Biosignals in Human Factors Research for Heavy Equipment Operators: A Review of Available Methods and Their Feasibility in Laboratory and Ambulatory Studies

Heavy equipment operation is a responsible and difficult task causing mental workload on a human operator and exposing the operator to a range of harmful factors. Human factors and ergonomics in heavy equipment design have traditionally been focused on anthropometry and questionnaires. More advanced...

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Bibliographic Details
Published in:IEEE access 2021, Vol.9, p.97466-97482
Main Authors: Hekmatmanesh, Amin, Zhidchenko, Victor, Kauranen, Kari, Siitonen, Kaija, Handroos, Heikki, Soutukorva, Sari, Kilpelainen, Asko
Format: Article
Language:English
Subjects:
Algorithms
Anthropometry
Biosensors
biosignal processing
Ergonomics
Feasibility
Heating systems
Human factors
human factors and heavy equipment operator ergonomics
Human factors research
Human stress detection
Identification methods
Laboratories
Operators
pattern recognition
Safety
Simulators
Stress
Task analysis
Vibrations
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Summary:Heavy equipment operation is a responsible and difficult task causing mental workload on a human operator and exposing the operator to a range of harmful factors. Human factors and ergonomics in heavy equipment design have traditionally been focused on anthropometry and questionnaires. More advanced techniques involving biosignal measurements were not applied to heavy equipment, mainly due to the diversity of real working conditions that were hard to reproduce in a laboratory environment and that prevented ambulatory studies. Recent advances in wearable biosensors and real-time simulators produce the capability of using biosignals for improving the ergonomics of heavy equipment operation. The present paper reviews the use of biosignals in human factors and the ergonomics of heavy machines by focusing on stress detection for the last ten years. The aim of the paper is analyzing the previous implemented algorithms to find a set of biosignals and methods of stress identification that could be suitable for identifying stress in heavy equipment operators both in laboratory and ambulatory studies. The conclusion emphasizes successful stress identification methods and a combination of the algorithms from different studies that facilitate the use of heavy equipment operator's applications. Also, feasible methods and directions for future research are considered.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2021.3092516