The natural frequency of a mechanical system provides insight into its condition. The degree of stress to which a system is subjected is reflected in sounds produced by the system when excited. In particular, the movement of a mechanical or biological cardiac valve pros-thesis generates audible sound; the natural frequency of a correctly functioning valve differs from that of a faulty valve. This research effort will focus on defining a prototype database management system and associated analysis algorithms for identifying failure modes of cardiac valve prosthetic devices.Tasks include developing criteria and protocols for collecting data from prosthetic valves mounted in a commercially available pulse duplicator system, specifying appropriate data structures and processing logic for storing and analyzing the data, and defining display techniques to permit visually as well as audibly associating unambiguous sound signatures with prosthetic devices in various stages of fatigue or stress failure. Successful development of analysis algorithms will permit valve manufacturers to more closely monitor manufacturing for quality control purposes as well as providing a basis for algorithms which can be used to determine the condition of valves in vivo. More generally, this algorithm research will have widespread impact on other manufacturing quality control and/or maintenance processes.Commercial Applications:For in vitro or in vivo analysis of the condition of cardiac valve prostheses. Pattern recognition algorithms will also be appropriate for non-invasive, non-destructive analysis of other types of material failures.
