International Conference on Information and Knowledge Technology

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BMPA- DSL: Binary Marine Predators Algorithm to Identify Driver's Different Levels of Stress

Authors :

Mahtab Vaezi¹ Mehdi Nasri² Farhad Azimifar³ Mahdi Mosleh⁴

1- Isfahan (Khorasgan) Branch, Islamic Azad University 2- Khomeinishahr branch, Islamic Azad University 3- Isfahan (Khorasgan) Branch, Islamic Azad University 4- Isfahan (Khorasgan) Branch, Islamic Azad University

Keywords :

driver's stress recognition،binary optimization،ECG،drivedb،heuristics feature selection،smart car

Abstract :

In smart cars, checking driver's conditions is necessary for safe driving. Stress is a destructive emotional state that causes drivers not to make timely decisions and brings irreparable risks. Therefore, detecting drivers' stress and giving timely warnings can prevent possible accidents. The best way to identify stress is to use bio-signals and intelligent processing algorithms. In the proposed method to identify drivers' stress, the drivedb database is used. Then, various statistical, frequency, entropy, and morphological characteristics have extracted from the ECG data of this database. In order to optimize the features, Binary Marine Predators Algorithm is used, which is a meta-heuristics method inspired by hunting prey by a marine in nature. Using two transfer functions, this algorithm can optimize features more than other heuristics optimizers. Using the proposed method, three states of low, medium, and high stress in drivers have been identified with 94.6% accuracy, which has increased the accuracy by 3-4% compared to the latest research in the field.