AIMC Topic: Workload

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EEG-Based Mental Workload Classification Method Based on Hybrid Deep Learning Model Under IoT.

IEEE journal of biomedical and health informatics
Automatically detecting human mental workload to prevent mental diseases is highly important. With the development of information technology, remote detection of mental workload is expected. The development of artificial intelligence and Internet of ...

Optimizing Human-Robot Teaming Performance through Q-Learning-Based Task Load Adjustment and Physiological Data Analysis.

Sensors (Basel, Switzerland)
The transition to Industry 4.0 and 5.0 underscores the need for integrating humans into manufacturing processes, shifting the focus towards customization and personalization rather than traditional mass production. However, human performance during t...

Classification of mental workload using brain connectivity and machine learning on electroencephalogram data.

Scientific reports
Mental workload refers to the cognitive effort required to perform tasks, and it is an important factor in various fields, including system design, clinical medicine, and industrial applications. In this paper, we propose innovative methods to assess...

User Experience Evaluation of a Spinal Surgery Robot: Workload, Usability, and Satisfaction Study.

JMIR human factors
BACKGROUND: Robotic spine surgery has continued to evolve since its US Food and Drug Administration approval in 2004, with products now including real-time video guidance and navigation during surgery. As the market for robotic surgical devices evolv...

Prediction of cognitive conflict during unexpected robot behavior under different mental workload conditions in a physical human-robot collaboration.

Journal of neural engineering
. Brain-computer interface (BCI) technology is poised to play a prominent role in modern work environments, especially a collaborative environment where humans and machines work in close proximity, often with physical contact. In a physical human rob...

Comparison of proactive and reactive interaction modes in a mobile robotic telecare study.

Applied ergonomics
Mobile robotic telepresence systems require that information about the environment, the task, and the robot be presented to a remotely located user (operator) who controls the robot for a specific task. In this study, two interaction modes, proactive...

Evaluating the performance of the cognitive workload model with subjective endorsement in addition to EEG.

Medical & biological engineering & computing
The aptitude-oriented exercises from almost all domains impose cognitive load on their operators. Evaluating such load poses several challenges owing to many factors like measurement mode and complexity, nature of the load, overloading conditions, et...

Deep learning-based metastasis detection in patients with lung cancer to enhance reproducibility and reduce workload in brain metastasis screening with MRI: a multi-center study.

Cancer imaging : the official publication of the International Cancer Imaging Society
OBJECTIVES: To assess whether a deep learning-based system (DLS) with black-blood imaging for brain metastasis (BM) improves the diagnostic workflow in a multi-center setting.

Diagnostic capabilities of artificial intelligence as an additional reader in a breast cancer screening program.

European radiology
OBJECTIVES: We aimed to evaluate the early-detection capabilities of AI in a screening program over its duration, with a specific focus on the detection of interval cancers, the early detection of cancers with the assistance of AI from prior visits, ...