首页|睡眠期间肠鸣音信号的鼾声噪声去除方法

睡眠期间肠鸣音信号的鼾声噪声去除方法

扫码查看
肠鸣音监测是评估睡眠期间肠动力的重要方法,但会受到鼾声噪声的严重影响.本文将自适应噪声的完备集合经验模态分解(CEEMDAN)方法用于睡眠期间肠鸣音的鼾声噪声去除.具体地,先对带噪肠鸣音进行带通滤波,然后使用CEEMDAN方法分解,最后选择适当的分量重构纯净肠鸣音.半模拟数据和真实数据验证表明,与普通的经验模式分解和小波去噪方法相比,CEEMDAN方法能更有效地去除鼾声噪声.CEEMDAN方法用于睡眠期间肠鸣音鼾声噪声去除,可为肠鸣音用于睡眠期间肠动力评估奠定重要基础.
Snoring noise removal method for bowel sound signal during sleep
Monitoring of bowel sounds is an important method to assess bowel motility during sleep,but it is seriously affected by snoring noise.In this paper,the complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)method was applied to remove snoring noise from bowel sounds during sleep.Specifically,the noisy bowel sounds were first band-pass filtered,then decomposed by the CEEMDAN method,and finally the appropriate components were selected to reconstruct the pure bowel sounds.The results of semi-simulated and real data showed that the CEEMDAN method was better than empirical mode decomposition and wavelet denoising method.The CEEMDAN method is used to remove snoring noise from bowel sounds during sleep,which lays an important foundation for using bowel sounds to assess the intestinal motility during sleep.

Bowel soundsSnoring noiseComplete ensemble empirical mode decomposition with adaptive noiseDenoising

王国静、王卫东、刘洪运

展开 >

北京航空航天大学生物与医学工程学院(北京 100191)

中国人民解放军总医院医学创新研究部(北京 100853)

中国人民解放军总医院工业和信息化部生物医学工程与转化医学重点实验室(北京 100853)

肠鸣音 鼾声 自适应噪声的完备集合经验模态分解 去噪

科技创新2030"新一代人工智能"项目

2020AAA0105800

2024

生物医学工程学杂志
四川大学华西医院 四川省生物医学工程学会

生物医学工程学杂志

CSTPCD北大核心
影响因子:0.432
ISSN:1001-5515
年,卷(期):2024.41(2)
  • 22