Fitbit Can Now Scan for Abnormal Heartbeats, Mirroring the Apple Watch Key Feature

Fitbit devices feature the capacity to detect abnormal heartbeats. Just recently, Fitbit was able to secure approval from the Food and Drug Administration for their algorithm that detects atrial fibrillation (AFib).

Fitbit's new PPG (photoplethysmography) algorithm will pave the way for users to have an Irregular Heart Rhythm Notifications feature that will alert them when an abnormal AFib is detected.

Detecting irregular heart rate is one of the features of the Apple Watch that distinguishes it as the best fitness and smartwatch, as it has the ability to detect irregular heart rhythms while users are wearing the device. Apple, on the other hand, is about to face some stiff competition in this area.

Fitbit AFib Detection Feature

Fitbit's new AFib detection feature would complement the ECG feature found on some of the best Fitbit devices, which allows the user to scan for AFib on a proactive basis.

The algorithm developed by the company marks a significant upgrade to their technology as the Fitbit now has the capacity to operate in the background.

With their new PPG AFib algorithm, users can have their heart rhythm assessed passively in the background while they're standing still or asleep. This lets people keep track of their heart health over time, which can help them find problems before they get worse.

As reported by Digital Trends, according to studies, approximately 33 million people worldwide have atrial fibrillation (AFib), and those who have the condition are at an increased risk of suffering a potentially debilitating or life-threatening stroke.

Even though AFib usually occurs without warning, and in some cases, without any noticeable symptoms, it can be difficult to diagnose the condition. Fitbit's system will be running all the time and in the background, even though it won't be visible. The device's sensors will be looking for any unusual heartbeats during the day and while you sleep.

Any time the Fitbit device detects something that could be indicative of AFib, the user will receive an alert. It should be noted that, while the feature cannot be used to diagnose AFib, it can be used to alert the user that the condition may be present.

How does Fitbit Afib Work?

Fitbit's parent company, Google, explained how their latest technology for detecting AFib works. Small blood vessels throughout our body expand and contract as a result of the heart's beating, depending on the volume of blood flowing through them.

Fitbit's PPG optical heart-rate sensor can detect these volume changes right on a user's wrist. Following these measurements, the detection algorithm analyzes the heart rhythm for irregularities and potential signs of atrial fibrillation, which will then be reported back to the user.

Fitbit's PPG algorithm has been clinically validated, according to data from the landmark Fitbit Heart Study, which began in 2020 and enrolled 455,699 participants over the course of five months. This is one of the largest remote studies of PPG-based software that has ever been done. It was done during the pandemic.

Fitbit PPG detections correctly identified AFib episodes 98% of the time, according to data presented at the 2021 American Heart Association Scientific Sessions, as confirmed by ECG patch monitors.

Fitbit now offers two methods for detecting atrial fibrillation (AFib), following the FDA's approval of our PPG-based algorithm today. Fitness tracker Fitbit's ECG app, which uses a spot-check approach, allows users to proactively screen themselves for possible atrial fibrillation (AFib) and record an ECG trace that they can then share with a healthcare provider.

New PPG-based algorithms also make it possible to look at long-term heart rhythms, which helps to find asymptomatic AFib that would otherwise go unnoticed. The company hopes that delivering this feature to its user base will help them live a better lifestyle.

© 2024 iTech Post All rights reserved. Do not reproduce without permission.

More from iTechPost

Real Time Analytics