Rényi and permutation entropy analysis for assessment of cardiac autonomic neuropathy

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

doi:10.1007/978-981-10-5122-7_189

Rényi and permutation entropy analysis for assessment of cardiac autonomic neuropathy

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

Research output: Book chapter/Published conference paper › Conference paper › peer-review

3 Citations (Scopus)

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.

Original language	English
Title of host publication	EMBEC & NBC 2017
Subtitle of host publication	Joint conference of the European Medical and Biological Engineering Conference EMBEC 2017 and the Nordic-Baltic conference on Biomedical Engineering and Medical Physics (NBC)
Editors	Hannu Eskola, Outi Vaisanen, Jari Viik, Jari Hyttinen
Place of Publication	Singapore
Publisher	Springer-Verlag London Ltd.
Pages	755-758
Number of pages	4
Volume	65
ISBN (Electronic)	9789811051227
ISBN (Print)	9789811051210
DOIs	https://doi.org/10.1007/978-981-10-5122-7_189
Publication status	Published - 2018
Event	Joint Conference of European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC) - Tampere Hall, Tampere, Finland Duration: 11 Jun 2017 → 15 Jun 2017 https://web.archive.org/web/20180213061956/https://embec2017.org/ (Conference website) https://link.springer.com/book/10.1007/978-981-10-5122-7 (Conference proceedings)

Publication series

Name	IFMBE Proceedings
Publisher	Springer Nature
Volume	65
ISSN (Print)	1680-0737
ISSN (Electronic)	1433-9277

Conference

Conference	Joint Conference of European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC)
Country/Territory	Finland
City	Tampere
Period	11/06/17 → 15/06/17
Other	It is our pleasure to invite you to the joint conference of the European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC), in Tampere, Finland, in June 2017. These two long running conferences are now combined for the first time with aim to build a truly cross-discipline conference. We aim to present all traditional BMES and BME areas, but also highlight new emerging fields, such as tissue engineering, bioinformatics, biosensing, neurotechnology, additive manufacturing technologies for medicine and biology, and bioimaging, to name a few. Moreover, we will emphasize the role of education, translational research, and commercialization.The scientific and social program at EMBEC’17 & NBC’17 provides an excellent platform for engineers, physicists, biologists, and clinical experts to enhance our knowledge and scientific achievements by bridging complementary disciplines and new findings into an interactive and attractive forum.
Internet address	https://web.archive.org/web/20180213061956/https://embec2017.org/ (Conference website) https://link.springer.com/book/10.1007/978-981-10-5122-7 (Conference proceedings)

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

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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 H. Eskola, O. Vaisanen, J. Viik, & J. Hyttinen (Eds.), EMBEC & 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) (Vol. 65, pp. 755-758). (IFMBE Proceedings; Vol. 65). Springer-Verlag London Ltd.. https://doi.org/10.1007/978-981-10-5122-7_189

Carricarte-Naranjo, C. ; Cornforth, D. J. ; Sanchez-Rodriguez, L. M. et al. / Rényi and permutation entropy analysis for assessment of cardiac autonomic neuropathy. EMBEC & 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). editor / Hannu Eskola ; Outi Vaisanen ; Jari Viik ; Jari Hyttinen. Vol. 65 Singapore : Springer-Verlag London Ltd., 2018. pp. 755-758 (IFMBE Proceedings).

@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 Marta Brown and M. Est{\'e}vez and A. Machado and Jelinek, {Herbert F.}",

note = "Includes bibliographical references.; Joint Conference of European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC)<br/> ; Conference date: 11-06-2017 Through 15-06-2017",

year = "2018",

doi = "10.1007/978-981-10-5122-7_189",

language = "English",

isbn = "9789811051210",

volume = "65",

series = "IFMBE Proceedings",

publisher = "Springer-Verlag London Ltd.",

pages = "755--758",

editor = "Hannu Eskola and Outi Vaisanen and Jari Viik and Jari Hyttinen",

booktitle = "EMBEC & NBC 2017",

address = "Germany",

url = "https://web.archive.org/web/20180213061956/https://embec2017.org/, https://link.springer.com/book/10.1007/978-981-10-5122-7",

}

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 H Eskola, O Vaisanen, J Viik & J Hyttinen (eds), EMBEC & 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). vol. 65, IFMBE Proceedings, vol. 65, Springer-Verlag London Ltd., Singapore, pp. 755-758, Joint Conference of European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC)
, Tampere, Finland, 11/06/17. https://doi.org/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. et al.
EMBEC & 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). ed. / Hannu Eskola; Outi Vaisanen; Jari Viik; Jari Hyttinen. Vol. 65 Singapore: Springer-Verlag London Ltd., 2018. p. 755-758 (IFMBE Proceedings; Vol. 65).

Research output: Book chapter/Published conference paper › Conference paper › peer-review

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, Marta

AU - Estévez, M.

AU - Machado, A.

AU - Jelinek, Herbert F.

N1 - Includes bibliographical references.

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

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

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

M3 - Conference paper

AN - SCOPUS:85021707069

SN - 9789811051210

VL - 65

T3 - IFMBE Proceedings

SP - 755

EP - 758

BT - EMBEC & NBC 2017

A2 - Eskola, Hannu

A2 - Vaisanen, Outi

A2 - Viik, Jari

A2 - Hyttinen, Jari

PB - Springer-Verlag London Ltd.

CY - Singapore

T2 - Joint Conference of European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC)<br/>

Y2 - 11 June 2017 through 15 June 2017

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 Eskola H, Vaisanen O, Viik J, Hyttinen J, editors, EMBEC & 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). Vol. 65. Singapore: Springer-Verlag London Ltd. 2018. p. 755-758. (IFMBE Proceedings). Epub 2017. doi: 10.1007/978-981-10-5122-7_189

Rényi and permutation entropy analysis for assessment of cardiac autonomic neuropathy

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