DeltaHackathon (@MAC 2017, Jan)

For Deltahack

Title: A mobile system monitoring and predict Cardiac Arrest by using biosensors.

Abstract: Cardiac arrest is a condition which the heart suddenly and unexpectedly stops beating, abruptly and without any warning. Immediately resuscitation play a key role in saving life when cardiac arrest happens. In Canada, there are approximately 40,000 cardiac arrests each year and up to 85% of cardiac arrests occur at home or in public places.

Scope: High risk of Cardiac Arrest users/or some heart disease patients (atrial fibrillation/arrhythmia)

Objectives: 1 By using wearable sensors to monitor heart rate and other parameters 2 Using K-Mean unsupervised method to clustering personazied heart rate range 3 Using SVM/Ramdon Forest Tress to classify the real-time data from biosensor 4 Once high risk of cardia arrest, the app will send alarm to users, and send sms/email to emergency contact with user's location 5 Contack emergency department to make further decision

Built With

• android-studio
• data-analysis
• deep-learning
• java
• machine-learning
• microsoft-band