Cardiac Data Compression for Reduced Traffic on Application of IoMT

Sudeshna Baliarsingh, Saumendra Kumar Mohapatra, Prakash Kumar Panda, M. Mohanty
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引用次数: 4

Abstract

The Internet of things (IoT) has a great role to provide the recent technology including the applications in the area of Health care, Engineering, smart societies and many different human activities. It needs the compliant for the Artificial Intelligence of Medical things (AIoMT). Among all the processes including the signal processing, communication and Machine Learning, data compression playing an important role to satisfy all these applications. We have considered the Arrhythmia ECG data for compression using different transforms. The data is collected from the physio-net data base. Its performance using wavelet transform found suitable in terms of noise suppression, multiband filtering and compression encoding. Further to satisfy IoT based communication wavelet Packet Transform (WPT) is utilised to develop the model for multicarrier communication. From the result it is observed that it can be useful for Medical professionals as well as the patients from the remote places.
应用IoMT减少流量的心脏数据压缩
物联网(IoT)在提供最新技术方面发挥着重要作用,包括在医疗保健,工程,智能社会和许多不同的人类活动领域的应用。它需要符合医疗物的人工智能(AIoMT)。在包括信号处理、通信和机器学习在内的所有过程中,数据压缩扮演着重要的角色,以满足所有这些应用。我们考虑了心律失常心电数据的压缩使用不同的变换。数据是从physio-net数据库中收集的。小波变换在噪声抑制、多频带滤波和压缩编码等方面表现良好。为了满足基于物联网的通信需求,利用小波包变换(WPT)建立了多载波通信模型。从结果来看,它对医疗专业人员以及来自偏远地区的患者都是有用的。
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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