Reproducibility archive: baroreflex winding number as a cardiac autonomic biomarker

Reproducibility Archive — "The baroreflex winding number"## J. R. Soc. Interface (submitted May 2026) **Author:** R. A. Satnoianu Oxford, UK **Contact:** [email protected] **Zenodo DOI:** https://doi.org/10.5281/zenodo.20359900 ## Purpose of this deposit This archive contains the analysis code that reproduces **all numericalresults, Table 1, Figure 1, and Figure 2** in the paper: > Satnoianu RA. "The baroreflex winding number: a theoretically grounded> frequency-ratio biomarker of cardiac autonomic function."> *Journal of the Royal Society Interface* (submitted 2026). The code is a **paper-specific reproducibility archive**. It is scopedexactly to the datasets, segments, and quality criteria described in thepaper. It is not a general-purpose library or production implementation. ## Access and licensing **This deposit is restricted access.** To request the files, use theZenodo request button. Access is granted to: - Academic researchers for the purpose of verifying or building upon the results in the paper (permitted under CC BY-NC-ND 4.0 below).- Journalists and science communicators assessing the work. **Commercial use — including incorporation into any product, device,service, or clinical workflow — is not permitted under this licenceand requires a separate written commercial licence agreement.** To enquire about a commercial licence, contact:[email protected] The baroreflex winding number method is additionally protected byUS Provisional Patent Applications:- 64/071,377 (FW-PROV-23, filed 21 May 2026)- 64/072,074 (FW-PROV-24, filed 22 May 2026)- 64/073,209 (FW-PROV-25, filed 23 May 2026)- 64/073,236 (FW-PROV-26, filed 23 May 2026) ## Licence **Creative Commons Attribution–NonCommercial–NoDerivatives 4.0International (CC BY-NC-ND 4.0)** You are free to share this material for non-commercial purposes, withattribution, and without modification or adaptation. See LICENSE fileand https://creativecommons.org/licenses/by-nc-nd/4.0/ for full terms. Commercial use of any kind — including use in medical devices, clinicalsoftware, wellness applications, biofeedback products, or any revenue-generating context — requires a separate commercial licence. [email protected]. ## Contents ```results_omega_B.json Pre-computed results: Table 1 individual values, CHF aggregate statistics, all reported statistics.plot_figures.py Reads the JSON; prints Table 1; saves Figure 1 and Figure 2. No signal processing — no PhysioNet download needed.requirements.txt Python dependencies (numpy, scipy, matplotlib only)LICENSE CC BY-NC-ND 4.0 licence textREADME.md This file``` **What is and is not deposited:**The JSON contains the pre-computed ω_B values, f_LF, f_RESP, and statisticsthat underlie Table 1 and Figures 1–2. The signal processing pipeline thatproduced these values (R-peak detection, Welch PSD estimation, RR interpolation,quality filtering) is described fully in the paper Methods section (§2.2–2.3)and is covered by the patent applications listed above. Raw physiologicalsignals are available from PhysioNet (see below). ## Raw datasets (not included — freely available from PhysioNet) - **Fantasia Database:** https://physionet.org/content/fantasia/1.0.0/- **CHF2DB Database:** https://physionet.org/content/chf2db/1.0.0/ > Goldberger AL, et al. PhysioBank, PhysioToolkit, and PhysioNet.> *Circulation* 2000;101(23):e215–e220. ## Reproducing the paper results ### Requirements Python 3.9+. No PhysioNet download required. ```bashpip install -r requirements.txt ### Running ```bashpython plot_figures.py This will:1. Read `results_omega_B.json`2. Print Table 1 to stdout and re-compute primary statistics3. Save `fig1_fantasia.pdf` (Figure 1, six panels)4. Save `fig2_crosscohort.pdf` (Figure 2, three panels) Expected runtime: < 30 seconds. ### Expected output Table 1 values should match the paper to within floating-point precision.Mann-Whitney U=17, p=0.037 (one-sided), Cohen d=1.22 (Fantasia primary).Cross-cohort: Young vs CHF p=0.038, d=0.88. --- ## Related deposits This deposit (DOI: 10.5281/zenodo.20359900) contains the focusedreproducibility archive for the JRSI baroreflex winding number paper.The broader Fibonacci biological programme, including the B6 PNAS manuscript,is archived separately at: - **Programme archive (DOI: 10.5281/zenodo.20304011):** "Fibonacci-φ pattern-formation research programme" — theoretical context and empirical observations across plant and vertebrate pattern formation (PNAS submission, May 2026). *Last updated: 23 May 2026*

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-23
DOI
https://doi.org/10.5281/zenodo.20359899
Primary Topic
Heart Rate Variability and Autonomic Control
Type
preprint
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Reproducibility archive: baroreflex winding number as a cardiac autonomic biomarker

Razvan Satnoianu
Zenodo (CERN European Organization for Nuclear Research)
Heart Rate Variability and Autonomic Control
preprint

Reproducibility archive: baroreflex winding number as a cardiac autonomic biomarker

Razvan Satnoianu
preprint en

Abstract

Reproducibility Archive — "The baroreflex winding number"## J. R. Soc. Interface (submitted May 2026) **Author:** R. A. Satnoianu Oxford, UK **Contact:** [email protected] **Zenodo DOI:** https://doi.org/10.5281/zenodo.20359900 ## Purpose of this deposit This archive contains the analysis code that reproduces **all numericalresults, Table 1, Figure 1, and Figure 2** in the paper: > Satnoianu RA. "The baroreflex winding number: a theoretically grounded> frequency-ratio biomarker of cardiac autonomic function."> *Journal of the Royal Society Interface* (submitted 2026). The code is a **paper-specific reproducibility archive**. It is scopedexactly to the datasets, segments, and quality criteria described in thepaper. It is not a general-purpose library or production implementation. ## Access and licensing **This deposit is restricted access.** To request the files, use theZenodo request button. Access is granted to: - Academic researchers for the purpose of verifying or building upon the results in the paper (permitted under CC BY-NC-ND 4.0 below).- Journalists and science communicators assessing the work. **Commercial use — including incorporation into any product, device,service, or clinical workflow — is not permitted under this licenceand requires a separate written commercial licence agreement.** To enquire about a commercial licence, contact:[email protected] The baroreflex winding number method is additionally protected byUS Provisional Patent Applications:- 64/071,377 (FW-PROV-23, filed 21 May 2026)- 64/072,074 (FW-PROV-24, filed 22 May 2026)- 64/073,209 (FW-PROV-25, filed 23 May 2026)- 64/073,236 (FW-PROV-26, filed 23 May 2026) ## Licence **Creative Commons Attribution–NonCommercial–NoDerivatives 4.0International (CC BY-NC-ND 4.0)** You are free to share this material for non-commercial purposes, withattribution, and without modification or adaptation. See LICENSE fileand https://creativecommons.org/licenses/by-nc-nd/4.0/ for full terms. Commercial use of any kind — including use in medical devices, clinicalsoftware, wellness applications, biofeedback products, or any revenue-generating context — requires a separate commercial licence. [email protected]. ## Contents ```results_omega_B.json Pre-computed results: Table 1 individual values, CHF aggregate statistics, all reported statistics.plot_figures.py Reads the JSON; prints Table 1; saves Figure 1 and Figure 2. No signal processing — no PhysioNet download needed.requirements.txt Python dependencies (numpy, scipy, matplotlib only)LICENSE CC BY-NC-ND 4.0 licence textREADME.md This file``` **What is and is not deposited:**The JSON contains the pre-computed ω_B values, f_LF, f_RESP, and statisticsthat underlie Table 1 and Figures 1–2. The signal processing pipeline thatproduced these values (R-peak detection, Welch PSD estimation, RR interpolation,quality filtering) is described fully in the paper Methods section (§2.2–2.3)and is covered by the patent applications listed above. Raw physiologicalsignals are available from PhysioNet (see below). ## Raw datasets (not included — freely available from PhysioNet) - **Fantasia Database:** https://physionet.org/content/fantasia/1.0.0/- **CHF2DB Database:** https://physionet.org/content/chf2db/1.0.0/ > Goldberger AL, et al. PhysioBank, PhysioToolkit, and PhysioNet.> *Circulation* 2000;101(23):e215–e220. ## Reproducing the paper results ### Requirements Python 3.9+. No PhysioNet download required. ```bashpip install -r requirements.txt ### Running ```bashpython plot_figures.py This will:1. Read `results_omega_B.json`2. Print Table 1 to stdout and re-compute primary statistics3. Save `fig1_fantasia.pdf` (Figure 1, six panels)4. Save `fig2_crosscohort.pdf` (Figure 2, three panels) Expected runtime: < 30 seconds. ### Expected output Table 1 values should match the paper to within floating-point precision.Mann-Whitney U=17, p=0.037 (one-sided), Cohen d=1.22 (Fantasia primary).Cross-cohort: Young vs CHF p=0.038, d=0.88. --- ## Related deposits This deposit (DOI: 10.5281/zenodo.20359900) contains the focusedreproducibility archive for the JRSI baroreflex winding number paper.The broader Fibonacci biological programme, including the B6 PNAS manuscript,is archived separately at: - **Programme archive (DOI: 10.5281/zenodo.20304011):** "Fibonacci-φ pattern-formation research programme" — theoretical context and empirical observations across plant and vertebrate pattern formation (PNAS submission, May 2026). *Last updated: 23 May 2026*

Zenodo (CERN European Organization for Nuclear Research)
Heart Rate Variability and Autonomic Control
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