Augmented Reality Binoculars.

In this paper we present an augmented reality binocular system to allow long range high precision augmentation of live telescopic imagery with aerial and terrain based synthetic objects, vehicles, people and effects. The inserted objects must appear stable in the display and must not jitter and drift as the user pans around and examines the scene with the binoculars. The design of the system is based on using two different cameras with wide field of view and narrow field of view lenses enclosed in a binocular shaped shell. Using the wide field of view gives us context and enables us to recover the 3D location and orientation of the binoculars much more robustly, whereas the narrow field of view is used for the actual augmentation as well as to increase precision in tracking. We present our navigation algorithm that uses the two cameras in combination with an inertial measurement unit and global positioning system in an extended Kalman filter and provides jitter free, robust and real-time pose estimation for precise augmentation. We have demonstrated successful use of our system as part of information sharing example as well as a live simulated training system for observer training, in which fixed and rotary wing aircrafts, ground vehicles, and weapon effects are combined with real world scenes.

Computer-assisted detection of systolic murmurs associated with hypertrophic cardiomyopathy: a pilot study.

A pilot study was conducted to ascertain the level of agreement between auscultatory findings derived from heart sound recordings by a cardiologist and the results of a computer-based heart sound analysis algorithm. Heart sound recordings were obtained from volunteer subjects previously diagnosed with hypertrophic cardiomyopathy. Twenty-second recordings were obtained at each of 4 standard auscultatory locations on the precordium in 2 postures: standing and reclining. Detailed auscultatory findings were derived by a cardiologist, who listened to the heart sound recordings and was blinded to the study design. The recordings were analyzed by an algorithm that detects heart sounds and murmurs, and derives associated timing and energy parameters. The algorithm results were compared with the auscultatory findings provided by the cardiologist and correlated with the medical histories provided by the volunteer subjects. A high degree of concordance between the medical histories, auscultatory findings, and computer analyses was obtained. The 1st and 2nd heart sounds were detected with high sensitivity (90.7%) and positive predictivity (93.0%). Systolic murmurs were detected with a sensitivity that increased from 50% for grade 1 to 100% for grades 2-3 and 3. The signal energy in the mid-frequency range correlated well with murmur grade judgments, and also agreed well with the cardiologist's judgments of the relative loudness of murmurs in standing versus reclining postures. The computer analysis algorithm thus instantiates the objective detection and identification of apical systolic murmurs that are louder in standing than in reclining postures; such murmurs are a cardinal sign of hypertrophic obstructive cardiomyopathy.