College of Engineering, South China Agricultural University, Wushan Road, Tianhe District, Guangzhou, 510642, China.
Guangdong Laboratory for Lingnan Modern Agriculture, Wushan Road, Tianhe District, Guangzhou, 510642, China.
Sci Rep. 2022 Mar 22;12(1):4858. doi: 10.1038/s41598-022-08705-z.
In recent years, fatigue has become an important issue in modern life that cannot be ignored, especially in some special occupations. Agricultural workers are high-risk occupations that, under fatigue conditions over a long period, will cause health problems. In China, since very few studies have focused on the fatigue state of agricultural workers, we were interested in using electrocardiogram (ECG) signals to analyze the fatigue state of agricultural workers. Healthy agricultural workers were randomly recruited from hilly orchards in South China. Through the field experiment, 130 groups of 5-min interval ECG signals were collected, and we analyzed the ECG signal by HRV. The time domain (meanHR, meanRR, SDNN, RMSSD, SDSD, PNN20, PNN50 and CV), frequency domain (VLF percent, LF percent, HF percent, LF norm, HF norm and LF/HF) and nonlinear parameters (SD1, SD2, SD1/SD2 and sample entropy) were calculated and Spearman correlation coefficient analysis and Mann-Whitney U tests were performed on each parameter for further analysis. For all subjects, nine parameters were slightly correlated in nonfatigue and fatigue state. Six parameters were significantly increased and ten HRV parameters were significantly decreased compared the nonfatigue state. As for males, fifteen parameters were significantly different, and for females, eighteen parameters were significantly different. In addition, the probability density functions of SDNN, SDSD, VLF%, HFnorm and LF/HF were significantly different in nonfatigue and fatigue state for different genders, and the nonlinear parameters become more discrete compared the nonfatigue state. Finally, we obtained the most suitable parameters, which reflect the fatigue characteristics of orchard workers under different genders. The results have instructional significance for identifying fatigue in orchard workers and provide a convincing and valid reference for clinical diagnosis.
近年来，疲劳已成为现代生活中一个不容忽视的重要问题，尤其是在一些特殊职业中。农业工人是高风险职业，如果长期处于疲劳状态，会导致健康问题。在中国，由于很少有研究关注农业工人的疲劳状态，我们有兴趣使用心电图（ECG）信号来分析农业工人的疲劳状态。我们从华南丘陵果园中随机招募了健康的农业工人。通过现场实验，采集了 130 组 5 分钟间隔的 ECG 信号，并通过 HRV 对 ECG 信号进行了分析。计算了时域（平均心率、平均 RR、SDNN、RMSSD、SDSD、PNN20、PNN50 和 CV）、频域（VLF 百分比、LF 百分比、HF 百分比、LF 正常、HF 正常和 LF/HF）和非线性参数（SD1、SD2、SD1/SD2 和样本熵），并对每个参数进行了 Spearman 相关系数分析和 Mann-Whitney U 检验，以进一步分析。对于所有受试者，在非疲劳和疲劳状态下，有九个参数存在轻微相关性。与非疲劳状态相比，有六个参数显著增加，十个 HRV 参数显著降低。对于男性，有十五个参数有显著差异，对于女性，有十八个参数有显著差异。此外，SDNN、SDSD、VLF%、HFnorm 和 LF/HF 的概率密度函数在不同性别之间的非疲劳和疲劳状态下存在显著差异，与非疲劳状态相比，非线性参数变得更加离散。最后，我们得到了最适合的参数，这些参数反映了不同性别果园工人的疲劳特征。这些结果对于识别果园工人的疲劳具有指导意义，并为临床诊断提供了令人信服和有效的参考。
