Rényi and permutation entropy analysis for assessment of cardiac autonomic neuropathy

C. Carricarte-Naranjo, D. J. Cornforth, L. M. Sanchez-Rodriguez, M. Brown, M. Estévez, A. Machado, Herbert F. Jelinek

Research output: Chapter in Book/Report/Conference proceedingConference paper

Abstract

Cardiac autonomic neuropathy (CAN) is a complication of diabetes with a long asymptomatic phase that is associated with high morbidity and mortality. Early identification of CAN in Type 1 diabetes mellitus (T1DM) may be possible using heart rate variability (HRV). However, the power of HRV analysis to identify CAN depends on the selection of suitable features that provide reliable information regarding cardiac autonomic regulation. Our aim was to compare the performance of Rényi entropy (RE) and permutation entropy (PE) for identification of T1DM patients with CAN. RE and PE measures from 235 data points and 5 min of cardiac interbeat interval (RR) sequences were analysed in 18 T1DM patients without CAN, 14 T1DM patients with CAN, and healthy controls matched for age and sex. RE was calculated for different orders α (-5, 5), pattern lengths λ (2, 4, 8), and tolerance σ. For PE analysis λ was set to (3-4) and time delays τ to (1-10). A forward stepwise discriminant analysis was carried out for estimating the classification functions. Accuracy was estimated following a K-fold cross-validation (k = 14). RE calculated for RR sequences of λ = 2, α > 0 showed the best performance for differentiating T1DM patients with CAN (p < 0.0001). PE measures showed better performance with ordinal patterns and τ = 4, 5 and 7 for differentiating patients with CAN. RE and PE provide complementary information achieving 100% classification accuracy (p < 0.0001 and p < 0.001, respectively). This approach might be promising as a sensitive and specific tool for CAN diagnosis in T1DM.
LanguageEnglish
Title of book or conference publicationEMBEC and NBC 2017 - Joint Conference of the European Medical and Biological Engineering Conference EMBEC 2017 and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics, NBC 2017
PublisherSpringer-Verlag London Ltd.
Pages755-758
Number of pages4
Volume65
ISBN (Print)9789811051210
DOIs
StatePublished - 2018
EventJoint Conference of the European Medical and Biological Engineering Conference, EMBEC 2017 and Nordic-Baltic Conference on Biomedical Engineering and Medical Physics, NBC 2107 - Tampere, Finland
Duration: 11 Jun 201715 Jun 2017

Conference

ConferenceJoint Conference of the European Medical and Biological Engineering Conference, EMBEC 2017 and Nordic-Baltic Conference on Biomedical Engineering and Medical Physics, NBC 2107
CountryFinland
CityTampere
Period11/06/1715/06/17

Fingerprint

Entropy
Medical problems
Discriminant analysis
Time delay

Cite this

Carricarte-Naranjo, C., Cornforth, D. J., Sanchez-Rodriguez, L. M., Brown, M., Estévez, M., Machado, A., & Jelinek, H. F. (2018). Rényi and permutation entropy analysis for assessment of cardiac autonomic neuropathy. In EMBEC and NBC 2017 - Joint Conference of the European Medical and Biological Engineering Conference EMBEC 2017 and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics, NBC 2017 (Vol. 65, pp. 755-758). Springer-Verlag London Ltd.. DOI: 10.1007/978-981-10-5122-7_189
Carricarte-Naranjo, C. ; Cornforth, D. J. ; Sanchez-Rodriguez, L. M. ; Brown, M. ; Estévez, M. ; Machado, A. ; Jelinek, Herbert F./ Rényi and permutation entropy analysis for assessment of cardiac autonomic neuropathy. EMBEC and NBC 2017 - Joint Conference of the European Medical and Biological Engineering Conference EMBEC 2017 and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics, NBC 2017. Vol. 65 Springer-Verlag London Ltd., 2018. pp. 755-758
@inproceedings{e14aa82dc44b442ebc7c9d88ec41b4b1,
title = "R{\'e}nyi and permutation entropy analysis for assessment of cardiac autonomic neuropathy",
abstract = "Cardiac autonomic neuropathy (CAN) is a complication of diabetes with a long asymptomatic phase that is associated with high morbidity and mortality. Early identification of CAN in Type 1 diabetes mellitus (T1DM) may be possible using heart rate variability (HRV). However, the power of HRV analysis to identify CAN depends on the selection of suitable features that provide reliable information regarding cardiac autonomic regulation. Our aim was to compare the performance of R{\'e}nyi entropy (RE) and permutation entropy (PE) for identification of T1DM patients with CAN. RE and PE measures from 235 data points and 5 min of cardiac interbeat interval (RR) sequences were analysed in 18 T1DM patients without CAN, 14 T1DM patients with CAN, and healthy controls matched for age and sex. RE was calculated for different orders α (-5, 5), pattern lengths λ (2, 4, 8), and tolerance σ. For PE analysis λ was set to (3-4) and time delays τ to (1-10). A forward stepwise discriminant analysis was carried out for estimating the classification functions. Accuracy was estimated following a K-fold cross-validation (k = 14). RE calculated for RR sequences of λ = 2, α > 0 showed the best performance for differentiating T1DM patients with CAN (p < 0.0001). PE measures showed better performance with ordinal patterns and τ = 4, 5 and 7 for differentiating patients with CAN. RE and PE provide complementary information achieving 100{\%} classification accuracy (p < 0.0001 and p < 0.001, respectively). This approach might be promising as a sensitive and specific tool for CAN diagnosis in T1DM.",
keywords = "Cardiac autonomic neuropathy, Heart rate variability, Ordinal patterns, Permutation entropy, R{\'e}nyi entropy",
author = "C. Carricarte-Naranjo and Cornforth, {D. J.} and Sanchez-Rodriguez, {L. M.} and M. Brown and M. Est{\'e}vez and A. Machado and Jelinek, {Herbert F.}",
year = "2018",
doi = "10.1007/978-981-10-5122-7_189",
language = "English",
isbn = "9789811051210",
volume = "65",
pages = "755--758",
booktitle = "EMBEC and NBC 2017 - Joint Conference of the European Medical and Biological Engineering Conference EMBEC 2017 and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics, NBC 2017",
publisher = "Springer-Verlag London Ltd.",
address = "Germany",

}

Carricarte-Naranjo, C, Cornforth, DJ, Sanchez-Rodriguez, LM, Brown, M, Estévez, M, Machado, A & Jelinek, HF 2018, Rényi and permutation entropy analysis for assessment of cardiac autonomic neuropathy. in EMBEC and NBC 2017 - Joint Conference of the European Medical and Biological Engineering Conference EMBEC 2017 and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics, NBC 2017. vol. 65, Springer-Verlag London Ltd., pp. 755-758, Joint Conference of the European Medical and Biological Engineering Conference, EMBEC 2017 and Nordic-Baltic Conference on Biomedical Engineering and Medical Physics, NBC 2107, Tampere, Finland, 11/06/17. DOI: 10.1007/978-981-10-5122-7_189

Rényi and permutation entropy analysis for assessment of cardiac autonomic neuropathy. / Carricarte-Naranjo, C.; Cornforth, D. J.; Sanchez-Rodriguez, L. M.; Brown, M.; Estévez, M.; Machado, A.; Jelinek, Herbert F.

EMBEC and NBC 2017 - Joint Conference of the European Medical and Biological Engineering Conference EMBEC 2017 and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics, NBC 2017. Vol. 65 Springer-Verlag London Ltd., 2018. p. 755-758.

Research output: Chapter in Book/Report/Conference proceedingConference paper

TY - GEN

T1 - Rényi and permutation entropy analysis for assessment of cardiac autonomic neuropathy

AU - Carricarte-Naranjo,C.

AU - Cornforth,D. J.

AU - Sanchez-Rodriguez,L. M.

AU - Brown,M.

AU - Estévez,M.

AU - Machado,A.

AU - Jelinek,Herbert F.

PY - 2018

Y1 - 2018

N2 - Cardiac autonomic neuropathy (CAN) is a complication of diabetes with a long asymptomatic phase that is associated with high morbidity and mortality. Early identification of CAN in Type 1 diabetes mellitus (T1DM) may be possible using heart rate variability (HRV). However, the power of HRV analysis to identify CAN depends on the selection of suitable features that provide reliable information regarding cardiac autonomic regulation. Our aim was to compare the performance of Rényi entropy (RE) and permutation entropy (PE) for identification of T1DM patients with CAN. RE and PE measures from 235 data points and 5 min of cardiac interbeat interval (RR) sequences were analysed in 18 T1DM patients without CAN, 14 T1DM patients with CAN, and healthy controls matched for age and sex. RE was calculated for different orders α (-5, 5), pattern lengths λ (2, 4, 8), and tolerance σ. For PE analysis λ was set to (3-4) and time delays τ to (1-10). A forward stepwise discriminant analysis was carried out for estimating the classification functions. Accuracy was estimated following a K-fold cross-validation (k = 14). RE calculated for RR sequences of λ = 2, α > 0 showed the best performance for differentiating T1DM patients with CAN (p < 0.0001). PE measures showed better performance with ordinal patterns and τ = 4, 5 and 7 for differentiating patients with CAN. RE and PE provide complementary information achieving 100% classification accuracy (p < 0.0001 and p < 0.001, respectively). This approach might be promising as a sensitive and specific tool for CAN diagnosis in T1DM.

AB - Cardiac autonomic neuropathy (CAN) is a complication of diabetes with a long asymptomatic phase that is associated with high morbidity and mortality. Early identification of CAN in Type 1 diabetes mellitus (T1DM) may be possible using heart rate variability (HRV). However, the power of HRV analysis to identify CAN depends on the selection of suitable features that provide reliable information regarding cardiac autonomic regulation. Our aim was to compare the performance of Rényi entropy (RE) and permutation entropy (PE) for identification of T1DM patients with CAN. RE and PE measures from 235 data points and 5 min of cardiac interbeat interval (RR) sequences were analysed in 18 T1DM patients without CAN, 14 T1DM patients with CAN, and healthy controls matched for age and sex. RE was calculated for different orders α (-5, 5), pattern lengths λ (2, 4, 8), and tolerance σ. For PE analysis λ was set to (3-4) and time delays τ to (1-10). A forward stepwise discriminant analysis was carried out for estimating the classification functions. Accuracy was estimated following a K-fold cross-validation (k = 14). RE calculated for RR sequences of λ = 2, α > 0 showed the best performance for differentiating T1DM patients with CAN (p < 0.0001). PE measures showed better performance with ordinal patterns and τ = 4, 5 and 7 for differentiating patients with CAN. RE and PE provide complementary information achieving 100% classification accuracy (p < 0.0001 and p < 0.001, respectively). This approach might be promising as a sensitive and specific tool for CAN diagnosis in T1DM.

KW - Cardiac autonomic neuropathy

KW - Heart rate variability

KW - Ordinal patterns

KW - Permutation entropy

KW - Rényi entropy

UR - http://www.scopus.com/inward/record.url?scp=85021707069&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85021707069&partnerID=8YFLogxK

U2 - 10.1007/978-981-10-5122-7_189

DO - 10.1007/978-981-10-5122-7_189

M3 - Conference paper

SN - 9789811051210

VL - 65

SP - 755

EP - 758

BT - EMBEC and NBC 2017 - Joint Conference of the European Medical and Biological Engineering Conference EMBEC 2017 and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics, NBC 2017

PB - Springer-Verlag London Ltd.

ER -

Carricarte-Naranjo C, Cornforth DJ, Sanchez-Rodriguez LM, Brown M, Estévez M, Machado A et al. Rényi and permutation entropy analysis for assessment of cardiac autonomic neuropathy. In EMBEC and NBC 2017 - Joint Conference of the European Medical and Biological Engineering Conference EMBEC 2017 and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics, NBC 2017. Vol. 65. Springer-Verlag London Ltd.2018. p. 755-758. Available from, DOI: 10.1007/978-981-10-5122-7_189