福建电脑2025，Vol.41Issue(7)：22-26,5.DOI:10.16707/j.cnki.fjpc.2025.07.005
DBN神经网络的异常心音检测方法研究
Research on Abnormal Heart Sound Detection Method Based on DBN Neural Network
马启良1
作者信息
- 1. 枣庄学院光电工程学院 山东 枣庄 277160
- 折叠
摘要
Abstract
In response to the problems of complex models,large amounts of feature data,and difficulty in deploying on mobile devices with limited computing resources in existing methods for detecting abnormal heart sounds,this paper proposes a lightweight abnormal heart sound detection algorithm based on hidden semi Markov models and deep belief networks.Using HSMM for precise segmentation of heart sound signals and extracting feature values from multiple dimensions such as time and amplitude reduces the amount of feature data.The experimental results show that the accuracy of this algorithm reaches 0.886,which is 34 times faster than mainstream algorithms while maintaining similar accuracy.关键词
异常心音检测/轻量化算法/智能穿戴设备Key words
Abnormal Heart Sound Detection/Lightweight Algorithm/Smart Wearable Devices分类
信息技术与安全科学引用本文复制引用
马启良..DBN神经网络的异常心音检测方法研究[J].福建电脑,2025,41(7):22-26,5.
