INDIVIDUAL RECOGNITION BY HEART-RATE-VARIABILITY OF 2 DIFFERENT AUTONOMIC PROFILES RELATED TO POSTURE

Background Power spectrum analysis of heart rate variability (HRV) can estimate the state of sympathovagal balance modulating sinus node act ivity. In view of the large distribution of spectral variables, a reco gnition of well-defined physiological conditions has never been attemp ted on an individual basis. Methods and Results We considered 10 spect ral variables extracted from short segments (200 to 500 cardiac cycles ) of 350 ECG tracings recorded in normal subjects in both supine and u pright positions (700 patterns). The tracings were first ordered conse cutively and subsequently assigned alternatively to a training or to a test set (each consisting of 175 cases, providing 350 patterns consid ered to be independent). A forecasting linear method estimated a norma lized activation index (ranging from -1 for supine to +1 for upright) that concentrated the information derived from spectral variables and that identified, in the test set, individual by individual, approximat e to 84% of corresponding body postures. Conclusions The combined use of spectral methodology and forecasting analysis has revealed an infor mation content embedded, per se, in a short series of RR intervals cap able of recognizing, individual by individual, two different autonomic profiles related to posture.