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We evaluated the value of automated analysis of cross-correlation baroreflex sensitivity (xBRS) and heart rate variability (HRV) and its relationship with clinical covariates in 13,326 participants from the multi-ethnic HELIUS study. Finger blood pressure (BP) was continuously recorded, from which xBRS, standard deviation of normal-to-normal intervals (SDNN), and squared root of mean squared successive difference between normal-to-normal intervals (RMSDD) were determined. A subset of\u00a03356 recordings\u2009&gt;\u2009300\u00a0s was used to derive the minimally required duration by comparing shortened to complete recordings, defined as intraclass correlation (ICC)\u2009&gt;\u20090.90. For xBRS and SDNN, 120\u00a0s and 180\u00a0s were required (ICC 0.93); for RMSDD, 60\u00a0s (ICC 0.94) was sufficient. We included 10,252 participants (median age 46\u00a0years, 54% women) with a recording\u2009&gt;\u2009180\u00a0s for the regression. xBRS, SDNN, and RMSDD decreased linearly up to 50\u00a0years\u00a0of age. For xBRS, there was a signification interaction with sex, with for every 10\u00a0years a decrease of 4.3\u00a0ms\/mmHg (95%CI 4.0\u20134.6) for men and 5.9\u00a0ms\/mmHg (95%CI 5.6\u20136.1) for women. Using splines, we observed sex-dependent nonlinearities in the relation with BP, waist-to-hip-ratio, and body mass index. Future studies can help unravel the dynamics of these relations and assess their predictive value.<\/jats:p>\n                <jats:p><jats:bold>Graphical Abstract<\/jats:bold><\/jats:p>\n                <jats:p>Panel 1 depicts automatic analysis and filtering of finger BP recordings, panel 2 depicts computation of xBRS from interpolated beat to beat data of systolic BP and interbeat interval, and (IBI) SDNN and RMSDD are computed directly from the filtered IBI dataset. Panel 3 depicts the results of large-scale analysis and relation of xBRS with age, sex, blood pressure and body mass index.<\/jats:p>","DOI":"10.1007\/s11517-023-02768-4","type":"journal-article","created":{"date-parts":[[2023,1,23]],"date-time":"2023-01-23T00:02:17Z","timestamp":1674432137000},"page":"1183-1191","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Automated analysis of finger blood pressure recordings provides insight in determinants of baroreflex sensitivity and heart rate variability\u2014the HELIUS study"],"prefix":"10.1007","volume":"61","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8572-8751","authenticated-orcid":false,"given":"D.","family":"Collard","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"B. E.","family":"Westerhof","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J. 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