دانلود کتاب ریتم ها در مراقبت های بهداشتی

Modern sensing technology enables the acquisition of rhythmic data from the human body and daily activities using a variety of sensors. Technological advancements and a better understanding of machine learning algorithms are catching up with medical practice and research in the field of digital healthcare. The extent to which digital healthcare is actually used is determined by a variety of factors, including the types of diseases and functions that patients suffer from, as well as their age and gender. We can improve the effectiveness of present treatments and the prognosis of patients by adopting new digital technology. This could be cutting-edge technology or an application built on a solid understanding of the basic physiology and anatomy of the human body. Anomaly rhythms can be used to predict any disease-related form using core body temperature, gene expression, and hormone secretion measurements. Sensors embedded in smartphones and other devices can now collect data on physical activity, sleep, and heart rate. As sensors improve, the volume, quality, and variety of data that can be conveniently collected in daily life will increase. As a result, several components of the circadian rhythm can be quantified and analysed.