Pathology can affect physiologic recordings in unexpected and interesting ways. PhysioNet encourages researchers to find new ways to extract information hidden in data.

For example, the figure to the right shows the instantaneous heart rates of four subjects. But only one signal is from a healthy person. Can you tell which it is?

Click here for the answer.

Learn more about this subject in Nonlinear Dynamics, Fractals, and Chaos Theory for Clinicians.

This one-minute excerpt of an eight-hour multichannel record of a patient with obstructive sleep apnea shows complex coupling of cardiopulmonary and electroencephalographic (EEG) dynamics. The shaded lines below the time axis indicate prolonged sleep apnea episodes, characterized by periodic cessation of breathing. BP indicates blood pressure; Resp, respiration; and SaO2, arterial oxygen saturation.

This sample comes from the Apnea-ECG Database, which was created to support the first in our annual series of open challenges.

Neuro-degenerative diseases often affect gait and mobility. To gain a better understanding of the pathophysiology of these diseases and to improve our ability to measure responses to therapeutic interventions, it may be helpful to quantify gait dynamics accurately. The data shown here are stride intervals (the time intervals between consecutive heel strikes of the same foot).

Find these and many more stride interval time series in the Gait Dynamics in Neuro-Degenerative Disease Database.