Abstract: A method and system for analyzing an electrogastrophic (EGG) signal are disclosed. Electrodes are positioned on abdominal skin of a subject adjacent a stomach thereof. The electrodes obtain the EGG signal produced by the stomach. An amplifier is connected to the electrodes, receives the obtained EGG signals, and amplifies the obtained EGG signal. A transforming device is operatively connected to the amplifier. The transforming device receives the amplified EGG signal and transforms the amplified EGG signal from a time domain representation to a frequency domain representation. The transformation is accomplished by way of a predetermined transform function incorporating a variable frequency and a window function. The window function has a time resolution and a frequency resolution. The frequency resolution of the window function is proportional to the frequency.

Abstract: Cardiac monitoring is disclosed in which thoracic impedance and EKG signals are gathered and processed for improved resolution and accuracy. EKG signals are adaptively processed by digitizing, filtering, differentiating and raising the resultant differential by a power greater than one to emphasize changes in the slope of the EKG signal. Blocks of the thus processed EKG data are analyzed to identify peak amplitude and to compare spacing between peak amplitudes adaptively to more accurately identify R wave peaks. Stroke volume is determined from a thoracic impedance signal and its time derivative. Preferably, a time-frequency distribution is taken of the time derivative thoracic impedance signal after low- and high-pass filtering to identify B and X wave events in the signal which are used to determine ventricular ejection time and dZ/dt.sub.min for a determination of heart stroke volume by conventional methods.

Abstract: The present invention reliably computes cardiac output with a noninvasive procedure. The system measures the electrical impedance of a patient's body, during a time interval of interest. The system then obtains frequency transforms of various time segments of the first derivative of the impedance signal. Each such transform is integrated over a frequency range of interest, and the values of the integrals are plotted as a function of time. The graph so derived has characteristic extrema which can be used to identify critical points in the impedance derivative signal. These critical points can be used to determine parameters which are used in a calculation of stroke volume and cardiac output.

Abstract: Cardiac monitoring is disclosed in which thoracic impedance and EKG signals are gathered and processed for improved resolution and accuracy. EKG signals are adaptively processed by digitizing, filtering, differentiating and raising the resultant differential by a power greater than one to emphasize changes in the slope of the EKG signal. Blocks of the thus processed EKG data are analyzed to identify peak amplitude and to compare spacing between peak amplitude adaptively to more accurately identify R wave peaks. Stroke volume is determined from a thoracic impedance signal and its time derivative. Preferably, a time-frequency distribution is taken of the time derivative thoracic impedance signal after low- and high-pass filtering to identify B and X wave events in the signal which are used to determine ventricular ejection time and dz/dt.sub.min for a determination of heart stroke volume by conventional methods.