BACKGROUND: The stress score (SS) and sympathetic-parasympathetic ratio (SPS) are heart rate variability (HRV) indices that have recently gained attention for monitoring autonomic balance in athletes. However, they are calculated from a Poincaré plot which is more complex than time-domain metrics such as the root mean square of successive normal-to-normal interval differences (RMSSD) or the standard deviation of normal-to-normal intervals (SDNN). Additionally, the SS and SPS are calculated from standardized procedures that require a 5-minute recording time that follows a 5-minute stabilization period. On the other hand, ultra-short (US) recordings that require only a 1-minute stabilization period followed by a 1-minute recording period have gained popularity for acquiring HRV in field settings. The purpose of this study was to determine the validity of a modified calculation of SS (SSMOD) and SPS (SPSMOD) from US recordings of RMSSD and SDNN. METHODS: NCAA Division-III male athletes were recruited for this study (n = 23, 21.43 ± 2.17 yrs.). Resting HRV was assessed via electrocardiography (ECG) with a modified Lead II electrode placement for 10 minutes while each participant assumed a supine position. Poincare plot analysis was performed on the last 5-minutes of the ECG, with the first 5-minute segment considered as stabilization. From the plot, the standard deviation of short- (SD1) and long-term (SD2) R-R interval variability were recorded. SS was calculated by taking the inverse function of SD2 and multiplying it by 1000, whereas SPS was calculated by dividing SS by SD1. For the modified US approach, RMSSD and SDNN were calculated from a 1-minute segment of the ECG, following a 1-minute stabilization period. SSMOD was calculated by taking the inverse function of SDNN and multiplying it by 1000, while the calculation of SPSMOD came from dividing SSMOD by RMSSD. RESULTS: The mean ± SD for SS was 14.74 ± 8.02 ms, for SPS was 0.55 ± 0.93, for SSMOD was 18.56 ± 10.91 ms, and SPSMOD was 0.61 ± 1.13. Pearson’s correlation procedures showed strong and significant correlations between SS and SSMOD (r = 0.93) and between SPS and SPSMOD (r = 0.98). DISCUSSION: These findings support the use of a modified SS and SPS calculation from US time-domain metrics during resting conditions. Because of the field-applicability of US time-domain HRV metrics, the SSMOD and SPSMOD indices could become highly useful in monitoring athlete training load and recovery status.

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