• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Electrotechnical Conference (MELECON), 2012 16th IEEE Mediterranean >Classification of multichannel uterine EMG signals by using a weighted majority voting decision fusion rule
【24h】

Classification of multichannel uterine EMG signals by using a weighted majority voting decision fusion rule

机译：基于加权多数投票决策融合规则的多通道子宫肌电信号分类

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

Recording the bioelectrical signals by using multiple sensors has been the subject of considerable research effort in the recent years. The multisensor recordings have opened the way to the application of more advanced signal processing techniques and the extraction of new parameters. The focus of this paper is to demonstrate the importance of multisensor recordings for classifying multichannel uterine EMG signals recorded by 16 electrodes. First, we showed that mapping the characteristics of the multichannel uterine EMG signals may allow to set some peculiar properties of these channels. Then, data recorded from each channel were individually classified. Based on the variability between the classification performances of each channel, a weighted majority voting (WMV) decision fusion rule was applied. The classification network yielded better classification accuracy than any individual channel could provide. We conclude that our multichannel-based approach can be very useful to gain insight into the modification of the uterine activity and can improve the classification accuracy of pregnancy and labor contractions.
机译：近年来，通过使用多个传感器来记录生物电信号一直是大量研究工作的主题。多传感器记录为更先进的信号处理技术的应用和新参数的提取开辟了道路。本文的重点是证明多传感器记录对于分类由16个电极记录的多通道子宫EMG信号的重要性。首先，我们表明，映射多通道子宫EMG信号的特征可以允许设置这些通道的某些特殊属性。然后，将从每个通道记录的数据分别进行分类。基于每个通道的分类性能之间的差异，应用了加权多数投票（WMV）决策融合规则。分类网络产生的分类精度比任何单个渠道都可以提供的更好。我们得出的结论是，基于多通道的方法对于深入了解子宫活动的改变非常有用，并且可以提高妊娠和分娩收缩的分类准确性。

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