AIMC Topic: Task Performance and Analysis
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Classification algorithms trained on simple (symmetric) lifting data perform poorly in predicting hand loads during complex (free-dynamic) lifting tasks.
Applied ergonomics
Dec 10, 2024
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
Dec 5, 2024
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...
Predefined-Time Convergent Kinematic Control of Robotic Manipulators With Unknown Models Based on Hybrid Neural Dynamics and Human Behaviors.
IEEE transactions on neural networks and learning systems
Dec 2, 2024
This article proposes a model-free kinematic control method with predefined-time convergence for robotic manipulators with unknown models. The predefined-time convergence property guarantees that the regulation task can be finished by robotic manipul...
Learning performance and physiological feedback-based evaluation for human-robot collaboration.
Applied ergonomics
Nov 28, 2024
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...
HuBar: A Visual Analytics Tool to Explore Human Behavior Based on fNIRS in AR Guidance Systems.
IEEE transactions on visualization and computer graphics
Nov 25, 2024
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...
Assessing operator stress in collaborative robotics: A multimodal approach.
Applied ergonomics
Nov 16, 2024
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...
Human-Robot Collaboration With a Corrective Shared Controlled Robot in a Sanding Task.
Human factors
Aug 8, 2024
OBJECTIVE: Physical and cognitive workloads and performance were studied for a corrective shared control (CSC) human-robot collaborative (HRC) sanding task.
Single-Task and Dual-Task Gait Performance After Sport-Related Concussion: A Machine Learning Statistical Approach.
Sports health
Aug 7, 2024
BACKGROUND: This study evaluated 2 different dual-task (DT) conditions during tandem gait (TG) to predict sport-related concussion (SRC) diagnosis.
Cognitive and behavioral markers for human detection error in AI-assisted bridge inspection.
Applied ergonomics
Jul 16, 2024
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
Jul 9, 2024
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...
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