dorsal/arxiv
View SchemaDemonstration of Circadian Rhythm in Heart Rate Turbulence using Novel Application of Correlator Functions
| Authors | Mari Watanabe, Mark Alford, Raphael Schneider, Axel Bauer, Petra Barthel, Phyllis Stein, Georg Schmidt |
|---|---|
| Categories | |
| ArXiv ID | physics/0612067 |
| URL | https://arxiv.org/abs/physics/0612067 |
Abstract
Background: It has been difficult to demonstrate circadian rhythm in the two parameters of heart rate turbulence, turbulence onset (TO) and turbulence slope (TS). Objective: To devise a new method for detecting circadian rhythm in noisy data, and apply it to selected Holter recordings from two post-myocardial infarction databases, Cardiac Arrhythmia Suppression Trial (CAST, n=684) and Innovative Stratification of Arrhythmic Risk (ISAR, n=327). Methods: For each patient, TS and TO were calculated for each hour with >4 VPCs. An autocorrelation function Corr(Delta t) = <TS(t) TS(t+Delta t)> was then calculated, and averaged over all patients. Positive Corr(Delta t) indicates that TS at a given hour and Delta t hours later are similar. TO was treated likewise. Simulations and mathematical analysis showed that circadian rhythm required Corr(Delta t) to have a U-shape consisting of positive values near Delta t=0 and 23, and negative values for intermediate Delta t. Significant deviation of Corr(Delta t) from the correlator function of pure noise was evaluated as a chi-squared value. Results: Circadian patterns were not apparent in hourly averages of TS and TO plotted against clock time, which had large error bars. Their correlator functions, however, produced chi-squared values of ~10 in CAST (both p<0.0001) and ~3 in ISAR (both p<0.0001), indicating presence of circadian rhythmicity. Conclusion: Correlator functions may be a powerful tool for detecting presence of circadian rhythms in noisy data, even with recordings limited to 24 hours.
{
"annotation_id": "03e05d0c-d4dd-47ed-8afa-eaea4dacf187",
"date_created": "2026-03-02T18:01:14.742000Z",
"date_modified": "2026-03-02T18:01:14.742000Z",
"file_hash": "5909cbb97681d5b7a6996e7178933d775c639c93218a431f66acea0596cce9de",
"private": false,
"record": {
"abstract": "Background: It has been difficult to demonstrate circadian rhythm in the two\nparameters of heart rate turbulence, turbulence onset (TO) and turbulence slope\n(TS).\n Objective: To devise a new method for detecting circadian rhythm in noisy\ndata, and apply it to selected Holter recordings from two post-myocardial\ninfarction databases, Cardiac Arrhythmia Suppression Trial (CAST, n=684) and\nInnovative Stratification of Arrhythmic Risk (ISAR, n=327).\n Methods: For each patient, TS and TO were calculated for each hour with \u003e4\nVPCs. An autocorrelation function Corr(Delta t) = \u003cTS(t) TS(t+Delta t)\u003e was\nthen calculated, and averaged over all patients. Positive Corr(Delta t)\nindicates that TS at a given hour and Delta t hours later are similar. TO was\ntreated likewise. Simulations and mathematical analysis showed that circadian\nrhythm required Corr(Delta t) to have a U-shape consisting of positive values\nnear Delta t=0 and 23, and negative values for intermediate Delta t.\nSignificant deviation of Corr(Delta t) from the correlator function of pure\nnoise was evaluated as a chi-squared value.\n Results: Circadian patterns were not apparent in hourly averages of TS and TO\nplotted against clock time, which had large error bars. Their correlator\nfunctions, however, produced chi-squared values of ~10 in CAST (both p\u003c0.0001)\nand ~3 in ISAR (both p\u003c0.0001), indicating presence of circadian rhythmicity.\n Conclusion: Correlator functions may be a powerful tool for detecting\npresence of circadian rhythms in noisy data, even with recordings limited to 24\nhours.",
"arxiv_id": "physics/0612067",
"authors": [
"Mari Watanabe",
"Mark Alford",
"Raphael Schneider",
"Axel Bauer",
"Petra Barthel",
"Phyllis Stein",
"Georg Schmidt"
],
"categories": [
"physics.med-ph"
],
"title": "Demonstration of Circadian Rhythm in Heart Rate Turbulence using Novel Application of Correlator Functions",
"url": "https://arxiv.org/abs/physics/0612067"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "79652566-7dac-4388-8348-1331e51111c2",
"id": "arXiv Dataset IDs",
"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
},
"user_id": 1000002
}