Real Time Recognition of Heart Attack in a Smart Phone

BACKGROUND: In many countries, including our own, cardiovascular disease is the most common cause of mortality and morbidity. Myocardial infarction (heart attack) is of particular importance in heart disease as well as time and type of reaction to acute myocardial infarction and these can be a determining factor in patients' outcome. METHODS: In order to reduce physician attendance time and keep patients informed about their condition, the smart phone as a common communication device has been used to process data and determine patients' ECG signals. For ECG signal analysis, we used time domain methods for extracting the ST-segment as the most important feature of the signal to detect myocardial infarction and the thresholding methods and linear classifiers by LabVIEW Mobile Module were used to determine signal risk. RESULTS: The sensitivity and specificity as criteria to evaluate the algorithm were 98% and 93.3% respectively in real time. CONCLUSIONS: This algorithm, because of the low computational load and high speed, makes it possible to run in a smart phone. Using Bluetooth to send the data from a portable monitoring system to a smart phone facilitates the real time applications. By using this program on the patient's mobile, timely detection of infarction so to inform patients is possible and mobile services such as SMS and calling for a physician's consultation can be done.