CordisX: Personalized Cardiac Monitoring Through Low-Cost Sensor Systems and Real-Time Statistical Analysis Algorithms

Overview

Heart disease is a prevalent issue in the modern world, with 84 million people in the US alone that require regular checkups with clinicians. CordisX aims to provide a cost­ effective, personalized cardiac diagnosis assistant that integrates both the hardware and software aspects of automated ECG interpretation and a mobile sensor system. Through a 3-lead electrode placement, an Arduino circuit system captures the real-time ECG data, which is then exported as a .dat file. The reformatted data is fed through a processing MATLAB program with automated filtering and peak recognition. Feature extractions and statistical analysis are utilized to compare a patient's ECG signal to normal sinus rhythms (baseline data) from the MIT-BIH database. Through the ECG interpretation framework, detailed and necessary diagnoses can be made for a patient's well-being, and anomalies foreshadowing arrhythmias (heart disease) can be detected instantly. I tested the diagnosis system on myself with different conditions to simulate abnormalities, and captured the output. The other component of the diagnosis system is a portable dual-sensor device that is synced with a custom-made Android application. Analyzing the correlation between heart rate and oxygen saturation based on the user's age and gender, the app displays diagnosis in the form of a warning or a confirmation of healthy vital data. In combination with the ECG analysis framework, the dual-sensor mobile system allows the user to better visualize his or her overall heart health through vital heart data and examinations of the ECG signal.

Competition history

• AJAS 2018 Category not listed

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