Pareeksh

A health diagnosis system using IOT for early detection and prevention

https://doi.org/10.53730/ijhs.v6nS3.9116

Authors

  • Narendra Kumar Assistant Professor Department of Electronics and Communication R.N.S Institute of Technology, Bengaluru Karnataka India 560098
  • K. B. Ramesh Associate Professor Department of Electronics and Instrumentation RV college of Engineering, Bengaluru Karnataka
  • Madhusudhan K. N. Assistant Professor Department of Electronics and Communication BMS Institute of Technology, Bengaluru Karnataka

Keywords:

naadisignal, ppg signal, ECG signal SVM, KNN algorithms, diagnosis, detection

Abstract

The changes in the body conditions are reflected in the flow of blood throughout the body. These changes can be measured as body signals using appropriate sensors. With an improvement in technology and miniaturization of sensors, the healthcare sector has witnessed significant advancement over the years. The signals measured by such sensors carry important information regarding a person’s health and this paper presents a method to utilize the same.The signals acquired from the PPG and ECG sensors are filtered and denoised. Statistical analysis is performed on these signals and important features are extracted. This set of features are given to a trained machine learning model which produces the classifications that confirm the health status of the subject for further investigations.

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Published

17-06-2022

How to Cite

Kumar, N., Ramesh, K. B., & Madhusudhan, K. N. (2022). Pareeksh: A health diagnosis system using IOT for early detection and prevention. International Journal of Health Sciences, 6(S3), 12156–12169. https://doi.org/10.53730/ijhs.v6nS3.9116

Issue

Section

Peer Review Articles