Barschdorff D, Ester S, Dorsel T, Most E
St. Vincenz Krankenhaus Paderborn, Universität-GH Paderborn, Fachgebiet Elektrische Messtechnik.
Biomed Tech (Berl). 1990 Nov;35(11):271-9. doi: 10.1515/bmte.1990.35.11.271.
New approaches to pattern recognition and modeling using neural networks also provide powerful tools for the analysis of heart sounds in the diagnosis of heart failure. This paper describes how a neutral network can be used to estimate the duration of systolic and diastolic heart phases as well as to suggest a suitable diagnosis. A neural network-based auscultation system is capable of documenting and analysing a heart sound signal by applying methods similar to those used by physicians in the subjective interpretation of stethoscopic signals.
使用神经网络进行模式识别和建模的新方法,也为心力衰竭诊断中的心音分析提供了强大工具。本文描述了如何使用神经网络来估计心脏收缩期和舒张期的持续时间,并提出合适的诊断建议。基于神经网络的听诊系统,能够通过应用类似于医生主观解读听诊信号时所使用的方法,来记录和分析心音信号。