Smart Health Band for Epilepsy and Seizure, Fits Detection with Alert System and Live Location using IoT and Cloud Computing

Millions of people worldwide suffer from the neurological condition known as epilepsy. The health of patients depends on the prompt identification of epileptic seizures, and technology can be very helpful in this respect. We present a smart health band in this conference article that interfaces with an ESP8266 Node MCU, uses a number of sensors (BMP280, MAX30102, IR, DHT11, LDR, and an OLED display), and interacts with MATLAB for data processing and analysis.Epilepsy is a neurological condition that impacts millions globally, making the prompt identification of seizures essential for patient care. In this conference paper, we introduce an innovative health band designed to continuously monitor vital parameters, including heart rate, oxygen levels, temperature, humidity, and ambient light through a range of sensors. The data collected in real-time is analyzed using MATLAB algorithms to detect patterns that may indicate an impending seizure. Upon detection, the health band activates an alert system that notifies caregivers or healthcare professionals, providing them with the patient's current location. The alert system of the smart health band is crafted to ensure efficiency and effectiveness, delivering timely notifications through multiple communication methods. The patient's location is determined using GPS or Wi-Fi positioning, facilitating rapid response and intervention during seizure events. Furthermore, the health band leverages cloud computing for data storage and analysis, allowing for remote health monitoring and access. This proposed system presents a holistic approach to epilepsy management and seizure detection, featuring an integrated alert mechanism and real-time location tracking through IoT and cloud technologies. By employing various sensors connected to an ESP8266 Node MCU and utilizing MATLAB for data processing, this system offers a reliable and precise method for seizure detection. The smart health band has the potential to greatly enhance the quality of life for individuals with epilepsy, ensuring their safety through timely alerts and accurate location information.

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Publication Details

Published
2024-11-23
DOI
https://doi.org/10.1109/icicat62666.2024.10923282
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
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article

Smart Health Band for Epilepsy and Seizure, Fits Detection with Alert System and Live Location using IoT and Cloud Computing

Ankit Sharma, Prashant Pandey, Ashok Kumar Tiwari, Kavita Mishra et al.
EEG and Brain-Computer Interfaces
article

Smart Health Band for Epilepsy and Seizure, Fits Detection with Alert System and Live Location using IoT and Cloud Computing

Ankit Sharma, Prashant Pandey, Ashok Kumar Tiwari, Kavita Mishra, Vishal Bind, Jayprakash
article en

Abstract

Millions of people worldwide suffer from the neurological condition known as epilepsy. The health of patients depends on the prompt identification of epileptic seizures, and technology can be very helpful in this respect. We present a smart health band in this conference article that interfaces with an ESP8266 Node MCU, uses a number of sensors (BMP280, MAX30102, IR, DHT11, LDR, and an OLED display), and interacts with MATLAB for data processing and analysis.Epilepsy is a neurological condition that impacts millions globally, making the prompt identification of seizures essential for patient care. In this conference paper, we introduce an innovative health band designed to continuously monitor vital parameters, including heart rate, oxygen levels, temperature, humidity, and ambient light through a range of sensors. The data collected in real-time is analyzed using MATLAB algorithms to detect patterns that may indicate an impending seizure. Upon detection, the health band activates an alert system that notifies caregivers or healthcare professionals, providing them with the patient's current location. The alert system of the smart health band is crafted to ensure efficiency and effectiveness, delivering timely notifications through multiple communication methods. The patient's location is determined using GPS or Wi-Fi positioning, facilitating rapid response and intervention during seizure events. Furthermore, the health band leverages cloud computing for data storage and analysis, allowing for remote health monitoring and access. This proposed system presents a holistic approach to epilepsy management and seizure detection, featuring an integrated alert mechanism and real-time location tracking through IoT and cloud technologies. By employing various sensors connected to an ESP8266 Node MCU and utilizing MATLAB for data processing, this system offers a reliable and precise method for seizure detection. The smart health band has the potential to greatly enhance the quality of life for individuals with epilepsy, ensuring their safety through timely alerts and accurate location information.

Madan Mohan Malaviya University of Technology (IN)
Good health and well-being
Openalex Percentile: Top 72%
EEG and Brain-Computer Interfaces
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