AIMC Topic: Healthy Volunteers

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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...
Humans Proprioception Female Adult Male Principal Component Analysis Robotics Healthy Volunteers
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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...
Machine Learning Female Young Adult Adult Male Humans Neural Networks, Computer Exercise Therapy Healthy Volunteers Shoulder Physical Therapy Modalities Computers, Handheld Middle Aged Support Vector Machine Monitoring, Physiologic Signal Processing, Computer-Assisted Patient Compliance
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Assessing Wrist Movement With Robotic Devices.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jul 5, 2018
Robotic devices have been proposed to meet the rising need for high intensity, long duration, and goal-oriented therapy required to regain motor function after neurological injury. Complementing this application, exoskeletons can augment traditional ...
Exoskeleton Device Wrist Joint Hand Humans Prosthesis Design Biomechanical Phenomena Healthy Volunteers Robotics Psychomotor Performance Wrist Movement
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Acute pain intensity monitoring with the classification of multiple physiological parameters.

Journal of clinical monitoring and computing Jun 26, 2018
Current acute pain intensity assessment tools are mainly based on self-reporting by patients, which is impractical for non-communicative, sedated or critically ill patients. In previous studies, various physiological signals have been observed qualit...
Critical Illness Female Reproducibility of Results Young Adult Adult Humans Neural Networks, Computer Electromyography Heart Rate Healthy Volunteers Respiration Hot Temperature Male ROC Curve Monitoring, Physiologic Area Under Curve Pain Measurement Acute Pain Galvanic Skin Response
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Reshaping Movement Distributions With Limit-Push Robotic Training.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society May 21, 2018
High-cost situations need to be avoided. However, occasionally, cost may only be learned by experience. Here, we tested whether an artificially induced unstable and invisible high-cost region, a "limit-push" force field, might reshape people's motion...
Movement Stroke Rehabilitation Male Middle Aged Virtual Reality Cohort Studies Recovery of Function Robotics Hand Humans Stroke Healthy Volunteers Algorithms Psychomotor Performance Female Young Adult Adult
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MR fingerprinting Deep RecOnstruction NEtwork (DRONE).

Magnetic resonance in medicine Apr 6, 2018
PURPOSE: Demonstrate a novel fast method for reconstruction of multi-dimensional MR Fingerprinting (MRF) data using Deep Learning methods.
Adult Male Deep Learning Image Processing, Computer-Assisted Models, Theoretical Magnetic Resonance Imaging Healthy Volunteers Neuroimaging Signal-To-Noise Ratio Monte Carlo Method Neural Networks, Computer Algorithms Brain Computer Simulation Reproducibility of Results Phantoms, Imaging Humans Normal Distribution
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Transcriptomics and machine learning predict diagnosis and severity of growth hormone deficiency.

JCI insight Apr 5, 2018
BACKGROUND: The effect of gene expression data on diagnosis remains limited. Here, we show how diagnosis and classification of growth hormone deficiency (GHD) can be achieved from a single blood sample using a combination of transcriptomics and rando...
Predictive Value of Tests Principal Component Analysis Healthy Volunteers Datasets as Topic Transcriptome Case-Control Studies Adolescent Human Growth Hormone Growth Disorders Child, Preschool Child ROC Curve Humans Gene Regulatory Networks Biomarkers Machine Learning Polymorphism, Single Nucleotide Female Male Severity of Illness Index Gene Expression Profiling
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Deep learning with domain adaptation for accelerated projection-reconstruction MR.

Magnetic resonance in medicine Feb 4, 2018
Magnetic Resonance Imaging Liver Healthy Volunteers Humans Tomography, X-Ray Computed Fourier Analysis Neural Networks, Computer Reproducibility of Results Software Deep Learning Algorithms Image Processing, Computer-Assisted
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Deep learning approaches for detection and removal of ghosting artifacts in MR spectroscopy.

Magnetic resonance in medicine Feb 1, 2018
Signal-To-Noise Ratio Humans Magnetic Resonance Spectroscopy Normal Distribution Image Processing, Computer-Assisted Neural Networks, Computer Healthy Volunteers Algorithms Artifacts Brain Gray Matter Computer Simulation Image Enhancement Deep Learning
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Respiratory motion correction for free-breathing 3D abdominal MRI using CNN-based image registration: a feasibility study.

The British journal of radiology Jan 31, 2018
OBJECTIVE: Free-breathing abdomen imaging requires non-rigid motion registration of unavoidable respiratory motion in three-dimensional undersampled data sets. In this work, we introduce an image registration method based on the convolutional neural ...
Motion Respiratory-Gated Imaging Techniques Male Humans Healthy Volunteers Image Interpretation, Computer-Assisted Imaging, Three-Dimensional Neural Networks, Computer Image Enhancement Abdomen Female Signal-To-Noise Ratio Magnetic Resonance Imaging Adult Feasibility Studies
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