Abstract
An automated algorithm for identifying periods of sleep and waking using data from the motor activity of the subject’s thoracic cage is proposed. The algorithm is based on accelerometry and is intended as a component of systems used for prolonged monitoring of cardiovascular system functions. Use of this algorithm allows trace segments to be defined as “sleep” or “waking” with accuracies of up to 77.6% in the overall cohort, 83.7% when there are no sleep disorders, and 70.5% in patients with respiratory abnormalities during sleep. Use of the algorithm in Holter monitoring systems in routine practice will help improve the accuracy of diagnostic results in cardiovascular diseases and the detection of sleep disorders.
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