Title :
Fast detection of wave V in ABRs using a smart single sweep analysis system
Author :
Strauss, Daniel J. ; Delb, Wolfgang ; Plinkert, Peter K. ; Schmidt, Helmut
Author_Institution :
Key Numerics, Saarbrucken, Germany
Abstract :
The analysis of auditory brainstem responses (ABRs) is accepted to be the most reliable method for the objective diagnosis and quantification of hearing loss in newborns. However, in currently available setups, a large number of sweeps has to be averaged to obtain a meaningful signal at low stimulation levels due to a poor signal-to-noise ratio. In this study, we present a new approach to the detection of wave V in ABRs using a smart single sweep analysis system. A small number of sweeps is decomposed by optimized tight frames and evaluated by a kernel based novelty detection machine. This hybrid supervised learning scheme is combined with an intersweep dissimilarity tracing for the final decision making. At the challenging stimulation level of 30 dB, our system reached a reasonable specificity and sensitivity for the detection of wave V in a fraction of the measurement time of conventional schemes.
Keywords :
auditory evoked potentials; learning (artificial intelligence); medical signal detection; medical signal processing; paediatrics; patient diagnosis; 30 dB; auditory brainstem responses; fast wave V detection; hearing loss diagnosis; intersweep dissimilarity tracing; newborns; smart single sweep analysis system; supervised learning; Anesthesia; Auditory system; Costs; Deafness; Feature extraction; Hospitals; Kernel; Loss measurement; Pediatrics; Time measurement; Adapted Filter Banks; Auditory Brainstem Responses; Hearing Screening; Kernel Machines; Single Sweep Analysis; Smart Systems; Wavelets;
Conference_Titel :
Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-8439-3
DOI :
10.1109/IEMBS.2004.1403193
