing, Computer-Assisted
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A Review of Algorithm & Hardware Design for AI-Based Biomedical Applications.

IEEE transactions on biomedical circuits and systems Feb 17, 2020
This paper reviews the state of the arts and trends of the AI-Based biomedical processing algorithms and hardware. The algorithms and hardware for different biomedical applications such as ECG, EEG and hearing aid have been reviewed and discussed. Fo...
Humans Artificial Intelligence Biomedical Engineering Electrodiagnosis Algorithms Signal Processing, Computer-Assisted
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