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Vibration comfort assessment of tractor drivers based on sEMG and vibration signals.

Authors :
Huang, Qingyang
Gao, Mengyu
Guo, Mingyang
Wei, Yuning
Zhang, Jingyuan
Jin, Xiaoping
Source :
Computer Methods in Biomechanics & Biomedical Engineering. Oct2024, Vol. 27 Issue 13, p1875-1892. 18p.
Publication Year :
2024

Abstract

In order to comprehensively evaluate the driver's vibration comfort under different vibration conditions, eighteen subjects were required to drive a tractor at different speeds on field and asphalt roads respectively in the real vehicle experiment. The sEMG signals and vibration acceleration signals of the subjects were recorded. And the time-frequency domain analysis of sEMG signals and acceleration signals were used to determine the relationship among the characteristic indexes, tractor speed and road surfaces. The relevance analysis showed that there was a significant correlation between the integral electromyography (iEMG) and median frequency (MF) of the middle scalene muscle, erector spinae muscle and gastrocnemius muscle, the RMS of weighted acceleration (aw) of the neck, waist and legs, and the subjective comfort feelings. It was proven that the tractor speed had a significant impact on human body vibration based on the ANOVA result (p < 0.05). With the increase of running speed, the time domain indexes of sEMG signals including iEMG, RMS and the vibration acceleration signals of the testing body parts increased significantly, while the amplitudes of frequency domain indexes decreased. Therefore, a quantitative regression evaluation model for the comfort of the neck, waist and legs integrating the sEMG and vibration signals was established, and its relative errors were 5.05, 4.38 and 6.12% respectively. This proposed assessment model can combine characteristics of the partial and overall vibration response of human body effectively, predict the tractor driver's vibration comfort accurately, provide a theoretical basis for the evaluation of tractor cab vibration comfort. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10255842
Volume :
27
Issue :
13
Database :
Academic Search Index
Journal :
Computer Methods in Biomechanics & Biomedical Engineering
Publication Type :
Academic Journal
Accession number :
179686418
Full Text :
https://doi.org/10.1080/10255842.2023.2263126