Novel Calculation Of Modified Stress Score And Sympathetic-parasympathetic Ratio From Ultra-short Time-domain Methods

PURPOSE: Stress score (SS) and sympathetic-parasympathetic ratio (SPS) are heart rate variability (HRV) indices that have gained attention for monitoring autonomic balance in athletes. 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, they are calculated from standardized procedures that require a 5-minute stabilization period followed by 5-minute recordings. Ultra-short (US) recordings require only a 1-minute stabilization period and a 1-minute recording period. They 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 time-domain metrics. 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 placement for 10 minutes in a supine position. Poincare plot analysis was performed on the last 5-minutes of the ECG. From the plot, the standard deviation of short-term (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. 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). CONCLUSIONS: 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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Journal
Medicine & Science in Sports & Exercise
Published
2024-09-16
DOI
https://doi.org/10.1249/01.mss.0001059912.78342.db
Primary Topic
Infrared Thermography in Medicine
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article
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article

Novel Calculation Of Modified Stress Score And Sympathetic-parasympathetic Ratio From Ultra-short Time-domain Methods

Ali M. Mohammadnabi, A Fields, Michael R. Esco
Medicine & Science in Sports & Exercise
Infrared Thermography in Medicine
article

Novel Calculation Of Modified Stress Score And Sympathetic-parasympathetic Ratio From Ultra-short Time-domain Methods

Ali M. Mohammadnabi, A Fields, Michael R. Esco
article en

Abstract

PURPOSE: Stress score (SS) and sympathetic-parasympathetic ratio (SPS) are heart rate variability (HRV) indices that have gained attention for monitoring autonomic balance in athletes. 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, they are calculated from standardized procedures that require a 5-minute stabilization period followed by 5-minute recordings. Ultra-short (US) recordings require only a 1-minute stabilization period and a 1-minute recording period. They 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 time-domain metrics. 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 placement for 10 minutes in a supine position. Poincare plot analysis was performed on the last 5-minutes of the ECG. From the plot, the standard deviation of short-term (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. 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). CONCLUSIONS: 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.

Medicine & Science in Sports & ExerciseVol. 56(10S)
University of Alabama (US)
Openalex Percentile: Top 74%
Infrared Thermography in Medicine
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