BACKGROUND: Despite the increasing demands of ultra-short-term heart rate (HR) variability (HRV) for practical ambulatory applications, there have been few studies that have investigated R-R interval recording for less than 5 min for HRV analysis. It has not been extensively validated, and, currently, no normative data for ultra-short-term HRV exist. The aim of this study was to investigate the relationship between standard 5-min and ultra-short-term HRV by collecting data from a large population consisting of a wide range of age groups. MATERIALS AND METHODS: The 5-min R-R interval series were obtained from 467 healthy volunteers ranging from 8 to 69 years of age. The original R-R interval was segmented into 270, 240, 210, 180, 150, 120, 90, 60, 30, 20, and 10 s, and those HRV features most commonly reported within the literature were calculated and compared with those using the original 5-min R-R interval series. The Pearson correlation r, the p value by the Kruskal-Wallis test, and the Bland-Altman plot analysis computations were performed for each HRV variable calculated using different lengths of R-R interval series. RESULTS: For each HRV variable, the minimum length of the R-R interval required to reliably estimate the 5-min HRV was identified. The results were different for each age group: 10 s for HR, 20 s for high-frequency, 30 s for root mean square difference, 60 s for proportion of the number of interval differences of successive NN intervals greater than 50 ms divided by total number of NNs, 90 s for low-frequency, normalized low-frequency, normalized high-frequency, and low-frequency/high-frequency, 240 s for standard deviation of successive NN interval differences and time-frequency, and 270 s for very low-frequency. In addition, the reference value for short-term HRV from normal healthy subjects was also presented. CONCLUSIONS: Some HRV variables calculated from R-R interval series shorter than 5 min were well matched with those calculated from the 5-min R-R interval. Thus, ultra-short-term HRV is likely to be a good surrogate method to assess trends in HRV.
BACKGROUND: Despite the increasing demands of ultra-short-term heart rate (HR) variability (HRV) for practical ambulatory applications, there have been few studies that have investigated R-R interval recording for less than 5 min for HRV analysis. It has not been extensively validated, and, currently, no normative data for ultra-short-term HRV exist. The aim of this study was to investigate the relationship between standard 5-min and ultra-short-term HRV by collecting data from a large population consisting of a wide range of age groups. MATERIALS AND METHODS: The 5-min R-R interval series were obtained from 467 healthy volunteers ranging from 8 to 69 years of age. The original R-R interval was segmented into 270, 240, 210, 180, 150, 120, 90, 60, 30, 20, and 10 s, and those HRV features most commonly reported within the literature were calculated and compared with those using the original 5-min R-R interval series. The Pearson correlation r, the p value by the Kruskal-Wallis test, and the Bland-Altman plot analysis computations were performed for each HRV variable calculated using different lengths of R-R interval series. RESULTS: For each HRV variable, the minimum length of the R-R interval required to reliably estimate the 5-min HRV was identified. The results were different for each age group: 10 s for HR, 20 s for high-frequency, 30 s for root mean square difference, 60 s for proportion of the number of interval differences of successive NN intervals greater than 50 ms divided by total number of NNs, 90 s for low-frequency, normalized low-frequency, normalized high-frequency, and low-frequency/high-frequency, 240 s for standard deviation of successive NN interval differences and time-frequency, and 270 s for very low-frequency. In addition, the reference value for short-term HRV from normal healthy subjects was also presented. CONCLUSIONS: Some HRV variables calculated from R-R interval series shorter than 5 min were well matched with those calculated from the 5-min R-R interval. Thus, ultra-short-term HRV is likely to be a good surrogate method to assess trends in HRV.
Authors: Roger D Dias; Heather M Conboy; Jennifer M Gabany; Lori A Clarke; Leon J Osterweil; David Arney; Julian M Goldman; Giuseppe Riccardi; George S Avrunin; Steven J Yule; Marco A Zenati Journal: OR 2.0 Context Aware Oper Theaters Comput Assist Robot Endosc Clin Image Based Proced Skin Image Anal (2018) Date: 2018-10-02
Authors: Antonia V Seligowski; Julia B Merker; Adam P Swiercz; Jeanie Park; Paul J Marvar; Kerry J Ressler; Tanja Jovanovic Journal: J Psychiatr Res Date: 2020-02-26 Impact factor: 4.791
Authors: Roger D Dias; Heather M Conboy; Jennifer M Gabany; Lori A Clarke; Leon J Osterweil; George S Avrunin; David Arney; Julian M Goldman; Giuseppe Riccardi; Steven J Yule; Marco A Zenati Journal: IEEE Int Interdiscip Conf Cogn Methods Situat Aware Decis Support Date: 2018-08-02
Authors: Sven Geurts; Martijn J Tilly; Banafsheh Arshi; Bruno H C Stricker; Jan A Kors; Jaap W Deckers; Natasja M S de Groot; M Arfan Ikram; Maryam Kavousi Journal: Clin Res Cardiol Date: 2022-08-13 Impact factor: 6.138
Authors: Roger C McIntosh; Tasneem Khambaty; Maria M Llabre; Krista M Perreira; Hector M Gonzalez; Mayank M Kansal; Wassim Tarraf; Neil Schneiderman Journal: Int J Psychophysiol Date: 2021-01-30 Impact factor: 2.997
Authors: Lauren R Kennedy-Metz; Roger D Dias; Rithy Srey; Geoffrey C Rance; Heather M Conboy; Miguel E Haime; Jacquelyn A Quin; Steven J Yule; Marco A Zenati Journal: Hum Factors Date: 2020-12-16 Impact factor: 2.888