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The Journal of Supercomputing

Erschienen in:

04.10.2019

A new healthcare diagnosis system using an IoT-based fuzzy classifier with FPGA

verfasst von: Sambit Satpathy, Prakash Mohan, Sanchali Das, Swapan Debbarma

Erschienen in: The Journal of Supercomputing | Ausgabe 8/2020

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Abstract

In this study, an Internet of Things (IoT)-based analysis system is proposed, which can be used to design a consumer electronic device. This IoT-based analysis system will alert the user when any of the parameters related to his/her health is above or below the normal range. The data collected using this system are uploaded to the cloud using a mobile application and then transferred to the field-programmable gate array (FPGA) analysis system. The raw data are computed and processed by the FPGA system, and pathological conditions are displayed on the patient’s wearable IoT device. The novelty of this work lies in the development of a fuzzy classifier, which indicates the pathological conditions of diseases with a higher accuracy. The FPGA implementation of the fuzzy classifier results in a lower execution time in comparison with that of previous models, such as K-nearest neighbour, decision tree, support vector machine, and naive Bayes.

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Titel: A new healthcare diagnosis system using an IoT-based fuzzy classifier with FPGA
verfasst von: Sambit Satpathy
Prakash Mohan
Sanchali Das
Swapan Debbarma
Publikationsdatum: 04.10.2019
Verlag: Springer US
Erschienen in: The Journal of Supercomputing / Ausgabe 8/2020
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-019-03013-2

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