@inproceedings{a923ede19aae4515b20fdbf1d6e317e6,
title = "High Accuracy Respiration and Heart Rate Detection Based on Artificial Neural Network Regression",
abstract = "A 24GHz Doppler radar system for accurate contactless monitoring of heart and respiratory rates is demonstrated here. High accuracy predictions are achieved by employing a CNN+LSTM neural network architecture for regression analysis. Detection accuracies of 99% and 98% have been attained for heart rate and respiration rate, respectively.Clinical Relevance - This work establishes a non-contact radar system with 99% detection accuracy for a heart rate variability warning system. This system can enable convenient and fast monitoring for daily care at home.",
author = "Tsai, {Yu Chiao} and Lai, {Shih Hsuan} and Ho, {Ching Ju} and Wu, {Fang Ming} and Lindor Henrickson and Wei, {Chia Chien} and Irwin Chen and Vincent Wu and Jyehong Chen",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020 ; Conference date: 20-07-2020 Through 24-07-2020",
year = "2020",
month = jul,
doi = "10.1109/EMBC44109.2020.9175161",
language = "English",
series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "232--235",
booktitle = "42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society",
address = "United States",
}