AIMC Topic: Healthy Volunteers

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Foveal avascular zone segmentation in optical coherence tomography angiography images using a deep learning approach.

Scientific reports
The purpose of this study was to introduce a new deep learning (DL) model for segmentation of the fovea avascular zone (FAZ) in en face optical coherence tomography angiography (OCTA) and compare the results with those of the device's built-in softwa...

Artificial Intelligence-Assisted motion capture for medical applications: a comparative study between markerless and passive marker motion capture.

Computer methods in biomechanics and biomedical engineering
We aimed to determine whether artificial intelligence (AI)-assisted markerless motion capture software is useful in the clinical medicine and rehabilitation fields. Currently, it is unclear whether the AI-assisted markerless method can be applied to ...

EEG-based trial-by-trial texture classification during active touch.

Scientific reports
Trial-by-trial texture classification analysis and identifying salient texture related EEG features during active touch that are minimally influenced by movement type and frequency conditions are the main contributions of this work. A total of twelve...

Development of LC-MS/MS determination method and backpropagation artificial neural networks pharmacokinetic model of febuxostat in healthy subjects.

Journal of clinical pharmacy and therapeutics
WHAT IS KNOWN AND OBJECTIVE: Febuxostat is a well-known drug for treating hyperuricemia and gout. The published methods for determination of febuxostat in human plasma might be unsuitable for high-throughput determination and widespread application. ...

Neuromorphic on-chip recognition of saliva samples of COPD and healthy controls using memristive devices.

Scientific reports
Chronic Obstructive Pulmonary Disease (COPD) is a life-threatening lung disease, affecting millions of people worldwide. Implementation of Machine Learning (ML) techniques is crucial for the effective management of COPD in home-care environments. How...

Wearable Biofeedback Improves Human-Robot Compliance during Ankle-Foot Exoskeleton-Assisted Gait Training: A Pre-Post Controlled Study in Healthy Participants.

Sensors (Basel, Switzerland)
The adjunctive use of biofeedback systems with exoskeletons may accelerate post-stroke gait rehabilitation. Wearable patient-oriented human-robot interaction-based biofeedback is proposed to improve patient-exoskeleton compliance regarding the intera...

Reconstructing lost BOLD signal in individual participants using deep machine learning.

Nature communications
Signal loss in blood oxygen level-dependent (BOLD) functional neuroimaging is common and can lead to misinterpretation of findings. Here, we reconstructed compromised fMRI signal using deep machine learning. We trained a model to learn principles gov...

Accelerating T mapping of the brain by integrating deep learning priors with low-rank and sparse modeling.

Magnetic resonance in medicine
PURPOSE: To accelerate T mapping with highly sparse sampling by integrating deep learning image priors with low-rank and sparse modeling.

Exploring augmented grasping capabilities in a multi-synergistic soft bionic hand.

Journal of neuroengineering and rehabilitation
BACKGROUND: State-of-the-art bionic hands incorporate hi-tech devices which try to overcome limitations of conventional single grip systems. Unfortunately, their complexity often limits mechanical robustness and intuitive prosthesis control. Recently...