In the last decade, the number of studies about machine learning algorithms applied to
sports, eg, injury forecasting and athlete performance prediction, have rapidly increased …

Heart disease, caused by low heart rate, is one of the most significant causes of mortality in
the world today. Therefore, it is critical to monitor heart health by identifying the deviation in …

In medical domain, the accuracy of the data supplied is critical. Missing values, on the other
hand, are a typical occurrence in this sector for a variety of reasons. Most current science …

Abstract Introduction Cognitive load (CogL) is increasingly recognized as an important
resource underlying operative performance. Current innovations in surgery aim to develop …

Aims People with type 1 diabetes have a higher risk for cardiovascular disease (CVD).
Reduced heart rate variability (HRV) is a clinical marker for CVD. In this observational study …

Background Cardiovascular disease not only occurs in the elderly but also tends to become
a common social health problem. Considering the fast pace of modern life, quantified heart …

Wearable cardiac sensors pave the way for advanced cardiac monitoring applications
based on heart rate variability (HRV). In real-life settings, heart rate (HR) measurements are …

The standard deviation of the interval between QRS complexes recorded over 24 h
(SDNN24) is an important metric of cardiovascular health. Wrist-worn fitness wearable …

Stress can potentially have detrimental effects on both physical and mental well-being, but
monitoring it can be challenging, especially in free-living conditions. One approach to …

Missing data occurs in all research, especially in medical studies. Missing data is the
situation in which a part of research data has not been reported. This will result in the …