The ECG sensor data from the Apple Watch may be utilised to create a reliable and effective stress prediction tool.
According to MacRumors, the researchers from the University of Waterloo in Canada found a strong correlation between subjects’ stated levels of stress at the time the measurements were collected and ECG data, including cardiac acceleration and deceleration capabilities.
Machine learning algorithms were developed using this data to produce a prediction model.
The paper claims that the stress models have a “high level of accuracy” but a “poor recall.”
The study finds that the Apple Watch has “promising” potential for stress prediction and hypothesises that even more data points may be added because the device gathers additional health information, such as sleep and activity information, to stress models to increase predicted accuracy.
The researchers also believe that the Apple Watch might be used to support mental health treatment by offering exercises like breathing exercises to counteract stress signals and responding quickly to changes in mental health, according to the article.
In the meanwhile, a recent research found that the Apple Watch can aid in the detection of silent cardiac illness.
Because cardiac dysfunction is asymptomatic, meaning that those who have it are unaware of it, the Mayo Clinic research notes that it frequently remains misdiagnosed.
Consumer-watch ECGs obtained in nonclinical settings can detect people with heart malfunction, according to the research.