Remote Diagnosis of Heart Disease Using Telemedicine

Megh Doshi, Maitri Fafadia, Stutee Oza, Amit A. Deshmukh, Shruti T. Pistolwala
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引用次数: 1

Abstract

In recent years, telemedicine has been a newly emerging field of technology, systems which aid in remote diagnosis have become a need of the hour. With the population increasing at an alarming rate, an efficient system for rapid and efficient diagnosis is imperative. In this paper we have performed a survey analysis of the existing systems of this sort, and we have performed partial implementation of our own proposed system which is a tool for assisted diagnosis of heart disease through telemedicine. Our proposed system, is a setup for remote diagnosis of patients in rural or non-accessible areas, such as isolated military camps or accident sites where specialized diagnosis and treatment is difficult to get. We have proposed a low-cost solution which comprises of a self-designed digital stethoscope which records and amplifies heart sounds to give us the phonocardiogram i.e. the PCG of the patient, and it classifies these sounds as normal or abnormal. The broad and significant highlights to build this system include- diaphragm as primary sensor for data acquisition from the subject; the data processing and its classification is based on Neural Network using Matlab as the IDE. Neural network used for this application utilizes unsupervised learning i.e it classifies data to inherent structure from input data and no pre-categorization is provided to it. Fine-KNN is classification algorithm in Neural Network that separates the data points into various class with respect to each other's similarities. Even classes are clustered based on similarity of neurons in the neighborhood. Further, this data is communicated to a specialist i.e. a cardiologist in this case, in the cityalong with the patient history for further investigation and the expert medical advice of the specialist is relayed back to the patient, or the doctor at the remote location. Our proposed setup also provides features like having live video conversations with medical experts and a unique identification system along with a fingerprint activated security system.
利用远程医疗对心脏病进行远程诊断
近年来,远程医疗是一个新兴的技术领域,辅助远程诊断的系统已成为一种需要。随着人口以惊人的速度增长,一个快速有效诊断的有效系统是必不可少的。在本文中,我们对现有的此类系统进行了调查分析,并对我们自己提出的通过远程医疗辅助心脏病诊断的系统进行了部分实现。我们提出的系统是为农村或交通不便地区的患者提供远程诊断的设置,例如孤立的军营或事故现场,这些地区难以获得专门的诊断和治疗。我们提出了一个低成本的解决方案,包括一个自行设计的数字听诊器,它可以记录和放大心音,为我们提供病人的心音图,即PCG,并将这些声音分为正常或异常。构建该系统的广泛和重要的亮点包括-膜片作为主要传感器从主体采集数据;数据处理和分类是基于神经网络的,使用Matlab作为IDE。用于此应用程序的神经网络利用无监督学习,即它从输入数据中将数据分类为固有结构,而不提供预分类。Fine-KNN是神经网络中的一种分类算法,它将数据点根据彼此的相似度划分为不同的类别。甚至类是基于邻近神经元的相似性聚类的。此外,这些数据将与患者病史一起传送给该市的专家,即心脏病专家进行进一步调查,专家的专家医疗建议将传回给患者或偏远地区的医生。我们提议的设置还提供了一些功能,比如与医学专家进行实时视频对话,以及一个独特的识别系统和指纹激活的安全系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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