AIMC Topic: Healthy Volunteers

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Analysis of body pressure distribution on car seats by using deep learning.

Applied ergonomics Nov 21, 2018
This study aimed to extract information from body pressure distribution, including comfort, participant body size, and seat characteristics by using supervised deep learning, and body pressure characteristics corresponding to sensory evaluation by us...
Body Size Adult Male Deep Learning Automobiles Pressure Ergonomics Sitting Position Equipment Design Healthy Volunteers Humans Female
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Machine learning provides novel neurophysiological features that predict performance to inhibit automated responses.

Scientific reports Nov 2, 2018
Neurophysiological features like event-related potentials (ERPs) have long been used to identify different cognitive sub-processes that may contribute to task performance. It has however remained unclear whether "classical" ERPs are truly the best re...
Young Adult Adult Male Models, Neurological Humans Machine Learning Female Inhibition, Psychological Neurophysiology Motor Cortex Behavior Observation Techniques Biological Variation, Population Electroencephalography Reaction Time Healthy Volunteers Evoked Potentials
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On the robustness of real-time myoelectric control investigations: a multiday Fitts' law approach.

Journal of neural engineering Oct 19, 2018
OBJECTIVE: Real-time myoelectric experimental protocol is considered as a means to quantify usability of myoelectric control schemes. While usability should be considered over time to assure clinical robustness, all real-time studies reported thus fa...
Pattern Recognition, Automated Electromyography Artificial Limbs Healthy Volunteers Psychomotor Performance Adult Male Computer Systems Signal Processing, Computer-Assisted Female Reproducibility of Results Young Adult Humans Neural Networks, Computer
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Automated segmentation of en face choroidal images obtained by optical coherent tomography by machine learning.

Japanese journal of ophthalmology Oct 6, 2018
PURPOSE: To develop an automated method to segment the choroidal layers of en face optical coherent tomography (OCT) images by machine learning.
Middle Aged Imaging, Three-Dimensional Choroid Tomography, Optical Coherence Young Adult Adult Cross-Sectional Studies Male Healthy Volunteers Retinal Pigment Epithelium Humans Machine Learning Prospective Studies Female Reproducibility of Results Aged Aged, 80 and over
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Compact convolutional neural networks for classification of asynchronous steady-state visual evoked potentials.

Journal of neural engineering Oct 3, 2018
OBJECTIVE: Steady-state visual evoked potentials (SSVEPs) are neural oscillations from the parietal and occipital regions of the brain that are evoked from flickering visual stimuli. SSVEPs are robust signals measurable in the electroencephalogram (E...
Machine Learning Algorithms Reproducibility of Results Adult Electroencephalography Humans Neural Networks, Computer Photic Stimulation Visual Cortex Signal Processing, Computer-Assisted Healthy Volunteers Brain-Computer Interfaces Evoked Potentials, Visual
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Classification of Overt and Covert Speech for Near-Infrared Spectroscopy-Based Brain Computer Interface.

Sensors (Basel, Switzerland) Sep 7, 2018
People suffering from neuromuscular disorders such as locked-in syndrome (LIS) are left in a paralyzed state with preserved awareness and cognition. In this study, it was hypothesized that changes in local hemodynamic activity, due to the activation ...
Hemoglobins Healthy Volunteers Brain-Computer Interfaces Broca Area Humans Spectroscopy, Near-Infrared Speech Support Vector Machine
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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.
Humans Neural Networks, Computer Databases, Factual Male Electrocardiography Signal Processing, Computer-Assisted Female Adult Heart Rate Healthy Volunteers Wakefulness Sleep
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Deep learning-based detection and classification of geographic atrophy using a deep convolutional neural network classifier.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie Aug 8, 2018
PURPOSE: To automatically detect and classify geographic atrophy (GA) in fundus autofluorescence (FAF) images using a deep learning algorithm.
Geographic Atrophy Tomography, Optical Coherence Fundus Oculi Healthy Volunteers Fluorescein Angiography Male Middle Aged Disease Progression Diagnosis, Computer-Assisted Humans Algorithms Neural Networks, Computer Female Machine Learning Reproducibility of Results Aged Sensitivity and Specificity
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Using principal component analysis to reduce complex datasets produced by robotic technology in healthy participants.

Journal of neuroengineering and rehabilitation Jul 31, 2018
BACKGROUND: The KINARM robot produces a granular dataset of participant performance metrics associated with proprioceptive, motor, visuospatial, and executive function. This comprehensive battery includes several behavioral tasks that each generate 9...
Principal Component Analysis Robotics Healthy Volunteers Humans Proprioception Female Adult Male
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Shoulder physiotherapy exercise recognition: machine learning the inertial signals from a smartwatch.

Physiological measurement Jul 23, 2018
OBJECTIVE: Participation in a physical therapy program is considered one of the greatest predictors of successful conservative management of common shoulder disorders. However, adherence to these protocols is often poor and typically worse for unsupe...
Exercise Therapy Healthy Volunteers Shoulder Physical Therapy Modalities Support Vector Machine Monitoring, Physiologic Signal Processing, Computer-Assisted Patient Compliance Humans Computers, Handheld Neural Networks, Computer Machine Learning Female Young Adult Adult Male Middle Aged
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