Evaluation of tractor driving vibration fatigue based on multiple physiological parameters.

The vibration generated by tractor field operations will seriously affect the comfort and health of the driver. The low frequency vibration generated by the engine and ground excitation is similar to the natural frequency of human organs. Long term operation in this environment will resonate with th...

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Autores principales:	Ruitao Gao, Huachao Yan, Zhou Yang
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/db8ea1b180ad465ba4fcc07e6c7edd8d
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spelling	oai:doaj.org-article:db8ea1b180ad465ba4fcc07e6c7edd8d2021-12-02T20:07:02ZEvaluation of tractor driving vibration fatigue based on multiple physiological parameters.1932-620310.1371/journal.pone.0254636https://doaj.org/article/db8ea1b180ad465ba4fcc07e6c7edd8d2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0254636https://doaj.org/toc/1932-6203The vibration generated by tractor field operations will seriously affect the comfort and health of the driver. The low frequency vibration generated by the engine and ground excitation is similar to the natural frequency of human organs. Long term operation in this environment will resonate with the organs and affect drivers' health. To investigate this possibility, in this paper we carried out a collection experiment of human physiological indicators relevant to vibration fatigue. Four physiological signals of surface electromyography, skin electricity, skin temperature, and photoplethysmography signal were collected while the subjects experienced vibration. Several features of physiological signals as well as the law of signal features changing with fatigue are studied. The test results show that with the increase of human fatigue, the overall physiological parameters show the following trends: The median frequency of the human body surface electromyography and the slope of skin surface temperature decreases, the value of skin conductivity and the mean value of the photoplethysmography signal increases. Furthermore, this paper proposes a vibration comfort evaluation method based on multiple physiological parameters of the human body. An artificial neural network model is trained with test samples, and the prediction accuracy rate reaches 88.9%. Finally, the vibration conditions are changed by the shock-absorbing suspension of a tractor, verifying the effectiveness of the physiological signal changing with the vibration of the human body. The established prediction model can also be used to objectively reflect the discomfort of the human body under different working conditions and provide a basis for structural design optimization.Ruitao GaoHuachao YanZhou YangPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 7, p e0254636 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Ruitao Gao Huachao Yan Zhou Yang Evaluation of tractor driving vibration fatigue based on multiple physiological parameters.
description	The vibration generated by tractor field operations will seriously affect the comfort and health of the driver. The low frequency vibration generated by the engine and ground excitation is similar to the natural frequency of human organs. Long term operation in this environment will resonate with the organs and affect drivers' health. To investigate this possibility, in this paper we carried out a collection experiment of human physiological indicators relevant to vibration fatigue. Four physiological signals of surface electromyography, skin electricity, skin temperature, and photoplethysmography signal were collected while the subjects experienced vibration. Several features of physiological signals as well as the law of signal features changing with fatigue are studied. The test results show that with the increase of human fatigue, the overall physiological parameters show the following trends: The median frequency of the human body surface electromyography and the slope of skin surface temperature decreases, the value of skin conductivity and the mean value of the photoplethysmography signal increases. Furthermore, this paper proposes a vibration comfort evaluation method based on multiple physiological parameters of the human body. An artificial neural network model is trained with test samples, and the prediction accuracy rate reaches 88.9%. Finally, the vibration conditions are changed by the shock-absorbing suspension of a tractor, verifying the effectiveness of the physiological signal changing with the vibration of the human body. The established prediction model can also be used to objectively reflect the discomfort of the human body under different working conditions and provide a basis for structural design optimization.
format	article
author	Ruitao Gao Huachao Yan Zhou Yang
author_facet	Ruitao Gao Huachao Yan Zhou Yang
author_sort	Ruitao Gao
title	Evaluation of tractor driving vibration fatigue based on multiple physiological parameters.
title_short	Evaluation of tractor driving vibration fatigue based on multiple physiological parameters.
title_full	Evaluation of tractor driving vibration fatigue based on multiple physiological parameters.
title_fullStr	Evaluation of tractor driving vibration fatigue based on multiple physiological parameters.
title_full_unstemmed	Evaluation of tractor driving vibration fatigue based on multiple physiological parameters.
title_sort	evaluation of tractor driving vibration fatigue based on multiple physiological parameters.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/db8ea1b180ad465ba4fcc07e6c7edd8d
work_keys_str_mv	AT ruitaogao evaluationoftractordrivingvibrationfatiguebasedonmultiplephysiologicalparameters AT huachaoyan evaluationoftractordrivingvibrationfatiguebasedonmultiplephysiologicalparameters AT zhouyang evaluationoftractordrivingvibrationfatiguebasedonmultiplephysiologicalparameters
_version_	1718375332704157696

Evaluation of tractor driving vibration fatigue based on multiple physiological parameters.

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