Work

A Novel Audio-Perception-Based Algorithm for Physiological Monitoring

Year: 2025

Type: article

Abstract: Exercise metrics are critical for assessing health, but real-time heart rate and respiration measurements remain challenging. We propose a physiological monitoring system that uses an in-ear microphone to extract heart rate and respiration from faint ear canal signals. An improved non-negative matrix factorization (NMF) algorithm combines with a short-time Fourier transform (STFT) to separate physiological components, while an inverse Fourier transform (IFT) reconstructs the signal. The earplug effect enhances the low-frequency components, thereby improving the signal quality and noise immunity. Heart rate is derived from short-term energy and zero-crossing rate, while a BiLSTM-based model can refine the breathing phases and calculate indicators such as respiratory rate. Experiments have shown that the average accuracy can reach 91% under various conditions, exceeding 90% in different environments and under different weights, thus ensuring the system's robustness.

Source: Sensors

DOI: 10.3390/s25123582

Authors: Zixuan Zhang, Wenxuan Jin, Dejiao Huang, Zhongwei Sun

Institutions: Qingdao University of Technology, Ocean University of China

Language: English

Topic: Non-Invasive Vital Sign Monitoring

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,137