Background The electrocardiogram (ECG) is one of the most commonly used diagnostic
tools in medicine and healthcare. Deep learning methods have achieved promising results …

Researchers have increasingly begun to use consumer wearables or wrist-worn
smartwatches and fitness monitors for measurement of cardiovascular psychophysiological …

Artificial intelligence (AI) stands out as a transformational technology of our digital age.
Questions about what it is, what it can already do—and what it has the potential to become …

Hypertension is a key risk factor for cardiovascular disease. Currently, around a third of
people with hypertension are undiagnosed, and of those diagnosed, around half are not …

We train and validate a semi-supervised, multi-task LSTM on 57,675 person-weeks of data
from off-the-shelf wearable heart rate sensors, showing high accuracy at detecting multiple …

Arterial hypertension (AH) is a progressive issue that grows in importance with the increased
average age of the world population. The potential role of artificial intelligence (AI) in its …

Polysomnography remains the cornerstone of objective testing in sleep medicine and results
in massive amounts of electrophysiological data, which is well-suited for analysis with …

Hypertension, or elevated blood pressure (BP), is a marker for many cardiovascular
diseases and can lead to life threatening conditions such as heart failure, coronary artery …

The spread of wearable watch devices with photoplethysmography (PPG) sensors has
made it possible to use continuous pulse wave data during daily life. We examined if PPG …

The use of consumer-grade wearables for purposes beyond fitness tracking has not been
comprehensively explored. We generated and analyzed multidimensional data from 233 …