Key result
Adaptive AR modeling using Kalman filtering revealed that the transition from a normoxic to a hypoxic state in intact animals requires tremendous short-term readjustment of autonomic control.
Population
Intact animals
Design
Other
Authors
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Suggests heightened autonomic vulnerability during acute hypoxia; leaves open clinical translation of adaptive AR modeling.
Adaptive AR modeling using Kalman filtering is a useful tool for analyzing nonstationary physiological signals like heart rate and EEG.
Arnold et al. (1998) studied Physiological signals (respiratory movement, heart rate, blood pressure, EEG). Adaptive AR modeling by means of Kalman filtering was evaluated. Adaptive AR modeling using Kalman filtering revealed that the transition from a normoxic to a hypoxic state in intact animals requires tremendous short-term readjustment of autonomic control.
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