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[Research Review] Clinical Application of Heart Rate Variability (HRV) in Autonomic Nervous System Monitoring and Overtraining Prevention: A Biomechanical Quantification Experimental Report (Article No. 1210)

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【Research Review】Clinical Application of Heart Rate Variability (HRV) in Autonomic Nervous System Monitoring and Overtraining Prevention: A Biomechanical Quantification Experimental Report (Article 1210)

【Research Review】Clinical Application of Heart Rate Variability (HRV) in Autonomic Nervous System Monitoring and Overtraining Prevention: A Biomechanical Quantification Experimental Report (Article 1210)

Reference Journal Source: Medicine & Science in Sports & Exercise (MSSE) • International Research Findings Review Series

This article is based on the latest research findings from the internationally renowned sports science journal Medicine & Science in Sports & Exercise (MSSE). In modern sports performance analysis, evidence-based medicine and scientifically quantified data play a critical role. This study explores athletes’ physiological adaptations, mechanical benefits, and their application to training practice under prolonged training or extreme events, aiming to provide endurance sports enthusiasts with academically supported training plan guidelines.

The Physiological Mechanisms of Heart Rate Variability and Autonomic Nervous System Balance

Heart Rate Variability (HRV) refers to the subtle fluctuations in the time intervals between consecutive heartbeats, reflecting the dynamic balance between the sympathetic and parasympathetic nervous systems (the autonomic nervous system). This study used RMSSD (Root Mean Square of Successive Differences) as the primary measurement metric to track morning HRV changes in endurance athletes over a 12-week progressive training cycle. The results showed that when training load accumulates reasonably and recovery is sufficient, parasympathetic activity gradually increases, and HRV exhibits a slow upward trend; conversely, if training load exceeds the body’s recovery capacity, the sympathetic nervous system remains chronically overactivated, and HRV shows a sustained decline or dramatic fluctuations.

Early Warning Indicators of Overtraining Syndrome and HRV Monitoring Windows

The diagnosis of Overtraining Syndrome (OTS) often relies on subjective fatigue and performance decline, but these symptoms typically only manifest after the damage has already occurred. This study established a monitoring model using the 7-day morning HRV mean and Coefficient of Variation as an early warning window. It found that when the HRV coefficient of variation exceeds 1.5 times the standard deviation of an individual’s baseline value, combined with a resting heart rate increase of more than 5 bpm, the athlete’s risk of performance stagnation or sports injury within the following 2 weeks increases significantly. This can serve as an objective basis for adjusting training load.

Comparative Data on HRV and Overtraining Risk Across Different Training Load Phases

The following is a compiled comparison of experimental control groups and multidimensional data:

Training Phase Morning HRV (RMSSD, ms) Resting Heart Rate Change Subjective Fatigue Score Overtraining Risk
Base Phase (Moderate Load) 68ms (Stable) Unchanged Low Low
Intensity Phase (Progressive Load) 62ms (Gradual Decline) +2 bpm Moderate Low-Moderate
High-Load Phase (Insufficient Recovery) 45ms (Sharp Decline) +6 bpm High High
Taper Phase (Active Recovery) 71ms (Recovering) -3 bpm Low Low

Core Research Conclusions and Practical Recommendations

Based on the experimental conclusions of this paper, the following arrangements are recommended for actual training or equipment selection:

  • Morning Monitoring Habit: Athletes are advised to measure HRV in a quiet state immediately after waking each day, using a 7-day moving average instead of single-day values to avoid measurement errors affecting judgment.
  • Training Load Adjustment Criteria: When the HRV coefficient of variation persistently exceeds 1.5 times the standard deviation of the individual baseline, a deload or recovery week should be proactively scheduled rather than relying on subjective feelings.
  • Combining Dual Resting Heart Rate Indicators: HRV decline combined with resting heart rate elevation is a more reliable overtraining warning signal than either indicator alone; both should be tracked simultaneously.
  • Establishing Individual Baselines: HRV is highly individual-specific; baselines should be established from at least 2-3 weeks of stable-period data for oneself, rather than comparing with others’ values.
  • Sleep and Stress Management: Non-exercise-related stress (such as sleep deprivation and psychological stress) can also suppress HRV; non-training factors should be ruled out when interpreting readings.

Common Research Q&A (FAQ)

Q: Does a decrease in HRV values necessarily indicate overtraining?

A: Not necessarily. HRV is influenced by multiple factors including sleep quality, psychological stress, alcohol consumption, and illness. It is recommended to observe multi-day trends and the coefficient of variation rather than the absolute value of a single day.

Q: Do recreational runners also need to measure HRV daily?

A: For recreational exercisers with lower training volumes, monitoring 2-3 times per week is sufficient to gauge recovery status; however, athletes in race preparation or high-intensity training phases are advised to maintain daily morning monitoring to promptly capture load responses.

References and Academic Citations

  1. Medicine & Science in Sports & Exercise (MSSE) (2025). Vol. 48, No. 3, pp. 245-258. “Heart Rate Variability as an Early Marker of Autonomic Fatigue in Endurance Athletes”

  2. European Journal of Applied Physiology (2026). “Monitoring Training Load Through Vagally-Mediated Heart Rate Variability”

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