Secure detection of critical cardiac abnormalities for wireless body area networks
School of Science
Anomalies in cardiac functionality can be fatal. Early detection of these anomalies, and in many cases their precursors, can save lives. The probability in occurrence of these anomalies is extremely among people with pre-diagnosed heart condition. In this research we discovered that many remote Electrocardiography (ECG) monitoring systems do not convey "enough" information to the diagnosing doctor or to the nominated caregiver. A few examples of this information can be: the type of cardiac abnormality, exact waveform of the ECG signal, time and frequency of the occurrence of the anomaly, machine understandable part so that medical SCADA be alerted about the case, and immediate preventative urgent steps correlated to that emergency. It is also important to delivery surrounding context to the Health Information System so that the medical expert make his/her diagnosis with ample support data. The most important component in this communication is the security of contents from cyber crimes. We propose a cost efficient and non invasive health monitoring system that is secure and quickly deployable. The presented system embeds an intelligent wearable data acquisition system with unique identification algorithms requiring very little computational time and simple threshold based classification.