Continuous Pulmonary Artery Pressure Monitoring using In-ear Microphone
Junyi Zhou, Chaoyi Sun, Di Fan, Yiyi Zhang, Cheng Chen, Xiaojun Wu, Chao Cai, Linyi Liu, Peng Guo
Abstract
The early diagnosis and effective management of Pulmonary Hypertension (PH) are critically dependent on the accurate monitoring of Pulmonary Arterial Pressure (PAP). However, current clinical methods are either invasive or resource-intensive, which limits their application for continuous PAP monitoring. To overcome this challenge, we introduce a novel, noninvasive method for PAP monitoring utilizing in-ear audio. Our approach traces the Heart Sound (HS) through a physics-guided modeling from in-ear audio. Subsequently, we derive PAP indicators from the second heart sound (S2) using a sophisticated signal processing pipeline. This pipeline incorporates mode decomposition, spectral clustering, and Morphological Component Analysis (MCA). Finally, a Dendritic Neuron Regression (DNR) network is employed to determine absolute PAP values from the extracted indicators. Validation of our method on real-world data from 26 participants demonstrates clinically acceptable error margins in the estimation of mean PAP (mPAP), with an estimation error of 1.31 ± 2.83 mmHg. These promising results highlight the potential of our in-ear audio approach for developing wearable, noninvasive, and continuous PAP monitoring devices. This could significantly improve the management of PH by providing a more accessible and patient-friendly monitoring solution.
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