Design and implementation of smart driving system using context recognition system

Author

Kim, Taehyun ; Kim, Soohan ; Shin, DongKyoo ; Shin, Dongil

Author_Institution

Dept. of Comput. Eng., Sejong Univ., Seoul, South Korea

fYear

2011

fDate

20-23 March 2011

Firstpage

84

Lastpage

89

Abstract

In this paper, we develop a context recognition system that is based on multimodal biometric signals and applicable to smart driving system. The context recognition system includes a biometric analysis module that analyzes and recognizes human biometric signal patterns. The context recognition system can recognize a user´s emotion and level of concentration by analyzing ECG (electrocardiogram) and EEG (electroencephalogram) patterns. To predict the concentration and stress status of the user, the electroencephalogram rendering system utilizes 5 signal values: MID_BETA, THETA, ALPHA, DELTA, and GAMMA. Also, electrocardiogram analysis system utilizes 5 basic signal values: P, Q, R, S, T wave. To recognize the user´s electrocardiogram signal patterns, a deformation K-means-based EM algorithm was applied.

Keywords

biometrics (access control); driver information systems; electrocardiography; electroencephalography; rendering (computer graphics); signal processing; ECG pattern; EEG pattern; context recognition system; deformation K-means-based EM algorithm; electroencephalogram rendering system; human biometric signal patterns; multimodal biometric signals; smart driving system; Context; Electrocardiography; Electroencephalography; Emotion recognition; Humans; Sensors; Stress;

fLanguage

English

Publisher

ieee

Conference_Titel

Computers & Informatics (ISCI), 2011 IEEE Symposium on

Conference_Location

Kuala Lumpur

Print_ISBN

978-1-61284-689-7

Type

conf

DOI

10.1109/ISCI.2011.5958889

Filename

5958889