It is difficult to establish the process of chaos in time series from cardiac dynamics. The output from such a system is probably the result of both its internal dynamics, and the input to the system from its surroundings. We present an optimization algorithm to find a time series that is as close as possible to the heart rate series subject to the constraint that it is deterministic with respect to some dynamics. The algorithm is tested by some famous forced dynamical systems, and applied to heart rate data. We find that the deterministic components of heart rate variability are chaotic.
