Neural network analysis of heart rhythm variability for diagnosis of immobilization syndrome and objectivization of effectiveness of early rehabilitation

Abstract

The article discusses the use of a neural network analysis of heart rate variability for the diagnosis of immobilization syndrome and post-intensive care syndrome (PICS) in patients with disorders of consciousness for monitoring the quality of the rehabilitation process. It is shown that there are statistical differences between the curves characterizing the heart rate variability of healthy patients and patients with impaired consciousness. The use of a neural network allows to automatically evaluate the severity of the immobilization syndrome and Post Intensive Care Syndrome, as well as the effectiveness of measures for their prevention and the overall quality of the work of medical personnel.

Keywords

heart rate variability / immobilization syndrome / post-intensive care syndrome (PICS) / impaired consciousness / neural networks / rehabilitation

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