Modern hospitals are equipped with sophisticated monitoring equipment that displays enormous volumes of raw data about the cardiopulmonary and neural functions of patients. The latest generation of bedside monitors attempts to present these data to the clinician in an integrated fashion to better represent the overall physiological condition of the patient. However, none of these systems are capable of extracting potentially important indices of pattern variability inherent within biological signals. This review has three main objectives. (1) To summarize the current state of data acquisition in the intensive care unit and identify limitations that must be overcome to achieve the goal of real-time processing of biological signals to capture subtleties identifying “early warning signals” hidden in physiologic patterns that may reflect current severity of the disease process and, more importantly, predict the likelihood of adverse progression and death or improvement and resolution. (2) To outline our approach to analyzing biological waveform data based on work in animal models of human disease. (3) To propose guidelines for the development, testing and implementation of integrated software and hardware solutions that will facilitate the novel application of complex systems approaches to biological waveform data with the goal of risk assessment.