AIMC Topic: Electrodes, Implanted

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Deep-learning for seizure forecasting in canines with epilepsy.

Journal of neural engineering Apr 8, 2019
OBJECTIVE: This paper introduces a fully automated, subject-specific deep-learning convolutional neural network (CNN) system for forecasting seizures using ambulatory intracranial EEG (iEEG). The system was tested on a hand-held device (Mayo Epilepsy...
Forecasting Seizures Dogs Electrocorticography Electrodes, Implanted Animals Deep Learning Epilepsy
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Latent Phase Detection of Hypoxic-Ischemic Spike Transients in the EEG of Preterm Fetal Sheep Using Reverse Biorthogonal Wavelets & Fuzzy Classifier.

International journal of neural systems Mar 26, 2019
Hypoxic-ischemic (HI) studies in preterms lack reliable prognostic biomarkers for diagnostic tests of HI encephalopathy (HIE). Our group's observations from fetal sheep models suggest that potential biomarkers of HIE in the form of developing HI mic...
Hypoxia-Ischemia, Brain Electrodes, Implanted Fetus Wavelet Analysis Algorithms Sheep, Domestic Electroencephalography Signal Processing, Computer-Assisted Animals Fuzzy Logic
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Accuracy of robot-assisted versus optical frameless navigated stereoelectroencephalography electrode placement in children.

Journal of neurosurgery. Pediatrics Jan 4, 2019
OBJECTIVE The aim of this study was to compare the accuracy of optical frameless neuronavigation (ON) and robot-assisted (RA) stereoelectroencephalography (SEEG) electrode placement in children, and to identify factors that might increase the risk of...
Humans Brain Retrospective Studies Child Imaging, Three-Dimensional Magnetic Resonance Imaging Robotics Female Male Child, Preschool Neuronavigation Tomography Scanners, X-Ray Computed Drug Resistant Epilepsy Electrodes, Implanted Optical Devices Electroencephalography Brain Waves Stereotaxic Techniques
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Frameless robot-assisted stereoelectroencephalography for refractory epilepsy in pediatric patients: accuracy, usefulness, and technical issues.

Acta neurochirurgica Nov 9, 2018
BACKGROUND: Stereoelectroencephalography (SEEG) is an effective technique to help to locate and to delimit the epileptogenic area and/or to define relationships with functional cortical areas. We intend to describe the surgical technique and verify t...
Stereotaxic Techniques Drug Resistant Epilepsy Electrodes, Implanted Postoperative Complications Adolescent Child, Preschool Child Robotics Electroencephalography Clinical Decision-Making Female Male Humans
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A review on microelectrode recording selection of features for machine learning in deep brain stimulation surgery for Parkinson's disease.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology Sep 25, 2018
OBJECTIVE: This study seeks to systematically review the selection of features and algorithms for machine learning and automation in deep brain stimulation surgery (DBS) for Parkinson's disease. This will assist in consolidating current knowledge and...
Humans Microelectrodes Machine Learning Electrodes, Implanted Parkinson Disease Deep Brain Stimulation
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Comparison of logistic regression, support vector machines, and deep learning classifiers for predicting memory encoding success using human intracranial EEG recordings.

Journal of neural engineering Sep 13, 2018
OBJECTIVE: We sought to test the performance of three strategies for binary classification (logistic regression, support vector machines, and deep learning) for the problem of predicting successful episodic memory encoding using direct brain recordin...
Electrodes, Implanted Theta Rhythm Logistic Models Support Vector Machine Predictive Value of Tests Memory, Episodic Mental Recall Electroencephalography Stochastic Processes Algorithms Humans Computer Simulation Deep Learning
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Combining biophysical modeling and deep learning for multielectrode array neuron localization and classification.

Journal of neurophysiology May 30, 2018
Neural circuits typically consist of many different types of neurons, and one faces a challenge in disentangling their individual contributions in measured neural activity. Classification of cells into inhibitory and excitatory neurons and localizati...
Biophysical Phenomena Electrodes, Implanted Models, Neurological Action Potentials Neurons Brain Deep Learning
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Sub-millimeter ECoG pitch in human enables higher fidelity cognitive neural state estimation.

NeuroImage Apr 18, 2018
Electrocorticography (ECoG), electrophysiological recording from the pial surface of the brain, is a critical measurement technique for clinical neurophysiology, basic neurophysiology studies, and demonstrates great promise for the development of neu...
Humans Machine Learning Temporal Lobe Cerebral Cortex Language Adult Microelectrodes Image Processing, Computer-Assisted Electrocorticography Models, Theoretical Electrodes, Implanted
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Motor-commands decoding using peripheral nerve signals: a review.

Journal of neural engineering Mar 2, 2018
During the last few decades, substantial scientific and technological efforts have been focused on the development of neuroprostheses. The major emphasis has been on techniques for connecting the human nervous system with a robotic prosthesis via nat...
Prosthesis Design Peripheral Nerves Electrodes, Implanted Brain Animals Muscle, Skeletal Robotics Electromyography Humans Artificial Limbs
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Characterization of the stimulus waveforms generated by implantable pulse generators for deep brain stimulation.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology Jan 31, 2018
OBJECTIVE: To determine the circuit elements required to theoretically describe the stimulus waveforms generated by an implantable pulse generator (IPG) during clinical deep brain stimulation (DBS).
Deep Brain Stimulation Humans Electrodes, Implanted Neural Networks, Computer Computer Simulation
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