Cardiovascular and cerebrovascular events have been observed during night-time associated with periodic breathing including sleep apnea and Cheyne-Stokes respiration. Early detection and treatment is important to reduce night-time events. We clarified the characteristics of the dynamic nature of heartbeats associated with periodic breathing by using detrended fluctuation analysis (DFA). We analyzed heartbeats in eight recordings from the MIT-BIH Polysomnographic database. We observed two crossover points and defined three scaling exponents, β 1 (n ≤ 40 beats), β 2 (50 ≤ n ≤ 200), and β 3 (251 ≤ n ≤ 1584). Compared with β 1 (1.2 1 ± 0.1 3 ) and β 3 (0.9 2 ± 0.1 6 ), scaling exponent β 2 (0.6 2 ± 0. 16 ) showed the statistically lowest value (p < 0.05). And there was a negative relationship between the scaling exponent β 2 and apnea/hypopnea index (p < 0.05). These results indicate that DFA analysis of heartbeats may be useful for the early detection of sleep associated breathing disorders including sleep apnea and its severity.
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