High Accuracy Respiration and Heart Rate Detection Based on Artificial Neural Network Regression
Yu-Chiao Tsai, Shih-Hsuan Lai, Ching-Ju Ho, Fang-Ming Wu, Lindor Henrickson, Chia-Chien Wei, Irwin Chen, Vincent Wu, Jyehong Chen
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.
Topics & Concepts
Artificial neural networkComputer scienceArtificial intelligenceRegressionRegression analysisPattern recognition (psychology)Machine learningStatisticsMathematicsNon-Invasive Vital Sign MonitoringHeart Rate Variability and Autonomic ControlECG Monitoring and Analysis