折线电容滤波算法在鼾声识别中的研究与应用  

Research and application of polylines capacitance algorithm in the snoring recognition

作　　者：薛雷[1] 何星剑[1] 高微微[1] 

机构地区：[1]上海大学通信与信息工程学院,上海200072

出　　处：《电子测量技术》2013年第2期6-10,共5页Electronic Measurement Technology

摘　　要：鼾声信号的采样是鼾声识别的关键技术,也是后级鼾声处理的前提。因此,采样到的鼾声信号的质量直接影响后级对鼾声信号处理的结果。鼾声在时域上具有连续性与均匀性,在频域上具有特定的频率宽度和共振峰等特征,由于以往采用的快速傅里叶(FFT)算法在鼾声频域采样上具有局限性,因此提出了一种基于无限增益巴特沃兹低通滤波器的折线电容滤波算法来对鼾声信号进行处理,并结合TMS320F2812DSP芯片多路同步对鼾声信号进行采样。采用这种方法不仅提高了采样效率,而且便于对各个频段鼾声能量进行分析。通过计算机仿真与实验验证,表明折线电容滤波算法可以有效的实现对鼾声信号的采样。The sampling of snoring signal is the key technology of the snoring recognition;it is also a prerequisite for the subsequent snoring processing.Therefore,the sampling's quality of snoring signal directly affects the results of subsequent snoring signal processing.Snoring signal has the continuity and uniformity in the time domain and has the specific frequency width and formant characteristics in the frequency domain.Considering the fast Fourier transform(FFT) used in the past has limitations in snoring frequency domain sampling,so we use the infinite gain multiple feedback low-pass filter based on the polylines capacitance algorithm to filter the snoring signal,and combining with TMS320F2812 DSP chip samplings snoring signal synchronously in multi-channel.This approach not only improves the sampling efficiency but also facilitates the analysis of each band of snoring energy.The simulation results of EWB show that the polylines capacitance algorithm can sampling the snoring signal effectively.

关 键 词：折线电容算法 低通滤波器 DSP 鼾声识别 

分 类 号：TP2[自动化与计算机技术—检测技术与自动化装置]