Signal Processing Method for Mattress-type Physiological Monitoring

SHEN Jinpeng†, WANG Xin’an

ACTA Scientiarum Naturalium Universitatis Pekinensis - - Contents -

The Key Laboratory of Integrated Microsystems, Peking University Shenzhen Graduate School, Shenzhen 518055; † E-mail: shenjp@pkusz.edu.cn

Abstract An empirical mode decomposition (EMD) based algorithm is proposed for mattress-type physiological monitoring. Fast Fourier Transform (FFT) is executed for the mixed physiological signal to estimate the frequency range of the respiration signal and heartbeat signal. Then the physiological signal is decomposed into several IMF components by EMD method, some of which are used to reconstruct the respiration signal and the heartbeat signal, according to the respiration or heartbeat spectrum energy in proportion of the total spectrum energy. The experiment result shows that the accuracy of measured respiration rate and heartbeat rate are both over 90%, compared with the polysomnography. Key words mattress-type physiological monitoring; EMD; piezoelectric sensor

呼吸和心跳信号是人体的基本生命特征信息,是反映人体心肺健康状况的重要参数[1–2]。传统的呼吸和心跳监测手段需要在人体佩戴传感器、粘贴电极等, 非常不方便。床垫式的人体生理信号监测系统是通过在床垫中安装压力或压电传感器, 可以在无负荷的情况下监测人体的呼吸和心跳, 使用简

[3–5]单, 已成为人体生理信号监测的研究热点 。床垫式生理信号监测系统的传感器采集的原始信号包括呼吸、心跳和噪声信号, 所以需要提取呼吸和心跳信号, 才能进一步计算呼吸率和心率。目前, 床垫式生理信号监测系统大多采用常规的滤波方法[6]

[7–8]或小波变换 来提取呼吸和心跳信号。然而, 异

常情况下的呼吸和心跳的频带与正常情况下的频带可能重叠, 常规的滤波方法不能处理这种情况。小波变换具有多分辨率的特性, 但是难以选取合适的小波基, 而且缺乏自适应性。因此, 本文提出一种基于 EMD (empirical mode decomposition)[9]的信号处理方法, 可以根据原始信号的特点, 动态地确定呼吸和心动的频带范围, 对输入信号进行自适应分解和重构, 有效地提取呼吸和心跳信号。

1 床垫式生理信号监测系统介绍

床垫式生理信号监测系统的框图见图 1。薄垫中安装 PVDF[10–11]压电传感器, 可以捕捉人体呼吸

Newspapers in Chinese (Simplified)

Newspapers from China

© PressReader. All rights reserved.