An integrated diabetic index using heart rate variability signal features for diagnosis of diabetes

U. Rajendra Acharya; Oliver Faust; S. Vinitha Sree; Dhanjoo N. Ghista; Sumeet Dua; Paul Joseph; V. I. Thajudin Ahamed; Nittiagandhi Janarthanan; Toshiyo Tamura

doi:10.1080/10255842.2011.616945

An integrated diabetic index using heart rate variability signal features for diagnosis of diabetes

U. Rajendra Acharya
, Oliver Faust
, S. Vinitha Sree
, Dhanjoo N. Ghista
, Sumeet Dua
, Paul Joseph
, V. I. Thajudin Ahamed
, Nittiagandhi Janarthanan
, Toshiyo Tamura

Ngee Ann Polytechnic
Nanyang Technological University
Framingham State University
National Institute of Technology Calicut
Government Engineering College, Sreekrishnapuram
Chiba University

Research output: Contribution to journal › Article › peer-review

Original language	American English
Journal	Computer Methods in Biomechanics and Biomedical Engineering
Volume	16
Issue number	2
DOIs	https://doi.org/10.1080/10255842.2011.616945
State	Published - Feb 1 2013

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Disciplines

Medicine and Health Sciences
Signal Processing
Biological Engineering

Access to Document

10.1080/10255842.2011.616945License: Unspecified

Cite this

@article{7c0a1cc9ff8f4fe78c9da14e0d49be33,

title = "An integrated diabetic index using heart rate variability signal features for diagnosis of diabetes",

author = "Acharya, \{U. Rajendra\} and Oliver Faust and Sree, \{S. Vinitha\} and Ghista, \{Dhanjoo N.\} and Sumeet Dua and Paul Joseph and Ahamed, \{V. I. Thajudin\} and Nittiagandhi Janarthanan and Toshiyo Tamura",

note = "Electrocardiogram (ECG) signals are difficult to interpret, and clinicians must undertake a long training process to learn to diagnose diabetes from subtle abnormalities in these signals. To facilitate these diagnoses, we have developed a technique based on the heart rate variability signal obtained from ECG signals.",

year = "2013",

month = feb,

day = "1",

doi = "10.1080/10255842.2011.616945",

language = "American English",

volume = "16",

journal = "Computer Methods in Biomechanics and Biomedical Engineering",

number = "2",

}

TY - JOUR

T1 - An integrated diabetic index using heart rate variability signal features for diagnosis of diabetes

AU - Acharya, U. Rajendra

AU - Faust, Oliver

AU - Sree, S. Vinitha

AU - Ghista, Dhanjoo N.

AU - Dua, Sumeet

AU - Joseph, Paul

AU - Ahamed, V. I. Thajudin

AU - Janarthanan, Nittiagandhi

AU - Tamura, Toshiyo

N1 - Electrocardiogram (ECG) signals are difficult to interpret, and clinicians must undertake a long training process to learn to diagnose diabetes from subtle abnormalities in these signals. To facilitate these diagnoses, we have developed a technique based on the heart rate variability signal obtained from ECG signals.

PY - 2013/2/1

Y1 - 2013/2/1

UR - https://dr.ntu.edu.sg/handle/10220/17841

U2 - 10.1080/10255842.2011.616945

DO - 10.1080/10255842.2011.616945

M3 - Article

VL - 16

JO - Computer Methods in Biomechanics and Biomedical Engineering

JF - Computer Methods in Biomechanics and Biomedical Engineering

IS - 2

ER -

An integrated diabetic index using heart rate variability signal features for diagnosis of diabetes

UN SDGs

Disciplines

Access to Document

Other files and links

Fingerprint

Cite this