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Monitoring Fatigue Status with HRV Measures in Elite Athletes: An Avenue Beyond RMSSD?

机译:使用HRV措施监测优秀运动员的疲劳状况:超越RMSSD的途径?

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Among the tools proposed to assess the athlete's “fatigue,” the analysis of heart rate variability (HRV) provides an indirect evaluation of the settings of autonomic control of heart activity. HRV analysis is performed through assessment of time-domain indices, the square root of the mean of the sum of the squares of differences between adjacent normal R-R intervals (RMSSD) measured during short (5 min) recordings in supine position upon awakening in the morning and particularly the logarithm of RMSSD (LnRMSSD) has been proposed as the most useful resting HRV indicator. However, if RMSSD can help the practitioner to identify a global “fatigue” level, it does not allow discriminating different types of fatigue. Recent results using spectral HRV analysis highlighted firstly that HRV profiles assessed in supine and standing positions are independent and complementary; and secondly that using these postural profiles allows the clustering of distinct sub-categories of “fatigue.” Since, cardiovascular control settings are different in standing and lying posture, using the HRV figures of both postures to cluster fatigue state embeds information on the dynamics of control responses. Such, HRV spectral analysis appears more sensitive and enlightening than time-domain HRV indices. The wealthier information provided by this spectral analysis should improve the monitoring of the adaptive training-recovery process in athletes.
机译:在提议用来评估运动员“疲劳”的工具中,对心率变异性(HRV)的分析提供了对心脏活动自主控制设置的间接评估。 HRV分析是通过评估时域指数进行的,即在早晨醒来的短卧(5分钟)录音期间测量的相邻正常RR间隔(RMSSD)之间的差平方和的平均值的平方根尤其是RMSSD的对数(LnRMSSD)已被建议作为最有用的静止HRV指标。但是,如果RMSSD可以帮助从业人员确定总体的“疲劳”水平,则不允许区分不同类型的疲劳。使用频谱HRV分析的最新结果首先强调,仰卧位和站立位评估的HRV谱独立且互补。其次,使用这些姿势轮廓可以将“疲劳”的不同子类别进行聚类。由于心血管控制的设置在站立姿势和卧姿中是不同的,因此使用两种姿势的HRV数字对疲劳状态进行聚类可以将信息嵌入控制响应的动力学信息中。这样,HRV频谱分析似乎比时域HRV指数更为灵敏和启发。通过这种频谱分析提供的更丰富的信息应该改善对运动员的适应性训练-恢复过程的监控。

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