@inproceedings{759d3179a41548ef8c66e82d4415dfbd,
title = "Coronary artery disease diagnosis by means of heart rate variability analysis using respiratory information",
abstract = "Heart rate variability (HRV) analysis during exercise has been used to evaluate cardiovascular response to the stress of exercise, which may offer additional value than in rest condition. To properly analyze HRV during exercise, several challenges need to be addressed, such as including respiratory information and removing the dependance with the mean heart rate (HR) level. The objective of this work is to extract parameters from HRV analysis and respiratory information during exercise to evaluate their capability of diagnose coronary artery disease (CAD). Significant differences in mean HR were found due to medication effect in patients with CAD. By correcting the HRV parameters by mean HR, this effect is minimized. Power related to high frequency, when guided by respiration, results to have the best diagnosis capability (AUC > 0.7).",
keywords = "CAD diagnosis, Exercise test, Respiratory rate, CAD diagnosis, Exercise test, Respiratory rate",
author = "D. Hernando and M. K{\"a}h{\"o}nen and J. L{\'a}zaro and R. Lehtinen and T. Nieminen and K. Nikus and T. Lehtim{\"a}ki and R. Bail{\'o}n and J. Viik",
note = "jufoid=58152; Joint Conference of the European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC) ; Conference date: 01-01-2018",
year = "2018",
doi = "10.1007/978-981-10-5122-7\_68",
language = "English",
isbn = "978-981-10-5121-0",
series = "IFMBE Proceedings",
publisher = "Springer Verlag",
pages = "270--273",
editor = "Hannu Eskola",
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",
address = "Germany",
}