Advances in wearable sensing and mobile computing have enabled the collection of health
and well-being data outside of traditional laboratory and hospital settings, paving the way for …

Surgery is a common first-line treatment for many types of disease, including cancer.
Mortality rates after general elective surgery have seen significant decreases whilst …

Cardiovascular diseases (CVD) are often characterized by their multifactorial complexity.
This makes remote monitoring and ambulatory cardiac rehabilitation (CR) therapy …

Day to day interactions with wearable and pervasive systems lead to collected data that
capture various aspects of human behavior and enable machine learning algorithms to …

Predicting cardiorespiratory fitness levels can be useful for measuring progress in an
exercise program as well as for stratifying cardiovascular risk in asymptomatic adults. This …

Healthcare systems are primarily focused on treating patients' conditions after a confirmed
diagnosis. The emerging field of precision health targets early detection and tailored …

Background Wearable technology has the potential to improve cardiovascular health
monitoring by using machine learning. Such technology enables remote health monitoring …

The increasing demand for personalized healthcare, particularly among individuals
requiring continuous health monitoring, has driven significant advancements in sensor …

Cardiorespiratory fitness is an established predictor of metabolic disease and mortality.
Fitness is directly measured as maximal oxygen consumption (VO2 max), or indirectly …

Background The step test provides valuable information on cardiorespiratory parameters
such as maximal oxygen uptake and heart rate. Cardiorespiratory capacity is critical to …