• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>2017 IEEE Calcutta Conference >A novel spectrogram based approach towards automatic lung sound cycle extraction
【24h】

A novel spectrogram based approach towards automatic lung sound cycle extraction

机译：一种基于频谱图的新型肺音循环自动提取方法

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Automatic lung sound cycle extraction is the pivotal step for automated lung status detection as well as in monitoring the chronic lung diseases. In recent works, an attempt has been made to get rid of the additional airflow sensors due to their inaccuracy, patient's discomfort, and extra cost. In this paper, we have proposed a novel signal processing based approach to automatically extract lung sound cycles. In this framework, spectrograms are used as images to get the trend of the lung sound cycles without the need for identifying the corresponding respiratory phases or use of any reference airflow signal. We have utilized the lung sounds recorded from 8 healthy and 24 diseased subjects (8 subjects each from Asthma, COPD, and DPLD) to develop and evaluate the proposed lung sound cycle extraction algorithm. We employ a 4-fold cross-validation in our study and the average accuracy of 98.62% is found.
机译：自动肺音循环提取是自动检测肺部状态以及监测慢性肺部疾病的关键步骤。在最近的工作中，由于它们的不准确性，患者的不适感和额外的费用，已经尝试摆脱额外的气流传感器。在本文中，我们提出了一种基于信号处理的新颖方法来自动提取肺音周期。在此框架中，将频谱图用作图像以获取肺部声音循环的趋势，而无需识别相应的呼吸相位或使用任何参考气流信号。我们已经利用从8名健康和24名患病受试者（哮喘，COPD和DPLD中的8名受试者）记录的肺音来开发和评估建议的肺音循环提取算法。我们在研究中采用了4倍交叉验证，发现平均准确性为98.62％。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号