Seizure-Glove

Title:-

Generalized Tonic Clonic Seizure Detection and alarming system using EMG sensor, MPU6050 and ESP8266. app combined with tensorflow lite model.

Idea Description:-

We hope to construct a wearable wrist band which will record sEMG signals and Accelerometry with the help of sensors such as EMG Muscle Sensor Module and a triaxial accelerometer embedded into the band. Using this information, we shall predict epileptic seizures and notify the caregiver in case a seizure actually occurs with the help of an Android application. The application will notify the caregiver such as a parent that an episode is taking place and also the exact location of the patient on Google maps. The solution also consists of a continuous low power heart rate monitoring system by Motion Capturing System (IMUs). The band will also consist of an audio module, which shall provide instructions on how to deliver first aid to the patient, for nearby people to help, in case the caregiver is far away. The application will also feature a database where the patient history can be uploaded for medical use including sleep time cycle. It will also include First Aid instructions to be followed during the seizure such as turning of the head to prevent choking, as well as the location of the nearest hospitals, in case of an emergency. We obtained dataset from Patients Data from Health Centre inside campus, which will be used to train the necessary Machine Learning/Deep Learning model. The model will predict the seizures activity by using the real-time data collected from sensors and will use that as test data to classify the activity as seizures or not. The IoT based alarming system will then inform the caretakers via Android application about the activity with certain other information as detailed earlier.

Technology Stack

EMG sensor and electrodes, MPU6050 accelerometer, ESP8266 Wi-Fi module, GPS module, Python Language, Deep Learning ,Keras, Firebase, Android Studio, Arduino IDE, PLX-DAQ, Microsoft Office.

Use cases

1. Alert for caretakers of epileptic patients
2. Continuous health monitoring helpful for hospitals
3. Continuous sleep monitoring system which can be used by non-epileptic people too
4. Detection of unobserved seizures(61% cases of unobserved seizure activity)
5. Location tracking of patients and list of nearby hospitals for emergency cases