CAJ | 학술논문

为了在滤除噪声的同时不丢失信号有用信息,将小波熵理论与小波阈值去噪方法综合起来,提出一种基于小波熵的自适应阈值去噪和R波峰值定位方法,对心电信号高频噪声不同信噪比情况做了去噪处理,并同小波熵最优阈值法做了对比分析,结果表明,本算法可以自适应地确定小波系数阈值,不需要直接处理大量的小波系数,且具有良好的滤波性能,尤其在噪声严重时,去噪和R波检测效果更优.最后对实测和数据库中46例数据都做了应用分析,表明本算法具有快速性、有效性和稳定性的特点.
위료재려제조성적동시불주실신호유용신식,장소파적이론여소파역치거조방법종합기래,제출일충기우소파적적자괄응역치거조화R파봉치정위방법,대심전신호고빈조성불동신조비정황주료거조처리,병동소파적최우역치법주료대비분석,결과표명,본산법가이자괄응지학정소파계수역치,불수요직접처리대량적소파계수,차구유량호적려파성능,우기재조성엄중시,거조화R파검측효과경우.최후대실측화수거고중46례수거도주료응용분석,표명본산법구유쾌속성、유효성화은정성적특점.
For keeping the available information of a signal when removing noise,a novel adaptive threshold filter and R wave detection method based on wavelet entropy is proposed,which combines the wavelet entropy theory with the threshold wavelet denoising method.Then the high-frequency noise with different SNR in the ECC signal is analyzed by this methocLAnd the analysis is done compared with the optimal threshold wavelet entropy denoising method.The results indicate that the arithmetic can adaptively confirm the wavelet coefficients threshold and it needn't dispose the large numbers of wavelet coefficients directly.At the same time,it has an excellent filter performance and especially more effective in serious noisy situations.At last,the proposed method is verified using the clinical data and the data from MIT-BIH arrhythmia database.It shows that this method is simple,effective and stable.