IOT Based Non-Invasive Blood Glucose Blood Pressure and Pulse Monitoring System

Abstract

This project involves the design of a non-invasive health monitoring system. The system will have the capability to measure blood sugar, blood pressure, pulse rate, and body temperature. The design involves the use of Internet of Things (IoT) for real-time continuous monitoring. This is especially useful for patients suffering from chronic diseases such as diabetes and high blood pressure. The design uses a central processing unit, ESP32, connected to non-invasive sensing devices. These devices are an infrared sensor for sugar measurement, a photoplethysmography sensor for pulse as well as blood pressure measurement, and a digital temperature sensor for body temperature. The signals obtained are processed by signal conditioning methods. This will ensure accurate measurement. The measured values are then displayed on an LCD display. The data is also sent to the cloud. This makes it possible for remote monitoring by healthcare providers or caregivers using a web page or mobile apps. This device, being portable, handheld, and easy to operate, has immense prospective uses for personal healthcare assistance, ultimately resulting in less visitations to healthcare institutions.

Introduction

Chronic diseases like diabetes, hypertension, and heart conditions require continuous monitoring of biological parameters such as blood sugar, blood pressure, pulse rate, and body temperature. Traditional monitoring methods are often invasive, inconvenient, and impractical in remote areas. Advances in sensor technology and IoT have enabled the development of non-invasive, real-time health monitoring systems.

This project presents an IoT-based non-invasive health monitoring device using an ESP32 microcontroller. The system measures pulse rate, blood pressure, glucose level, and body temperature using sensors like MAX30102, TCRT1000, and LM35, displays the results on an LCD, and uploads the data to the Blynk IoT platform for remote monitoring. The device aims to provide continuous preventive healthcare, early anomaly detection, and remote access for caregivers or medical professionals.

Methodology:

• Pulse Rate: Measured via photoplethysmography (PPG) using MAX30102.

• Blood Pressure: Estimated using Pulse Transit Time (PTT) derived from PPG signals.

• Glucose Level: Measured using an IR-based sensor with regression-based estimation.

• Body Temperature: Measured with LM35/MLX90614 sensors and corrected for skin-to-body offset.

• Data is processed by ESP32, displayed locally, and sent to the cloud in real time.

Results:

• Overall accuracy: ~92%, with high precision for SpO? and blood pressure. Minor deviations in temperature, heart rate, and glucose due to sensor limitations.

• Real-time updates with negligible delay, confirming stable wireless communication.

• Errors attributed to sensor placement, motion artifacts, sensor noise, and non-invasive estimation approximations.

Conclusion

The Non-Invasive Health Monitoring System using IoT is highly effective in measuring important health variables like blood glucose, blood pressure, pulse rate, and body temperature without going under invasive processes. By making use of ESP32 and Blynk IoT cloud, remote monitoring is established on a mobile platform. This is highly beneficial from a safety and comfort aspect of patients and also gives them better accessibility to health care. This project provides an innovative and convenient solution in wireless health care.

References

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Copyright

Copyright © 2025 Rajashree R, Rashmi J, Raksha M, Rimsha Anwar, Prof. Pratik Shankar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.