AIMC Topic: Signal Processing, Computer-Assisted

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A Hybrid Network for ERP Detection and Analysis Based on Restricted Boltzmann Machine.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Mar 1, 2018
Detecting and Please provide the correct one analyzing the event-related potential (ERP) remains an important problem in neuroscience. Due to the low signal-to-noise ratio and complex spatio-temporal patterns of ERP signals, conventional methods usua...
Neural Networks, Computer Algorithms Electroencephalography Humans Signal-To-Noise Ratio Evoked Potentials Event-Related Potentials, P300 Signal Processing, Computer-Assisted Prosthesis Design Brain-Computer Interfaces
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Robust Support Matrix Machine for Single Trial EEG Classification.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Mar 1, 2018
Electroencephalogram (EEG) signals are of complex structure and can be naturally represented as matrices. Classification is one of the most important steps for EEG signal processing. Newly developed classifiers can handle these matrix-form data by ad...
Artifacts Brain-Computer Interfaces Humans Signal-To-Noise Ratio Software Algorithms Support Vector Machine Electroencephalography Signal Processing, Computer-Assisted
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[Design and Implementation of Portable Abnormal ECG Signal Analysis Instrument Based on Feature Classifcation].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation Feb 8, 2018
OBJECTIVES: To collect and analyze the ECG signal in real time, the analog filter and the signal amplifier were used to construct the abnormal signal acquisition and classification system.
Signal Processing, Computer-Assisted Heart Arrhythmias, Cardiac Algorithms Electrocardiography Support Vector Machine Humans
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VLSI Design of SVM-Based Seizure Detection System With On-Chip Learning Capability.

IEEE transactions on biomedical circuits and systems Feb 1, 2018
Portable automatic seizure detection system is very convenient for epilepsy patients to carry. In order to make the system on-chip trainable with high efficiency and attain high detection accuracy, this paper presents a very large scale integration (...
Signal Processing, Computer-Assisted Humans Machine Learning Algorithms Wearable Electronic Devices Electroencephalography Seizures
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As above, so below? Towards understanding inverse models in BCI.

Journal of neural engineering Feb 1, 2018
OBJECTIVE: In brain-computer interfaces (BCI), measurements of the user's brain activity are classified into commands for the computer. With EEG-based BCIs, the origins of the classified phenomena are often considered to be spatially localized in the...
Algorithms Brain Electroencephalography Humans Machine Learning Signal Processing, Computer-Assisted Brain-Computer Interfaces
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Machine-Learning Prediction of Drug-Induced Cardiac Arrhythmia: Analysis of Gene Expression and Clustering.

Critical reviews in biomedical engineering Jan 1, 2018
A marked delay in the electrical repolarization of heart ventricles is characterized by prolongation of the Q-T wave (QT) interval on a surface electrocardiogram. Such a delay can lead to potentially life-threatening cardiac arrhythmia (torsades de p...
Heart Drug Evaluation, Preclinical Male Arrhythmias, Cardiac Heart Ventricles Support Vector Machine MAP Kinase Signaling System Clinical Trials as Topic Reproducibility of Results Drug Design Cluster Analysis Gene Expression Regulation Humans False Positive Reactions Sensitivity and Specificity Gene Expression Profiling Signal Processing, Computer-Assisted Mice Torsades de Pointes Machine Learning Animals Rats Female Electrocardiography
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Research: Use of Dry Electroencephalogram and Support Vector for Objective Pain Assessment.

Biomedical instrumentation & technology Jan 1, 2018
The reliability of normal gel-based electrode electroencephalogram (EEG) for measuring pain has been validated. To date, however, few documented trials have used dry EEG for pain quantification. The primary goal of this study was to objectively quant...
Humans Female Young Adult Support Vector Machine Electroencephalography Adult Male Signal Processing, Computer-Assisted Cohort Studies Pain Measurement
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ABroAD: A Machine Learning Based Approach to Detect Broadband NIRS Artefacts.

Advances in experimental medicine and biology Jan 1, 2018
Artefacts are a common and unwanted aspect of any measurement process, especially in a clinical environment, with multiple causes such as environmental changes or motion. In near-infrared spectroscopy (NIRS), there are several existing methods that c...
Spectroscopy, Near-Infrared Signal Processing, Computer-Assisted Artifacts Humans Machine Learning Brain
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Human emotion classification based on multiple physiological signals by wearable system.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2018
BACKGROUND: Human emotion classification is traditionally achieved using multi-channel electroencephalogram (EEG) signal, which requires costly equipment and complex classification algorithms.
Humans Algorithms Wearable Electronic Devices Electrocardiography Support Vector Machine Emotions Monitoring, Ambulatory Respiration Posture Electroencephalography Signal Processing, Computer-Assisted
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Classification of single-channel EEG signals for epileptic seizures detection based on hybrid features.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2018
BACKGROUND: Epilepsy is a common chronic neurological disorder of the brain. Clinically, epileptic seizures are usually detected via the continuous monitoring of electroencephalogram (EEG) signals by experienced neurophysiologists.
Machine Learning Signal Processing, Computer-Assisted Humans Algorithms Sensitivity and Specificity Electroencephalography Epilepsy
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