Personalized Exercise Program Design with Machine Learning in Sensor Networks

Authors

  • Yan Lu School of Physical Education, University of Sanya, Sanya 572000, China

DOI:

https://doi.org/10.12694/scpe.v24i4.2440

Keywords:

Clinical trials, EHRs, sensor based software for health development, challenges of ML and DSN

Abstract

The use of wearable solutions and sensors has reached the point of modern machine learning (ML) techniques in recent years. It contains the different programs that help to develop personalized opportunities for the betterment of the individuals. The research shed light upon the functions of ML and distributed sensor networks (DSN) in promoting healthcare among users. It can be said that the functions of the ML help to develop good fitness among the users, which results in good health. This dissertation consists of different kinds of ML algorithms and the usage of DSNs for the development of physical exercise programs. It has been found that most individuals use the sensors for their benefit in developing good health. The use of machine learning techniques not only helps to record an individual's health data but also sends emergency information to the nearest medical center for the user's benefit. The use of ML helps to the identification of the location of an individual with the help of GPS measures of real-time distance and users' health activities.

Downloads

Published

2023-11-17

Issue

Section

Special Issue - Scalability and Sustainability in Distributed Sensor Networks