Paper Title
DESIGN AND DEVELOPMENT OF A STANDALONE BIOMEDICAL SYSTEM TO DETERMINE PATIENT’S HEALTH CONDITION USING MACHINE LEARNING

Abstract
The modern patient monitoring system is the integration of biomedical parameters and machine learning algorithms. This paper presents a biomedical device integrating sensors like Heart Rate/SpO2 sensor, Temperature sensor, Blood Pressure monitoring device and machine learning for health monitoring. Multiple linear regression and ANOVA identified relations between significant parameters like age, weight, gender, medical history, blood pressure, pulse pressure, SpO2 and heart rate for predicting health status. Decision tree algorithms categorized subjects into different health levels based on vital parameters. The system demonstrated accurate prediction with low error rates, highlighting its potential for reliable, personalized healthcare monitoring. Keywords - Health Status, Machine Learning, Multiple Linear Regression, Decision Tree Algorithm