ICA在肠鸣音信号处理中的应用研究

Research of Independent Component Analysis for Processing Bowel Sounds

目的:肠鸣音的去噪及时域特征提取。方法:本文首先分析了独立分量分析的基本原理,研究了FastICA算法,并给出了此算法的具体实现步骤。然后利用该方法对肠鸣音进行了处理,并用归一化平均香农能量分布提取了肠鸣音的时域特征。结果:上述方法有效地去除了肠鸣音信号中的噪声,发现正常音与异常音的时域特征存在典型差异。结论:肠鸣音的检测和处理在胃肠道疾病的诊断治疗中具有重要的价值,实验结果可以看出独立分量分析在肠鸣音信号处理中是非常有效的。

Objective： To eliminate the noise merged in bowel sounds and extract the time-domain features of the main signal. Methods： In this paper, the principles of Independent Conponent Analysis （ICA） were investigated; the algorithm of FastlCA was discussed; the step of ICA was given. Then we processed the bowel sounds with this method, and extracted the time-domain features with normalized average Shannon energy, representative differences were found between the normal and abnormal signals. Results： The noise merged in bowel sounds is eliminated and there are statistical differences between the normal and abnormal bowel sounds. Conclusions： Detection and analysis of bowel sounds has important value in the diagnosis and cure of gastrointestinal diseases, the experimental results show that ICA is an effective method for processing bowel sounds.