Mobile technology is being extensively used by biotechnology and pharmaceutical companies to devise functional, affordable and accurate apps for the early detection of serious health issues. Just recently, AliveCor has introduced a heart monitor analyzing app that can allow the users to detect atrial fibrillation.
The FDA approved, smartphone enabled digital ECG application can carefully detect irregular heartbeat (that is generally not felt by the patient) in at-risk population. Atrial fibrillation is a serious condition, which if left untreated can significantly increase the risk of stroke or congestive heart failure in otherwise asymptomatic patients.
This ECG application is available at both the Apple and Android mobile phones after receiving the FDA’s approval since the fall of 2013. Hundreds and thousands of people are using this app efficiently since March 2014. Yet, the buyers who were utilizing this app were required to wait for at least 24- hours to get their ECG report/ evaluation from a board-certified cardiologist or cardiovascular professional. The results could also be achieved a bit earlier with a small fees. But with this advanced application, patients will be able to get an immediate reading regarding their status of atrial fibrillation.
The president and CEO of AliveCor – Euan Thomson is a firm believer that this mobile app would help minimize the risk of sudden cardiac death in patients, over the age of 40 years, due to higher likelihood of the detection of silent or asymptomatic atrial fibrillation. He also affirmed that the calculation has 100% sensitivity (it never gives back a false negative) and 97% specificity (it sends back a false positive around 3% of the time).
The application will be released for customers in September, and there are no plans to take the cardiologists off the picture; however the experts think the algorithm will go beyond AliveCor’s thinking, since they are persistently learning and improving their algorithm from the ECG readings overflowing into their database, carrying 1.1 million ECGs of which a high portion belong to diagnosis of atrial fibrillation. This database consists detailed analysis of diverse clinical conditions which can become a great source of learning, training and improving their human interpretative algorithm.