Title :
Automated analysis of the auditory brainstem response
Author :
Bradley, Andrew P. ; Wilson, Wayne J.
Abstract :
We describe an algorithm for automated peak-trough labelling of the auditory brainstem response (ABR). The algorithm finds the peaks of clinical interest by estimating the first and second derivatives of the ABR waveform. Prior knowledge regarding the expected latencies and amplitudes of the various peaks is then used to label the peaks incrementally I to VII. The performance of the algorithm is estimated on a set of 240 ABR waveforms captured at a stimulus intensity of 90 dBnHL. The proposed algorithm not only offers insight into the manual process of ABR peak detection, but is shown to be extremely, accurate (96-98%) at finding the primary peaks of clinical interest (I, III, and V). It is also shown that although peak IV can only be found with moderate accuracy (77%), almost one third of these correct detections come as a direct result of locating the "peak" using the second derivative.
Keywords :
auditory evoked potentials; medical signal detection; medical signal processing; parameter estimation; auditory brainstem response; automated peak-trough labelling; automated signal analysis; clinical interest; peak detection; primary peaks; second derivative; waveform derivatives; Auditory system; Australia; Delay; Information processing; Information technology; Labeling; Matched filters; Patient monitoring; Sensor phenomena and characterization; Signal processing;
Conference_Titel :
Intelligent Sensors, Sensor Networks and Information Processing Conference, 2004. Proceedings of the 2004
Print_ISBN :
0-7803-8894-1
DOI :
10.1109/ISSNIP.2004.1417519