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基于心动周期估计的心音分割及异常心音筛查算法

赵湛 张旭茹 方震 陈贤祥 杜利东 李田昌

赵湛, 张旭茹, 方震, 陈贤祥, 杜利东, 李田昌. 基于心动周期估计的心音分割及异常心音筛查算法[J]. 电子与信息学报, 2017, 39(11): 2677-2683. doi: 10.11999/JEIT170108
引用本文: 赵湛, 张旭茹, 方震, 陈贤祥, 杜利东, 李田昌. 基于心动周期估计的心音分割及异常心音筛查算法[J]. 电子与信息学报, 2017, 39(11): 2677-2683. doi: 10.11999/JEIT170108
ZHAO Zhan, ZHANG Xuru, FANG Zhen, CHEN Xianxiang, DU Lidong, LI Tianchang. Phonocardiogram Segmentation and Abnormal Phonocardiogram Screening Algorithm Based on Cardiac Cycle Estimation[J]. Journal of Electronics & Information Technology, 2017, 39(11): 2677-2683. doi: 10.11999/JEIT170108
Citation: ZHAO Zhan, ZHANG Xuru, FANG Zhen, CHEN Xianxiang, DU Lidong, LI Tianchang. Phonocardiogram Segmentation and Abnormal Phonocardiogram Screening Algorithm Based on Cardiac Cycle Estimation[J]. Journal of Electronics & Information Technology, 2017, 39(11): 2677-2683. doi: 10.11999/JEIT170108

基于心动周期估计的心音分割及异常心音筛查算法

doi: 10.11999/JEIT170108
基金项目: 

国家自然科学基金(61302033),北京市自然科学基金(Z160003),国家重点研发计划(2016YFC1304302, 2016YFC0206502, 2016YFC1303900)

Phonocardiogram Segmentation and Abnormal Phonocardiogram Screening Algorithm Based on Cardiac Cycle Estimation

Funds: 

The National Natural Science Foundation of China (61302033), The Beijing Municipal Natural Science Foundation (Z160003), The National Key Research and Development Project (2016YFC1304302, 2016YFC0206502, 2016YFC1303900)

  • 摘要: 心脏疾病是全球发病率和死亡率最高的疾病,心音听诊可以获取心脏的机械特性及结构特征,与超声心动图、核磁共振等无创诊断技术相比具有快速、低成本和操作简单的优势。心音信号成分复杂,容易受到各种噪声和干扰的影响,听诊诊断结果容易受到医生主观性的影响,极大限制了心音听诊的应用。该文提出一种基于心动周期估计的心音分割及异常心音筛查算法,预先估计了心音的心动周期,存在随机干扰的情况下也可以正确识别信号中80%以上的心动周期,提高了算法的稳定性。同时提出了区分度良好的时域和频域特征指标,利用支持向量机建模,对异常心音的识别率可达92%。算法可辅助医生诊断,或用于家用便携式心音监护设备。
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出版历程
  • 收稿日期:  2017-02-10
  • 修回日期:  2017-04-20
  • 刊出日期:  2017-11-19

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