HRV and BPV indices in differentiating OSA patients from healthy controls - Open Research Data - Bridge of Knowledge

Your account

login

Search

HRV and BPV indices in differentiating OSA patients from healthy controls

Description

The various HRV and BPV indices computed for the purpose of the analyses described in the paper “Differentiating patients with obstructive sleep apnea from healthy controls based on heart rate–blood pressure coupling quantified by entropy-based indices” by P. Pilarczyk, G. Graff, J.M. Amigó, K. Tessmer, K. Narkiewicz, and B. Graff.

The paper was published in Chaos 33 (2023), 103140. DOI: 10.1063/5.0158923. See also arXiv:2311.10752.

If you use this data in your research, please, cite the paper.

Each row in the CSV file corresponds to data for one person.

The first ten columns in the CSV file contain the following data:
1. Classification of the person: OSA – a patient suffering from obstructive sleep apnea, CON – a healthy individual (control).
2. Duration of the processed recording (in seconds).
3. Number of R peaks detected in the ECG data.
4. Number of R peaks chosen for the analysis (which excludes outliers and other artifacts).
5. Minimum length of an RR interval considered.
6. Maximum length of an RR interval considered.
7. Number of systolic blood pressure (BP peaks) in the data.
8. Number of BP peaks chosen for the analysis (which excludes outliers and other artifacts).
9. Minimum value of BP peak considered.
10. Maximum value of BP peak considered.

The columns that follow contain the values of indices computed for each patient, as described in the paper. The columns with labels ending with “_bad%” indicate the percentage of sequences excluded from the computation of the corresponding indices based on ordinal patterns due to the fact that any of the sequences in use would contain an artifact.

This research was supported by the National Science Centre, Poland, within the following grants: SHENG 2018/30/Q/ST1/00228 (G. Graff), OPUS 2021/41/B/ST1/00405 (P. Pilarczyk), and MAESTRO 2011/02/A/NZ5/00329 (B. Graff and K. Narkiewicz). J. M. Amigó was financially supported by Agencia Estatal de Investigación, Spain, Grant No. PID2019-108654GB-I00/AEI/10.13039/501100011033 and by Generalitat Valenciana, Spain, Grant PROMETEO/2021/063. G. Graff and K. Tessmer were also supported by Gdańsk University of Technology grant Neptunium Excellence Initiative—Research University, DEC−2/2021/IDUB/II. Computations were carried out using the computers of Centre of Informatics Tricity Academic Supercomputer and Network.

Dataset file

DATA.csv
95.2 kB, S3 ETag 8a139e6ba39f5e586e759eff7a3f0385-1, downloads: 33
The file hash is calculated from the formula
hexmd5(md5(part1)+md5(part2)+...)-{parts_count} where a single part of the file is 512 MB in size.

Example script for calculation:
https://github.com/antespi/s3md5

File details

License:
Creative Commons: 0 1.0 open in new tab
CC 0
Public Domain Dedication

Details

Year of publication:
2023
Verification date:
2024-09-25
Creation date:
2023
Dataset language:
English
Fields of science:
  • mathematics (Natural sciences)
  • physical sciences (Natural sciences)
  • medical sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/h62n-py28 open in new tab
Series:
Verified by:
Gdańsk University of Technology

Keywords

References

Cite as

Authors

seen 90 times