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Task Performance and Analysis

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HuBar: A Visual Analytics Tool to Explore Human Behavior Based on fNIRS in AR Guidance Systems.

IEEE transactions on visualization and computer graphics
The concept of an intelligent augmented reality (AR) assistant has significant, wide-ranging applications, with potential uses in medicine, military, and mechanics domains. Such an assistant must be able to perceive the environment and actions, reaso...

Cognitive and behavioral markers for human detection error in AI-assisted bridge inspection.

Applied ergonomics
Integrating Artificial Intelligence (AI) and drone technology into bridge inspections offers numerous advantages, including increased efficiency and enhanced safety. However, it is essential to recognize that this integration changes the cognitive er...

Human manipulation strategy when changing object deformability and task properties.

Scientific reports
Robotic literature widely addresses deformable object manipulation, but few studies analyzed human manipulation accounting for different levels of deformability and task properties. We asked participants to grasp and insert rigid and deformable objec...

Human-Robot Collaboration With a Corrective Shared Controlled Robot in a Sanding Task.

Human factors
OBJECTIVE: Physical and cognitive workloads and performance were studied for a corrective shared control (CSC) human-robot collaborative (HRC) sanding task.

An Integrated Electroencephalography and Eye-Tracking Analysis Using eXtreme Gradient Boosting for Mental Workload Evaluation in Surgery.

Human factors
ObjectiveWe aimed to develop advanced machine learning models using electroencephalogram (EEG) and eye-tracking data to predict the mental workload associated with engaging in various surgical tasks.BackgroundTraditional methods of evaluating mental ...

Learning performance and physiological feedback-based evaluation for human-robot collaboration.

Applied ergonomics
The development of Industry 4.0 has resulted in tremendous transformations in the manufacturing sector to supplement the human workforce through collaboration with robots. This emphasis on a human-centered approach is a vital aspect in promoting resi...

Assessing operator stress in collaborative robotics: A multimodal approach.

Applied ergonomics
In the era of Industry 4.0, the study of Human-Robot Collaboration (HRC) in advancing modern manufacturing and automation is paramount. An operator approaching a collaborative robot (cobot) may have feelings of distrust, and experience discomfort and...

Explainable AI improves task performance in human-AI collaboration.

Scientific reports
Artificial intelligence (AI) provides considerable opportunities to assist human work. However, one crucial challenge of human-AI collaboration is that many AI algorithms operate in a black-box manner where the way how the AI makes predictions remain...

Classification algorithms trained on simple (symmetric) lifting data perform poorly in predicting hand loads during complex (free-dynamic) lifting tasks.

Applied ergonomics
The performance of machine learning (ML) algorithms is dependent on which dataset it has been trained on. While ML algorithms are increasingly used for lift risk assessment, many algorithms are often trained and tested on controlled simulation datase...

Asymmetric Multi-Task Learning for Interpretable Gaze-Driven Grasping Action Forecasting.

IEEE journal of biomedical and health informatics
This work tackles the automatic prediction of grasping intention of humans observing their environment. Our target application is the assistance to people with motor disabilities and potential cognitive impairments, using assistive robotics. Our prop...