The document proposes a real-time smart epilepsy detection and alert system using IoT. It aims to help epilepsy patients avoid unpredictable violent seizures caused by sudden falling. The proposed system uses a heart rate sensor and MEMS accelerometer sensor to detect epileptic conditions. When a seizure is detected, an alarm is sounded and alerts are sent via messages to caregivers and doctors with the patient's location and details. The low-cost wearable device is designed to allow epilepsy patients to lead safer, more independent lives and receive quick help during seizures.

1. First Review
IOT based Automatic Detection And
Alert System for Epilepsy Patient
Guided By
Mr.T.JEYASEELAN AP/ECE
presented by

2. OBJECTIVE
 To design and develope a real time Smart epilepsy detection
and alert system.
To help Epilepsy patients to get quick recovery from epilesy
and to avoid unpredictable violent seizures caused by
sudden falling.

3. LITERATURE SURVEY
S.
NO
AUTHOR’S NAME TITLE&YEAR WORKDONE
1 1.Ms. A. Priya
2. Dr. B. Persis Urbana
Ivy,
3. Mr..M. Vigneshwaran
Design of Smart Alert
System for Epileptic
Seizure Detection
;2020
The proposed
technology will help
Epilepsy patient to lead
better and secured
lifestyle in their houses.
2 1.Ms.S.Archana,
2.K.Ammu,
3.S.Bhuvaneshwari
4 S.Tamilmozhi,
5 S.Vidhya
Real-Time Iot
Framework For
Epileptic Seizures
Detection And Alert
System&March 2019..
It is a weightless device,
rugged, affordable
wearable device which
helps millions of people
affected by epilepsy
around the world.

4. S.
no
Author’s
Name
Title & Year Work done
3. Aziis Yudha
Adwitiya,
David
Habsara
Hareva, Irene
Astuti
Lazarusli;
Epileptic Alert
System on
Smartphone;2019
Smartphones' motion sensors can be
utilized as alert system using “fall
detection” algorithm. It can drive SOS
alarm sound, then trigger Smartphone's
direct call and send text alert with GPS
coordinates information.;
4. M. Anil
kumar, S.
Kishore ,
N. Karthik ,
K. Chandra
sekhar ,
Shaik Shafi
,M.C.Chinna
ia
Realtime Epileptic
Seizures Detection
and Alert System
Using NI Lab-
View;2015
It will do the help in both the ways
means not only checks the condition but
also sends an SMS to the concerned
doctor for the patient’s live saving sake.
To implement all the above process we
have used mainly four modules micro
controller KEIL module, ARDUINO
module, GSM module to send an SMS,
and LABVIEW.

5. S.
no
Author’s Name Title & Year Work done
5. Mrs. M.janani,
Dr. B. ferrous,
Mr. M. Vinoth,
Design of Smart
Alert System for
Epileptic Seizure
Detection;2019
The abnormal activity in the brain
leads to seizures. It is diagnosed in
brain tumor patients, elderly
people affected by stroke. The
proposed system can act as a
“valueadded service” to them by
providing a comfortable and
confident lifestyle. Bringing out
such techno products for
utilization in India shall improve
their quality of life and
confidence.

6. EXISTING SYSTEM
Generate SMS alert when seizure is detected for an
epileptic patient to the caretaker. The system also alerts
the ambulance if seizure occurs prolong.
Existing system fail to predict sudden falling due to
epileptic.

7. Proposed System
The proposed technology will help epilepsy patient
to lead better and secured life style. The idea of the
system will clearly address and solve their
problems.
The system Even if a single seizure is left unnoticed
it may lead to a drastic problem in patient’s health
issue. Heart rate sensor and MEMS sensor detects
for seizure.

8. The proposed system uses Heart rate sensor and MEMS
accelerometer sensor to predict and detect epileptic
condition.
This proposed system will produce alarm sound and alert
by sending message to the caretakers and doctor about
the location,the patient details such as
name,address,details of consulting doctor and patients
diagonist historiy.
Muscle contractions are collected using micro
electromechanical sensors (MEMS) that are attached to
the body.

9. BLOCK DIAGRAM
k
ARDUINO
ATmega 328P
ESP 32
NODE MCU
Message
Mobile
Application
Thinkspeak
cloud
LCD Display
GSM Module
Pulse rate
GPS Module
BLYNK

10. Description
Pulse Rate Sensor
 The Pulse Sensor has a plug-and-play heart-rate sensor
for Arduino.
 It can be used by students, artists, athletes, makers, and
game & mobile developers who want to easily
incorporate live heart-rate data into their projects.
 It essentially combines a simple optical heart rate sensor
with amplification and noise cancellatio circuitry making
it fast and easy to get reliable pulse readings.

11. MEMS Sensor
 That device that is used to measure acceleration and the
force producing it.The capacitive MEMS accelerometer is
famous for its high sensitivity and its accuracy at high
temperatures.
 Due to its small size and robust sensing feature, they are
further developed to obtain multi-axis sensing One of the
most commonly used MEMS accelerometer.
 Hence it displays the output value on the LCD display

12. ESP 32 NODE MCU;
This board has 2.4GHz dual-mode wifi and BT wireless
connection.
In addtion,a 512kb SRAM and a 4MB flash memory are
integrted into the microcontroller development board.
The board has 21pins for interface
connection,including12c,SPI,UART,DAC,and ADC.
Thing Spaek cloud;
Thing Spaek is an IOT analytics patform service that
allows you to aggregate,visualize, and analyze live data
streams in the cloud.
The send data to ThingSpeak from your device,create
instant visualization of live data,and send alerts.

13. GSM Module:
GSM module uses for enabling communication system. It
can transmit voice, SMS and data information with low
power consumption.
GSM module connected with Arduino Uno in this project.
It requires huge power, and its peak power requirement is
3 Amps. GSM module can get 4.7 V to 5 V power supply
from Arduino.
GPS Module:
Global positioning system (GPS) is a navigation and
precise positioning tool, which tracks the location in the
form of longitude and latitude based on Earth.

14. Advantage :
Better and Quick diagnosis.
To avoid unnecessary injury.
Simple to design and install.
Very Low Cost & Low Power Consumption
Easy to wear and monitoring the patient

15. HARDWARE REQUIREMENT
ARDUINO controller
GSM Module
GPS Module
LCD Display
Power supply unit
MEMS sensor
Pulse rate Sensor
Battery

16. SOFTWARE DESCRIPTIONS
Cloud(Thingspeak)
Mobile Application(BLYNK)
Arduino IDE

17. work plan:
Literature survey
Hardware Design
Software
Design
Implementation
0
20
40
60
80
100
120
Dec'22 Jan'22 Feb'22 Mar'22
Activity
Month
work plan

18. CONCLUSION
A cost-effective wearable device is developed to help
millions of people with epilepsy all around the world.
Using this device people with epilepsy can move freely
without worries like normal people.
People with such difficulty create an insecure problem to
roam outside and unable to commanded service to
provide comfortable
This technology-based product will improve the mental
health of the users and reduces the risk of falling.

19. REFERENCES
Alert System for Epileptic Seizure Dr.K. Johny Elma1 ,
Nithiyashree.P2 , Savitha.A3 and Sneha.S4 1Assistant
Professor, Department of Information Technology, Easwari
Engineering College, Chennai.2022
 J. Song, Q. Li, B. Zhang, M. B. Westover and R. Zhang,
"A New Neural Mass Model Driven Method and Its
Application in Early Epileptic Seizure Detection," in IEEE
Transactions on Biomedical Engineering, vol. 67, no. 8, pp.
2194-2205, Aug. 2020, doi: 10.1109/TBME.2019.2957392
S. B. Wilson, M. L. Scheuer, R. G. Emerson, and A. J.
Gabor, ‘‘Seizure detection: Evaluation of the reveal
algorithm,’’ Clin. Neurophysiol., vol. 115, no. 10, pp.
2280–2291, Oct. 2004

20. A. Supratak, L. Li, and Y. Guo, ‘‘Feature extraction with
stacked autoencoders for epileptic seizure detection,’’ in
Proc. 36th Annu. Int. Conf. Eng. Med. Biol. Soc.
(EMBC), Chicago, IL, USA, Aug. 2014, pp. 4184–4187.
P. M. Shanir et al., ‘‘Automatic seizure detection based on
morphological features using one-dimensional local
binary pattern on long-term EEG,’’ Clin. EEG Neurosci.,
Vol. 49, no. 5, pp. 351–362, Sep. 2018, doi:
10.1177/155005941774489.

21. Field Visit

22. Thank You