For Deltahack
Title: A mobile system monitoring and predict Cardiac Arrest by using biosensors.
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 App search the nearst Cardiopulmonary resuscitation (CPR) and automated external defibrillator (AED) device. 5 Contack emergency department to make further decision
Abstract: Cardiac arrest is a condition which the heart suddenly and unexpectedly stops beating, abruptly and without any warning. If the heartbeat is not restored with an electrical shock (automated external defibrillator, AED) immediately or cardiopulmonary resuscitation (CPR), death always follows within a short time. So 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 place. To improve survival rate of cardiac arrest, the government provide CPR training and install AED in different communities. It is reported that Ontario will receive another 2500 AED and 25000 more persons will be certified in CPR and AED this year, which establish a save-life network. CardiacProtect provide a real-time monitor heart rate, alert users and healthcare providers once high risk of a cardiac arrest is identified.