The ECG sensor data from the Apple Watch can be utilised to create a reliable and effective stress prediction tool, according to a team of researchers who have studied the watch’s ECG sensor in depth.
According to MacRumors, the researchers from the University of Waterloo in Canada found a strong correlation between subjects’ reported levels of stress at the time the readings were collected and ECG data, including heart acceleration and deceleration capabilities.
Machine learning algorithms were developed using this data to produce a prediction model.
The report claims that the stress models have a “high level of precision” but a “poor recall.”
The study concludes that the Apple Watch has “promising” potential for stress prediction and hypothesises that even more data points might be merged into stress models to increase predicted accuracy because the device captures additional health data, such as sleep and activity data.
Additionally, the paper stated that the researchers believe the Apple Watch might be used to support mental health treatment by offering workouts like breathing exercises to counteract stress signals and responding quickly to changes in mental health.
A recent study, meantime, found that the Apple Watch can aid in the early detection of silent cardiac illness.
According to the Mayo Clinic study, cardiac dysfunction frequently remains misdiagnosed because it is asymptomatic, meaning that those who have it are not aware of it.
Consumer-watch ECGs obtained in nonclinical settings can identify people with heart malfunction, according to the research.
