Introduction: How wearables can detect atrial fibrillation. Smartwatches and other wearable technologies are a booming space within ‘HealthTech’ & modern medicine and have the potential to provide many benefits to people with atrial fibrillation and other heart conditions, such as access to health information. Enhancement, self-monitoring, and better communication with them. Doctors,
There are multiple leading brands of wearable devices on the market (new or updated every year) with built-in health monitoring applications approved for use in Australia, which support chronic disease management.
For example, a person with diabetes can connect their smartwatch to their glucose monitor patch and scan their blood sugar levels throughout the day. For people with atrial fibrillation, smartwatches can help monitor their heart rhythm and heart rate, especially those with built-in ECG monitoring (‘electrocardiogram’ monitoring).
Although heart rate monitors and various ECG devices may have been around for some time, it is only in the last few years that Australia’s Therapeutic Goods Administration has approved wearable ECGs due to their accuracy and quality standards that are expected to produce a ‘medical grade’ ECG. This group of approved devices is causing excitement for people with AFib and their electrophysiologists.
How wearables can detect atrial fibrillation
Wearables have revolutionized how we monitor and manage our health, and one of the significant advancements is their ability to detect atrial fibrillation (AF).
Atrial fibrillation is a common cardiac arrhythmia characterized by irregular and rapid heartbeats that can lead to severe complications like stroke if left undiagnosed or untreated. With the integration of advanced sensors and algorithms, wearables can now provide continuous monitoring and early detection of AF, enabling timely medical intervention.
In this article, we will explore how wearables can detect atrial fibrillation.
The primary method used by wearables to detect AF is through the use of optical sensors, specifically photoplethysmography (PPG). PPG works by emitting light into the skin and measuring the reflected or transmitted light to determine changes in blood volume. This data can then derive cardiovascular parameters, including heart rate and rhythm.
Wearable appliances such as smartwatches and fitness trackers with PPG sensors continuously monitor the user’s pulse rate. When a deviation from the normal rhythm is detected, the device can alert the user to irregular heart activity. This can be done through visual cues, such as a notification on the device’s screen, or haptic feedback, where the device vibrates to indicate an abnormality.
To ensure accuracy, wearables employ advanced algorithms to analyze the PPG data and distinguish between normal sinus rhythm and atrial fibrillation. These algorithms can detect irregular heart rate variability, beat-to-beat intervals, and other features indicative of AF. Machine learning techniques are often employed to train these algorithms on large ECG (electrocardiogram) recordings datasets to improve their accuracy and reduce false positives.
Some wearables also offer the option of conducting an on-demand ECG. This is done by incorporating additional electrodes or metal contacts into the wearable device, which the user can touch or hold to obtain an electrocardiogram reading.
ECG is considered the gold standard for detecting atrial fibrillation and provides more detailed information about the heart’s electrical activity than PPG. The ECG data can be recorded and analyzed by the wearable device or transmitted to a paired smartphone or cloud-based platform for further assessment by healthcare professionals.
Furthermore, wearables with built-in accelerometers can detect irregular physical activity patterns associated with AF. Atrial fibrillation often leads to decreased physical exertion due to fatigue or discomfort. By monitoring the user’s activity levels, wearables can identify significant deviations from the expected baseline and alert the user to seek medical attention.
It’s important to note that while wearables are becoming increasingly accurate in detecting AF, they are not intended to replace professional medical diagnoses. Instead, they serve as valuable screening tools that prompt individuals to seek further evaluation from healthcare providers. If AF is suspected based on wearable data, a doctor may recommend additional diagnostic tests, such as a clinical ECG, to confirm the diagnosis.
Why are ECGs important in diagnosing and managing AFib?
An ECG records the heart’s electrical activity and is a crucial diagnostic and monitoring tool for patients with AFib. They are also used to help diagnose other heart diseases. An ECG is a painless, non-invasive way to measure the heart’s electrical signals.
A traditional ECG test in a clinic or hospital uses 12 electrodes placed on different body parts to measure the heart’s electrical activity from several angles. Electrodes are usually small adhesive stickers that are placed on the skin.
An ECG recording is a series of waves of heart rhythm intervals seen and interpreted by a cardiologist. The 12-lead ECG is believed to be the ‘gold standard’ for ECG testing and is commonly used in the clinical setting.
The cardiologist looks at the waveform and its components to see how often they occur and whether the spaces between them are uniform or variable. Cardiac electrophysiologists (or cardiologists specializing in heart rhythms) can use this information to diagnose a wide range of conditions from the ECG.
Do smart wearable devices detect AFib?
With the beginning of new wearable technology, electrodes inside smartwatches can encourage wearers to take an ECG from their wrist through their watch and see their results in real-time.
The accuracy of the atrial fibrillation (AFib) detection algorithm in a smartwatch device may vary depending on the device and the algorithm used.
Studies have shown that the sensitivity and specificity of smartwatch algorithms for AFib detection is around 70-90%. Sensitivity refers to the algorithm’s ability to correctly identify cases of AFib, while specificity refers to the algorithm’s ability to identify issues where AFib is not present ideally.
Conclusion: How wearables can detect atrial fibrillation
In conclusion, wearables equipped with optical sensors and advanced algorithms can effectively detect atrial fibrillation by continuously monitoring heart rate and rhythm. Photoplethysmography, combined with machine learning techniques, allows these devices to identify irregularities and alert users to potential AF episodes.
Integrating on-demand ECG capabilities and activity monitoring further enhances the accuracy of AF detection. While wearables play a crucial role in early detection, it’s essential to consult healthcare professionals for a comprehensive diagnosis and appropriate medical management of atrial fibrillation.
Also read: Can wearables measure blood pressure?; Can wearable detect sleep apnea; IoMT Wearable Device