Abstract: A method for extracting and evaluating features from cardiac acoustic signals includes the steps of obtaining a cardiac acoustic signal, extracting physiologically significant features from the cardiac acoustic signal using a neural network, analyzing the cardiac acoustic signal with a wavelist decomposition to extract time-frequency information, and identifying basic heart sounds using neutral networks applied to the extracted time-frequency information. A method for determining a status of heart murmurs includes the steps of obtaining a cardiac acoustic signal, detecting a murmur, if any, from the cardiac acoustic signal, and determining whether the murmur is one of functional and pathological based upon expert rules.

Abstract: An apparatus according to an embodiment of the present invention is provided for sensing acoustic signals. The apparatus includes a housing having an apertured posterior member, a sensing unit extending through the apertured posterior member for interfacing by contact with a patient, a cursor control for positioning a cursor on a display, the display located anteriorially on the housing, a button for fixing a position of the cursor in the display, indicating the position on the housing with respect to the patient, and a circuit for causing the cursor to move about the display in response to the cursor control, and for transmitting the acoustic signal.

Abstract: A method for extracting features from cardiac acoustic signals includes the steps of obtaining a cardiac acoustic signal, and extracting physiologically significant features from the cardiac acoustic signal using a neural network. A method for evaluating cardiac acoustic signals includes the steps of obtaining a cardiac acoustic signal, analyzing the cardiac acoustic signal with a wavelet decomposition to extract time-frequency information, and identifying basic heart sounds using neural networks applied to the extracted time-frequency information. A method for determining cardiac event sequences from cardiac acoustic signals includes the steps of obtaining a cardiac acoustic signal, and processing a sequence of features extracted from the cardiac acoustic signal by a probabilistic finite-state automaton to determine a most probable sequence of cardiac events given the cardiac acoustic signal.

Abstract: According to an embodiment of the present invention, an acoustic signal sensing apparatus is provided. The apparatus includes a housing having an apertured posterior and three studs wherein at least one stud is an electrode providing a temporal reference signal and a sensing unit contacting a patient and capturing an acoustic cardiovascular signal and the temporal reference signal, wherein a portion of the sensing unit is located within the housing. The apparatus further includes a telemetry sensor connected to the sensing unit, communicating the acoustic signal, the temporal reference signal, and a position of the sensing unit with respect to the patient to a data processor.