Automatically labeling of Brainstem Auditory Evoked Potential based on vector algorithm

Author

Sun, Ying ; Chen, Zhaoxue ; Lu, Hongwei

Author_Institution

Med. Instrum. & Food Eng. Coll., Univ. of Shanghai for Sci. & Technol., Shanghai, China

Volume

4

fYear

2011

fDate

15-17 Oct. 2011

Firstpage

2206

Lastpage

2209

Abstract

Brainstem Auditory Evoked Potential (BAEP) is one of the widely-used evoked potentials in clinical application. For many applications such as auditory threshold estimation and surgical monitoring, automatic analysis of BAEP waveform is required to provide BAEP determination threshold for clinical analysis. This paper describes one new vector algorithm which is used to perform automatic labeling of BAEP thresholds on collected BAEP data, and experiment results have shown that label accuracy is more than 90% under a stimulus intensity of 75dBnHL.

Keywords

auditory evoked potentials; medical signal processing; vectors; BAEP waveform analysis; auditory threshold estimation; brainstem auditory evoked potential automatic labelling; clinical analysis; surgical monitoring; vector algorithm; Algorithm design and analysis; Estimation; Labeling; Noise; Vectors; Visualization; Wiener filter; Automatically Labeling of Threshold; Brainstem Auditory Evoked Potential; Vector Algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Signal Processing (CISP), 2011 4th International Congress on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-9304-3

Type

conf

DOI

10.1109/CISP.2011.6100540

Filename

6100540