利用机器学习和物联网预测压力

Amit Jain, Muskan Kumari
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引用次数: 0

摘要

压力被认为是医疗保健中的主要问题。本文简要回顾了机器学习算法和物联网,以及它们在应力预测中的作用。研究者在压力预测方面做了大量的研究,参考前人的研究,我们在感知压力量表(PSS)、EDR和ECG的基础上,比较了SVM和KNN的准确率和性能。本文讨论了目前在物联网(IoT)上实现的机器学习技术。此外,重点是确定压力的原因,症状以及研究与压力相关的现有机器学习算法。
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Prediction of Stress using Machine Learning and IoT
Stress is considered as the leading problem in healthcare. This paper is about a brief review of machine learning Algorithms and IoT, and their roles in the prediction of stress. A lot of research has been done by researchers in the prediction of stress by taking reference to previous research we compare SVM and KNN accuracy and performanceon the basis of PSS (perceived stress scale), EDR and ECG. This paper discusses ML Techniques that are implemented on the Internet of things (IoT) nowadays. Also, emphasis has been laid on identifying the causes, symptoms of stress along with studying the existing Machine Learning algorithms related to Stress.
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