EEG Based Hearing States Detection Using AR Modeling Techniques

被引：0
作者：
Subramaniam, Kamalraj [1 ]
Paulraj, M. P. [2 ]
Divya, B. S. [1 ]
机构：
[1] Karpagam Univ, Coimbatore, Tamil Nadu, India
[2] SRIT, Coimbatore, Tamil Nadu, India
来源：
2016 IEEE EMBS CONFERENCE ON BIOMEDICAL ENGINEERING AND SCIENCES (IECBES) | 2016年
关键词：
Electroencephalogram (EEG); auditory evoked potential; Hearing threshold; Parametric modeling technique; EXTRACTION; RESPONSES; SIGNALS;
D O I：
暂无
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
In this paper, a simple method to determine the hearing threshold state of a subject using the parametric model of EEG time series signal has been investigated. The proposed autoregressive (AR) pole-tracking algorithm tracks the position of the poles and extracts the upper and lower hearing threshold factors of a subject. From the results, for abnormal hearing subjects, the hearing-threshold values are about 40-50 % higher than the normal hearing subjects. The results also show that the hearing threshold factors obtained using AR modeling clearly distinguishes the normal and abnormal hearing states across 20 subjects. The results obtained are promising and it can be used to determine the hearing-threshold state for newborns, infants, and multiple handicaps, a person who lacks verbal communication and behavioral response to the sound stimulation.
引用
收藏
页码：513 / 521
页数：9
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