基于光纤光栅传感器的心音信号提取与处理算法研究

本文研究了一种用于光纤光栅智能服装的心音信号提取与处理算法，实现异常心音的初步识别。提出基于希尔伯特-黄变换（HHT）和小波阈值消噪相结合的心音提取算法，对波长解调信号进行消噪，提取有用的心音信号。采用数学形态学进行心音包络提取，提出基于直线结构元素和余弦结构元素相结合的心音处理算法，准确获取心音峰值点和起止点位置并计算心音特征值，根据心音特征值的临床意义，判断心音是否正常。实验结果表明该算法能够有效消除波长解调信号中的呼吸干扰与噪声，对20例实测正常心音和8类常见异常心音均能正确识别。该算法具有易实现、识别率高的特点，对光纤传感智能服装的研发和心脏疾病的早期诊断具有重要意义。 

Study on Heart Sound Extraction and Identification based on an Optical Grating Sensor

A heart sound extracted and processing algorithm was studied for smart clothing based on fiber grating sensors. Combining Hilbert-Huang transform (HHT) with wavelet threshold denoising, the heart sound denoising algorithm was proposed to extract the useful heart sound signal from wavelength demodulated signal. The peak points and start and end points of heart sound were obtained respectively from the envelopes extracted by mathematical morphology method based on the line and cosine structuring elements, and then the characteristic parameters of the heart sound were calculated. Using those parameters, normal or abnormal heart sounds can be identified. The experimental results show that the algorithm can effectively remove the breathing interference and noise mixed in the wavelength demodulated signal. In the tests of 20 cases of normal heart sounds and 8 kinds common abnormal heart sounds, all of the recognition results are correct. The algorithm is characterized by easy realization and high recognition rate, and it is significant to the development of the fiber optic sensing smart clothing and the early diagnosis of heart disease.