HEALTH MONITORING SYSTEM

Abstract

ABSTRACT A health monitoring system (100), comprising plurality of wearable sensors (102) configured to detect and measure physiological data, including heart rate, blood pressure, and body temperature, from a patient, a microcontroller (104) coupled to the wearable sensors, the microcontroller processes the physiological data and transmits the data wirelessly to a cloud-based platform, a machine learning module (106) hosted on the cloud-based platform, programmed to analyse the physiological data in real-time, identify patterns, and detect potential health abnormalities based on pre-trained machine learning algorithms; and an alert module (108) that generates alerts based on the detected health abnormalities and transmits the alerts to a healthcare provider or the patient’s mobile device for prompt intervention. <>

Specification

Description:FIELD OF THE DISCLOSURE
[0001] This invention generally relates to health monitoring systems, and more specifically, to an Internet of Things (IoT) and machine learning-based health monitoring system for real-time data collection and analysis.
BACKGROUND

[0002] The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to implementations of the claimed technology.
[0003] Monitoring health remotely has become an essential part of modern healthcare, especially as health services move toward patient-centric, preventive care. Wearable devices enable continuous tracking of vital signs, such as h , Claims:1. A health monitoring system (100), comprising:
plurality of wearable sensors (102) configured to detect and measure physiological data, including heart rate, blood pressure, and body temperature, from a patient;
a microcontroller (104) coupled to the wearable sensors, wherein the microcontroller processes the physiological data and transmits the data wirelessly to a cloud-based platform;
a machine learning module (106) hosted on the cloud-based platform, programmed to analyse the physiological data in real-time, identify patterns, and detect potential health abnormalities based on pre-trained machine learning algorithms; and
an alert module (108) that generates alerts based on the detected health abnormalities and transmits the alerts to a healthcare provider or the patient's mobile device for prompt intervention.

2. The health monitoring system (100) as claimed in claim 1, wherein the machine learning module is configured to use a combination of Support Vector Machine (SVM) and Random Forest algorithms t

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