AIMC Topic: Healthy Volunteers

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Using an artificial neural network for fast mapping of the oxygen extraction fraction with combined QSM and quantitative BOLD.

Magnetic resonance in medicine Jul 4, 2019
PURPOSE: To apply an artificial neural network (ANN) for fast and robust quantification of the oxygen extraction fraction (OEF) from a combined QSM and quantitative BOLD analysis of gradient echo data and to compare the ANN to a traditional quasi-New...
Computer Simulation Positron-Emission Tomography Female Humans Healthy Volunteers Adult Magnetic Resonance Imaging Neural Networks, Computer Male Gray Matter Brain Mapping Brain White Matter Image Processing, Computer-Assisted Oxygen Cerebrovascular Circulation Oxygen Consumption Normal Distribution Least-Squares Analysis
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Deep learning-based selection of human sperm with high DNA integrity.

Communications biology Jul 3, 2019
Despite the importance of sperm DNA to human reproduction, currently no method exists to assess individual sperm DNA quality prior to clinical selection. Traditionally, skilled clinicians select sperm based on a variety of morphological and motility ...
Normal Distribution Learning Curve Chromatin Bayes Theorem Semen Analysis Humans DNA Fragmentation Neural Networks, Computer Spermatozoa Male Healthy Volunteers Deep Learning DNA
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Weighted Transfer Learning for Improving Motor Imagery-Based Brain-Computer Interface.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jun 17, 2019
One of the major limitations of motor imagery (MI)-based brain-computer interface (BCI) is its long calibration time. Due to between sessions/subjects variations in the properties of brain signals, typically, a large amount of training data needs to ...
Space Perception Imagination Humans Machine Learning Algorithms Electroencephalography Calibration Brain-Computer Interfaces Healthy Volunteers Movement Psychomotor Performance
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Testing a deep convolutional neural network for automated hippocampus segmentation in a longitudinal sample of healthy participants.

NeuroImage May 7, 2019
Subtle changes in hippocampal volumes may occur during both physiological and pathophysiological processes in the human brain. Assessing hippocampal volumes manually is a time-consuming procedure, however, creating a need for automated segmentation m...
Female Young Adult Adult Male Middle Aged Humans Algorithms Healthy Volunteers Hippocampus Neuroimaging Deep Learning Adolescent Child Image Processing, Computer-Assisted Magnetic Resonance Imaging
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A Convolutional Neural Network for the Detection of Asynchronous Steady State Motion Visual Evoked Potential.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society May 7, 2019
A key issue in brain-computer interface (BCI) is the detection of intentional control (IC) states and non-intentional control (NC) states in an asynchronous manner. Furthermore, for steady-state visual evoked potential (SSVEP) BCI systems, multiple s...
Humans Neural Networks, Computer Algorithms Electroencephalography Brain-Computer Interfaces Stroke Evoked Potentials, Visual Intention Healthy Volunteers Aged Psychomotor Performance Young Adult Adult Male Middle Aged
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Gaussian Process Trajectory Learning and Synthesis of Individualized Gait Motions.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Apr 30, 2019
This paper proposes a Gaussian process-based method for trajectory learning and generation of individualized gait motions at arbitrary user-designated walking speeds, intended to be used in generating reference motions for robotic gait rehabilitation...
Gait Disorders, Neurologic Middle Aged Models, Statistical Robotics Gait Healthy Volunteers Leg Walking Speed Normal Distribution Aged Humans Markov Chains Young Adult Algorithms Anthropometry Adult Joints Female Biomechanical Phenomena Male
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Hand Extension Robot Orthosis (HERO) Glove: Development and Testing With Stroke Survivors With Severe Hand Impairment.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Apr 11, 2019
The hand extension robot orthosis (HERO) glove was iteratively designed with occupational therapists and stroke survivors to enable stroke survivors with severe hand impairment to grasp and stabilize everyday objects, while being portable, lightweigh...
Stroke Rehabilitation Self-Help Devices Movement Disorders Wearable Electronic Devices Treatment Outcome Hand Strength Robotics Young Adult Hand Adult Stroke Male Prosthesis Design Middle Aged Healthy Volunteers Humans Adolescent Psychomotor Performance Female Range of Motion, Articular Aged Aged, 80 and over
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A deep learning-based decision support system for diagnosis of OSAS using PTT signals.

Medical hypotheses Mar 27, 2019
Sleep disorders, which negatively affect an individual's daily quality of life, are a common problem for most of society. The most dangerous sleep disorder is obstructive sleep apnea syndrome (OSAS), which manifests itself during sleep and can cause ...
Medical Informatics Humans Sleep Wake Disorders Neural Networks, Computer Algorithms Sleep Apnea, Obstructive Female Decision Support Systems, Clinical Aged Electroencephalography Carbon Dioxide Electrocardiography Adult Signal Processing, Computer-Assisted Heart Rate Support Vector Machine Male Electromyography Healthy Volunteers Middle Aged Motivation Deep Learning
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Human electrocortical dynamics while stepping over obstacles.

Scientific reports Mar 18, 2019
To better understand human brain dynamics during visually guided locomotion, we developed a method of removing motion artifacts from mobile electroencephalography (EEG) and studied human subjects walking and running over obstacles on a treadmill. We ...
Brain Mapping Robotics Electroencephalography Exercise Test Walking Gait Electrodes Healthy Volunteers Artifacts Locomotion Humans Female Male Motor Cortex Parietal Lobe
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Cyborg groups enhance face recognition in crowded environments.

PloS one Mar 6, 2019
Recognizing a person in a crowded environment is a challenging, yet critical, visual-search task for both humans and machine-vision algorithms. This paper explores the possibility of combining a residual neural network (ResNet), brain-computer interf...
Facial Recognition Electroencephalography Reaction Time Healthy Volunteers Humans Brain Brain-Computer Interfaces Neural Networks, Computer Female Evoked Potentials, Visual Adult Male Decision Making
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