Abstract: The present invention is a method and system for detection of high-frequency heart sounds for diagnosing heart diseases. One embodiment utilizes an accelerometer-based detector that presents a light load to the chest, is sensitive to the desired high frequency range, and provides a quantitative measurement of the quality of the acquired signal. Two thin piezoelectric flexible sensors, supported by a lightweight mechanical structure, are center-loaded so that they respond to the same mechanical energy and will produce identical electrical signals in the absence of noise. A signal processing system compares the signals from the two sensors to produce an estimate of the signal-to-noise ratio. The two signals can be combined to further improve the signal-to-noise ratio. The invention is designed to be light weight, to have a sensitive sensor mechanism, to provide an estimate of the signal-to-noise ratio of the detected signal, and to be relatively immune to noise.

Abstract: When human intestine becomes damaged due to insufficient blood perfusion (ischemic disease), the damaged tissue must be surgically removed and the remaining tissue sewn together (end-to-end anastomoses). If nonviable tissue is not removed the result can be fatal while removal of too much bowel can also lead to severe complication. The distinction between viable and nonviable tissue must often hastily be made during urgent operations on critically ill patients. This decision remains a challenge for even the most experienced general surgeon. The system disclosed herein is a medical instrument designed to quantify the survivability of intestine compromised by ischemic disease. This medical instrument evaluates ischemic tissue through the quantification of electrical and contractile activity. The computer-based instrument uses advanced signal processing techniques to remove measurement artifact and physiological variability.

Abstract: A method and system for non-invasively detecting Coronary Artery Disease. The method comprises analyzing the diastolic heart sounds detected from a patient's chest cavity during the diastolic portion of the heart cycle in order to identify a low level auditory component associated with turbulent blood flow in partially occluded coronary arteries. These diastolic heart sounds are modeled using advanced signal processing techniques such as Autoregressive (AR), Autoregressive Moving Averaging (ARMA) and Eigenvector methods, so that the presence of such an auditory component may be reliably indicated even under high noise conditions. The system includes an acoustic transducer, pulse sensor device, signal processor means and a diagnostic display. Additionally, the system includes a controller for automatically sequencing data collection, analysis and display stages, therefore requiring a minimum of operator interaction.

Abstract: A method and system for non-invasively detecting Coronary Artery Disease. The method comprises analyzing the diastolic heart sounds detected from a patient's chest cavity during the diastolic portion of the heart cycle in order to identify a low level auditory component associated with turbulent blood flow in partially occluded coronary arteries. These diastolic heart sounds are modeled using advanced signal processing techniques such as Autoregressive (AR), Autoregressive Moving Averaging (ARMA) and Eigenvector methods, so that the presence of such an auditory component may be reliably indicated even under high noise conditions. The system includes an acoustic transducer, pulse sensor device, signal processor means and a diagnostic display. Additionally, the system includes a controller for automatically sequencing data collection, analysis and display stages, therefore requiring a minimum of operator interaction.