Fabian Theurl, Michael Schreinlechner, Nikolay Sappler, Michael Toifl, Theresa Dolejsi, Florian Hofer, Celine Massmann, Christian Steinbring, Silvia Komarek, Kurt Mölgg, Benjamin Dejakum, Christian Böhme, Rudolf Kirchmair, Sebastian Reinstadler, Axel Bauer
{"title":"智能手表得出的心率变异性:与心血管疾病黄金标准的正面比较。","authors":"Fabian Theurl, Michael Schreinlechner, Nikolay Sappler, Michael Toifl, Theresa Dolejsi, Florian Hofer, Celine Massmann, Christian Steinbring, Silvia Komarek, Kurt Mölgg, Benjamin Dejakum, Christian Böhme, Rudolf Kirchmair, Sebastian Reinstadler, Axel Bauer","doi":"10.1093/ehjdh/ztad022","DOIUrl":null,"url":null,"abstract":"<p><strong>Aims: </strong>We aimed to investigate the concordance between heart rate variability (HRV) derived from the photoplethysmographic (PPG) signal of a commercially available smartwatch compared with the gold-standard high-resolution electrocardiogram (ECG)-derived HRV in patients with cardiovascular disease.</p><p><strong>Methods and results: </strong>We prospectively enrolled 104 survivors of acute ST-elevation myocardial infarction, 129 patients after an ischaemic stroke, and 30 controls. All subjects underwent simultaneous recording of a smartwatch (Garmin vivoactive 4; Garmin Ltd, Olathe, KS, USA)-derived PPG signal and a high-resolution (1000 Hz) ECG for 30 min under standardized conditions. HRV measures in time and frequency domain, non-linear measures, as well as deceleration capacity (DC) were calculated according to previously published technologies from both signals. Lin's concordance correlation coefficient (<i>ρ</i><sub>c</sub>) between smartwatch-derived and ECG-based HRV markers was used as a measure of diagnostic accuracy. A very high concordance within the whole study cohort was observed for the mean heart rate (<i>ρ</i><sub>c</sub> = 0.9998), standard deviation of the averages of normal-to-normal (NN) intervals in all 5min segments (SDANN; <i>ρ</i><sub>c</sub> = 0.9617), and very low frequency power (VLF power; <i>ρ</i><sub>c</sub> = 0.9613). In contrast, detrended fluctuation analysis (DF-α1; <i>ρ</i><sub>c</sub> = 0.5919) and the square mean root of the sum of squares of adjacent NN-interval differences (rMSSD; <i>ρ</i><sub>c</sub> = 0.6617) showed only moderate concordance.</p><p><strong>Conclusion: </strong>Smartwatch-derived HRV provides a practical alternative with excellent accuracy compared with ECG-based HRV for global markers and those characterizing lower frequency components. However, caution is warranted with HRV markers that predominantly assess short-term variability.</p>","PeriodicalId":72965,"journal":{"name":"European heart journal. Digital health","volume":null,"pages":null},"PeriodicalIF":3.9000,"publicationDate":"2023-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/c0/d9/ztad022.PMC10232241.pdf","citationCount":"0","resultStr":"{\"title\":\"Smartwatch-derived heart rate variability: a head-to-head comparison with the gold standard in cardiovascular disease.\",\"authors\":\"Fabian Theurl, Michael Schreinlechner, Nikolay Sappler, Michael Toifl, Theresa Dolejsi, Florian Hofer, Celine Massmann, Christian Steinbring, Silvia Komarek, Kurt Mölgg, Benjamin Dejakum, Christian Böhme, Rudolf Kirchmair, Sebastian Reinstadler, Axel Bauer\",\"doi\":\"10.1093/ehjdh/ztad022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Aims: </strong>We aimed to investigate the concordance between heart rate variability (HRV) derived from the photoplethysmographic (PPG) signal of a commercially available smartwatch compared with the gold-standard high-resolution electrocardiogram (ECG)-derived HRV in patients with cardiovascular disease.</p><p><strong>Methods and results: </strong>We prospectively enrolled 104 survivors of acute ST-elevation myocardial infarction, 129 patients after an ischaemic stroke, and 30 controls. All subjects underwent simultaneous recording of a smartwatch (Garmin vivoactive 4; Garmin Ltd, Olathe, KS, USA)-derived PPG signal and a high-resolution (1000 Hz) ECG for 30 min under standardized conditions. HRV measures in time and frequency domain, non-linear measures, as well as deceleration capacity (DC) were calculated according to previously published technologies from both signals. Lin's concordance correlation coefficient (<i>ρ</i><sub>c</sub>) between smartwatch-derived and ECG-based HRV markers was used as a measure of diagnostic accuracy. A very high concordance within the whole study cohort was observed for the mean heart rate (<i>ρ</i><sub>c</sub> = 0.9998), standard deviation of the averages of normal-to-normal (NN) intervals in all 5min segments (SDANN; <i>ρ</i><sub>c</sub> = 0.9617), and very low frequency power (VLF power; <i>ρ</i><sub>c</sub> = 0.9613). In contrast, detrended fluctuation analysis (DF-α1; <i>ρ</i><sub>c</sub> = 0.5919) and the square mean root of the sum of squares of adjacent NN-interval differences (rMSSD; <i>ρ</i><sub>c</sub> = 0.6617) showed only moderate concordance.</p><p><strong>Conclusion: </strong>Smartwatch-derived HRV provides a practical alternative with excellent accuracy compared with ECG-based HRV for global markers and those characterizing lower frequency components. However, caution is warranted with HRV markers that predominantly assess short-term variability.</p>\",\"PeriodicalId\":72965,\"journal\":{\"name\":\"European heart journal. 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Smartwatch-derived heart rate variability: a head-to-head comparison with the gold standard in cardiovascular disease.
Aims: We aimed to investigate the concordance between heart rate variability (HRV) derived from the photoplethysmographic (PPG) signal of a commercially available smartwatch compared with the gold-standard high-resolution electrocardiogram (ECG)-derived HRV in patients with cardiovascular disease.
Methods and results: We prospectively enrolled 104 survivors of acute ST-elevation myocardial infarction, 129 patients after an ischaemic stroke, and 30 controls. All subjects underwent simultaneous recording of a smartwatch (Garmin vivoactive 4; Garmin Ltd, Olathe, KS, USA)-derived PPG signal and a high-resolution (1000 Hz) ECG for 30 min under standardized conditions. HRV measures in time and frequency domain, non-linear measures, as well as deceleration capacity (DC) were calculated according to previously published technologies from both signals. Lin's concordance correlation coefficient (ρc) between smartwatch-derived and ECG-based HRV markers was used as a measure of diagnostic accuracy. A very high concordance within the whole study cohort was observed for the mean heart rate (ρc = 0.9998), standard deviation of the averages of normal-to-normal (NN) intervals in all 5min segments (SDANN; ρc = 0.9617), and very low frequency power (VLF power; ρc = 0.9613). In contrast, detrended fluctuation analysis (DF-α1; ρc = 0.5919) and the square mean root of the sum of squares of adjacent NN-interval differences (rMSSD; ρc = 0.6617) showed only moderate concordance.
Conclusion: Smartwatch-derived HRV provides a practical alternative with excellent accuracy compared with ECG-based HRV for global markers and those characterizing lower frequency components. However, caution is warranted with HRV markers that predominantly assess short-term variability.