IOT System for Detecting Epileptic Seizures Based on Fuzzy Logic
Epilepsy affects around 50 million people globally and is marked by unpredictable seizures due to abnormal neural activities in the brain. With nearly 30% of epilepsy patients experiencing drug-resistant seizures, there is a crucial need for effective seizure detection. This paper focuses on the ch...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wasit University
2025-06-01
|
| Series: | Wasit Journal of Engineering Sciences |
| Subjects: | |
| Online Access: | https://ejuow.uowasit.edu.iq/index.php/ejuow/article/view/587 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850100551665057792 |
|---|---|
| author | Jehan A. abbas Manaf K. Hussei Riyadh A. Abbas |
| author_facet | Jehan A. abbas Manaf K. Hussei Riyadh A. Abbas |
| author_sort | Jehan A. abbas |
| collection | DOAJ |
| description |
Epilepsy affects around 50 million people globally and is marked by unpredictable seizures due to abnormal neural activities in the brain. With nearly 30% of epilepsy patients experiencing drug-resistant seizures, there is a crucial need for effective seizure detection. This paper focuses on the challenge of predicting seizures to enable preventive actions. To achieve this the proposed system utilizes the STM32F103C8T6 microcontroller to process data from a 3-axis accelerometer, heart rate sensor and temperature sensor. The collected data is analysed using a fuzzy logic algorithm in MATLAB to interpret sensor readings for identifying seizures. When a possible seizure is detected, notifications are sent through GSM along with the patient’s location provided by GPS. Additionally, the system explores seizure detection methods device’s role in health monitoring and IoT integration in healthcare, with an accuracy rate of 94%. This work contributes to the field of healthcare technology by offering an innovative solution for continuous and automated monitoring of epilepsy patients, ultimately aiming to improve patient safety and quality of life.
|
| format | Article |
| id | doaj-art-bb371d81b23b41b8a975c043b69d2f43 |
| institution | DOAJ |
| issn | 2305-6932 2663-1970 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Wasit University |
| record_format | Article |
| series | Wasit Journal of Engineering Sciences |
| spelling | doaj-art-bb371d81b23b41b8a975c043b69d2f432025-08-20T02:40:17ZengWasit UniversityWasit Journal of Engineering Sciences2305-69322663-19702025-06-0113210.31185/wjes.Vol13.Iss2.587IOT System for Detecting Epileptic Seizures Based on Fuzzy LogicJehan A. abbas 0Manaf K. Hussei1Riyadh A. Abbas2Department of Electrical Engineering, College of Engineering, University of Wasit, Wasit, Iraq.Department of Electrical Engineering, College of Engineering, University of Wasit, Wasit, IraqDepartment of Electrical Engineering, College of Engineering, University of Wasit, Wasit, Iraq Epilepsy affects around 50 million people globally and is marked by unpredictable seizures due to abnormal neural activities in the brain. With nearly 30% of epilepsy patients experiencing drug-resistant seizures, there is a crucial need for effective seizure detection. This paper focuses on the challenge of predicting seizures to enable preventive actions. To achieve this the proposed system utilizes the STM32F103C8T6 microcontroller to process data from a 3-axis accelerometer, heart rate sensor and temperature sensor. The collected data is analysed using a fuzzy logic algorithm in MATLAB to interpret sensor readings for identifying seizures. When a possible seizure is detected, notifications are sent through GSM along with the patient’s location provided by GPS. Additionally, the system explores seizure detection methods device’s role in health monitoring and IoT integration in healthcare, with an accuracy rate of 94%. This work contributes to the field of healthcare technology by offering an innovative solution for continuous and automated monitoring of epilepsy patients, ultimately aiming to improve patient safety and quality of life. https://ejuow.uowasit.edu.iq/index.php/ejuow/article/view/587Internet of Things (IoT) Epilepsy; Epileptic seizure detection; Fuzzy logic inference; wearable device. |
| spellingShingle | Jehan A. abbas Manaf K. Hussei Riyadh A. Abbas IOT System for Detecting Epileptic Seizures Based on Fuzzy Logic Wasit Journal of Engineering Sciences Internet of Things (IoT) Epilepsy; Epileptic seizure detection; Fuzzy logic inference; wearable device. |
| title | IOT System for Detecting Epileptic Seizures Based on Fuzzy Logic |
| title_full | IOT System for Detecting Epileptic Seizures Based on Fuzzy Logic |
| title_fullStr | IOT System for Detecting Epileptic Seizures Based on Fuzzy Logic |
| title_full_unstemmed | IOT System for Detecting Epileptic Seizures Based on Fuzzy Logic |
| title_short | IOT System for Detecting Epileptic Seizures Based on Fuzzy Logic |
| title_sort | iot system for detecting epileptic seizures based on fuzzy logic |
| topic | Internet of Things (IoT) Epilepsy; Epileptic seizure detection; Fuzzy logic inference; wearable device. |
| url | https://ejuow.uowasit.edu.iq/index.php/ejuow/article/view/587 |
| work_keys_str_mv | AT jehanaabbas iotsystemfordetectingepilepticseizuresbasedonfuzzylogic AT manafkhussei iotsystemfordetectingepilepticseizuresbasedonfuzzylogic AT riyadhaabbas iotsystemfordetectingepilepticseizuresbasedonfuzzylogic |