This project focuses on developing a complete telemetry system in response to the growing demand for efficient, mobile and inexpensive system for detecting cardiovascular abnormalities. Our team has already developed two algorithms. The first algorithm detects various critical points on Electrocardiograph (ECG) waveforms such as: P-wave, QRS complex, T-wave and ST elevation. Based on these points, the second algorithm detects Myocardial Infractions (MI) in a patient. Currently, we are developing a telemetry system that comprises of an Arduino microcontroller and a smartphone. The 12-lead ECG signals are collected from a patient or an ECG simulator. The signals are then sent to an electronic circuit for amplification and filtration. The amplified and filtered signals are collected in the Arduino microcontroller. The microcontroller sends the signals, via Bluetooth, to an Android smartphone application developed by our team. The ECG data is sent from the smartphone to a webserver using 3G or Wi-Fi connection. The data is securely processed and analyzed in the webserver using the algorithms developed by our team. The processed ECG waveforms and the results of its analysis are sent back and displayed on the smartphone application. The analyzed results display whether the patient has a likelihood of having an MI. Furthermore, the analyzed results are stored in a secure database for future reference. Using the real-time analyzed ECG waveforms, the integrated system is designed to provide early warning of cardiac risk, thus saving valuable time and effort in patients' treatment. Along with that, this system will be efficient in terms of cyber security, cost management and reliability.


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