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紧张状态下累积性疲劳的短时心电特征分析
陆嘉文1,李川涛2,陈始圆3,王志1,许金芳4,谢长勇5*
0
(1. 上海理工大学健康科学与工程学院, 海军军医大学(第二军医大学)联合培养班, 上海 200093;
2. 海军军医大学(第二军医大学)海军特色医学中心航空生理心理训练队, 上海 200433;
3. 海军军医大学(第二军医大学)海军特色医学中心航空医学研究室, 上海 200433;
4. 海军军医大学(第二军医大学)卫生勤务学系军队卫生统计学教研室, 上海 200433;
5. 海军军医大学(第二军医大学)海军特色医学中心医研部, 上海 200433
*通信作者)
摘要:
目的 探索是否存在一种可作为累积性疲劳生物标志物的短时心电特征。方法 动态跟踪上海理工大学14名健康被试(男、女各7人,年龄为19~23岁)在参加全国大学生电子设计竞赛期间的心电信号,收集被试的主观疲劳量表评分与睡眠时长,并计算心率变异性、心电熵值、高低频段功率值、平均RR间期等13项心电特征。使用Wilcoxon符号秩检验对被试清醒与疲劳时的心电特征差值进行比较。结果 被试在缺少睡眠的情况下主观疲劳程度加深,短时心电特征的高频段功率值、高/低频段功率值比值和庞加莱图长半轴在区分清醒与疲劳状态时有统计学意义(P均<0.05)。结论 某些常见的短时心电特征可作为检测累积性疲劳的生物标志物。
关键词:  累积性疲劳  短时心电特征  自评疲劳程度  生物标志物
DOI:10.16781/j.CN31-2187/R.20220380
投稿时间:2022-05-06修订日期:2023-02-23
基金项目:海装航空局装备科研项目(HJ20172A02133),国家自然科学基金青年科学基金(82101970).
Analysis of short-term electrocardiogram characteristics of cumulative fatigue under stress
LU Jia-wen1,LI Chuan-tao2,CHEN Shi-yuan3,WANG Zhi1,XU Jin-fang4,XIE Chang-yong5*
(1. Co-cultivation Class of Naval Medical University(Second Military Medical University), School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;
2. Aviation Physiological and Psychological Training Team, Naval Medical Center, Naval Medical University(Second Military Medical University), Shanghai 200433, China;
3. Department of Aviation Medicine, Naval Medical Center, Naval Medical University(Second Military Medical University), Shanghai 200433, China;
4. Department of Military Health Statistics, Faculty of Medical Services, Naval Medical University(Second Military Medical University), Shanghai 200433, China;
5. Medical Research Department, Naval Medical Center, Naval Medical University(Second Military Medical University), Shanghai 200433, China
*Corresponding author)
Abstract:
Objective To explore whether there are short-term electrocardiogram characteristics which may serve as a biomarker for cumulative fatigue. Methods The electrocardiogram signals of 14 students (7 males and 7 females, with age ranging 19-23 years) from the University of Shanghai for Science and Technology, who were participating in the national electronic design competition for college students, were dynamically tracked. The scores of subjective fatigue scale and sleep duration were collected, and 13 characteristic electrocardiogram items were calculated, including heart rate variability, electrocardiogram entropy, high and low frequency values, and average RR interval. The difference between the electrocardiogram items was compared using the Wilcoxon signed-rank test between awakening and fatigue states. Results The subjective fatigue level was increased during lack of sleep, and the high frequency value of short-term electrocardiogram characteristics, the ratio of high to low frequency values and the Poincaré plot SD2 were significantly different between awakening and fatigue states (all P<0.05). Conclusion Some short-term electrocardiogram characteristics could be used for the detection of cumulative fatigue.
Key words:  cumulative fatigue  short-term electrocardiogram characteristics  self-rated fatigue level  biomarkers