AI Medical Compendium Journal:
Ergonomics

Showing 41 to 47 of 47 articles

A machine learning approach to detect changes in gait parameters following a fatiguing occupational task.

Ergonomics
The purpose of this study is to provide a method for classifying non-fatigued vs. fatigued states following manual material handling. A method of template matching pattern recognition for feature extraction ($1 Recognizer) along with the support vect...

Using Neural Networks to predict HFACS unsafe acts from the pre-conditions of unsafe acts.

Ergonomics
Human Factors Analysis and Classification System (HFACS) is based upon Reason's organizational model of human error which suggests that there is a 'one to many' mapping of condition tokens (HFACS level 2 psychological precursors) to unsafe act tokens...

Human interaction with robotic systems: performance and workload evaluations.

Ergonomics
We first tested the effect of differing tactile informational forms (i.e. directional cues vs. static cues vs. dynamic cues) on objective performance and perceived workload in a collaborative human-robot task. A second experiment evaluated the influe...

Impact of three task demand factors on simulated unmanned system intelligence, surveillance, and reconnaissance operations.

Ergonomics
The present study investigated how three task demand factors influenced performance, subjective workload and stress of novice intelligence, surveillance, and reconnaissance operators within a simulation of an unmanned ground vehicle. Manipulations we...

Introducing RiskSOAP to communicate the distributed situation awareness of a system about safety issues: an application to a robotic system.

Ergonomics
This paper introduces the RiskSOAP ('RiskSOAP' is the abbreviation for Risk SituatiOn Awareness Provision.) indicator to measure the capability of a complex socio-technical system to provide its agents with situation awareness (SA) about the presence...

Expanding the occupational health methodology: A concatenated artificial neural network approach to model the burnout process in Chinese nurses.

Ergonomics
UNLABELLED: Artificial neural networks are sophisticated modelling and prediction tools capable of extracting complex, non-linear relationships between predictor (input) and predicted (output) variables. This study explores this capacity by modelling...

We have to go back, back to the future! Reflecting on 75 years of human factors in the UK to shape a future of responsible artificial intelligence innovation.

Ergonomics
The origins of Human Factors (HF) are rooted in the Second World War. It is a sign of the times that 75 years on from the formation of the Ergonomics Research Society, discussions occur as to whether Artificial Intelligence (AI) could/should be capab...