AIMC Topic: Humans

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Dual Mode HRI-HRI Control System with a Hybrid Admittance-Force Controller for Ultrasound Imaging.

Sensors (Basel, Switzerland)
The COVID-19 pandemic has brought unprecedented extreme pressure on the medical system due to the physical distance policy, especially for procedures such as ultrasound (US) imaging, which are usually carried out in person. Tele-operation systems are...

Fear Detection in Multimodal Affective Computing: Physiological Signals versus Catecholamine Concentration.

Sensors (Basel, Switzerland)
Affective computing through physiological signals monitoring is currently a hot topic in the scientific literature, but also in the industry. Many wearable devices are being developed for health or wellness tracking during daily life or sports activi...

Perioperative outcomes following robot-assisted partial nephrectomy for renal cell carcinoma according to surgeon generation.

BMC surgery
OBJECTIVE: The experience of performing robot-assisted partial nephrectomy (RAPN) is associated with better surgical outcomes. However, surgeon's generation may impact surgical outcomes. We evaluated the perioperative outcomes of RAPN between first- ...

Development of a deep learning model that predicts Bi-level positive airway pressure failure.

Scientific reports
Delaying intubation for patients failing Bi-Level Positive Airway Pressure (BIPAP) may be associated with harm. The objective of this study was to develop a deep learning model capable of aiding clinical decision making by predicting Bi-Level Positiv...

Plant phenotype relationship corpus for biomedical relationships between plants and phenotypes.

Scientific data
Medicinal plants have demonstrated therapeutic potential for applicability for a wide range of observable characteristics in the human body, known as "phenotype," and have been considered favorably in clinical treatment. With an ever increasing inter...

Deep learning-based automated segmentation of eight brain anatomical regions using head CT images in PET/CT.

BMC medical imaging
OBJECTIVE: We aim to propose a deep learning-based method of automated segmentation of eight brain anatomical regions in head computed tomography (CT) images obtained during positron emission tomography/computed tomography (PET/CT) scans. The brain r...

Dual-energy CT based mass density and relative stopping power estimation for proton therapy using physics-informed deep learning.

Physics in medicine and biology
Proton therapy requires accurate dose calculation for treatment planning to ensure the conformal doses are precisely delivered to the targets. The conversion of CT numbers to material properties is a significant source of uncertainty for dose calcula...

Decoding neural activity preceding balance loss during standing with a lower-limb exoskeleton using an interpretable deep learning model.

Journal of neural engineering
Falls are a leading cause of death in adults 65 and older. Recent efforts to restore lower-limb function in these populations have seen an increase in the use of wearable robotic systems; however, fall prevention measures in these systems require ear...

Deep Multi-Scale Residual Connected Neural Network Model for Intelligent Athlete Balance Control Ability Evaluation.

Computational intelligence and neuroscience
Athlete balance control ability plays an important role in different types of sports. Accurate and efficient evaluations of the balance control abilities can significantly improve the athlete management performance. With the rapid development of the ...

A Data-Driven Adaptive Emotion Recognition Model for College Students Using an Improved Multifeature Deep Neural Network Technology.

Computational intelligence and neuroscience
With the increasing pressure on college students in terms of study, work, emotion, and life, the emotional changes of college students are becoming more and more obvious. For college student management workers, if they can accurately grasp the emotio...