Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14365/5850
Title: | Investigating the Effect of Noise Levels on Mental Tasks Using Artificial Intelligence | Authors: | Sipahioglu, E. Akbugday, B. Akbugday, S.P. Akan, A. |
Keywords: | Artificial Intelligence Eeg Environment Machine Learning N-Back Task Noise Ppg Working Memory |
Publisher: | Institute of Electrical and Electronics Engineers Inc. | Abstract: | The impact of stress on daily life has been a subject of interest in the last decades. The utilization of numerous electrical and electronic devices as well as increased land and air transportation densities constantly create noise which is a significant contributor to stress. In this study, the relationship between environmental noise, cognitive workload, and stress is investigated. Electroencephalogram (EEG) and photoplethysmogram (PPG) signals of 30 volunteers were recorded simultaneously while performing a 2-back task with different background noise levels. Features were then extracted from the processed signals to be classified with various machine learning algorithms. Results show that medium noise levels result in increased accuracy for the 2-back task which indicates keeping the noise levels at an acceptable level would be better for work and learning environments. © 2024 IEEE. | URI: | https://doi.org/10.1109/TIPTEKNO63488.2024.10755381 https://hdl.handle.net/20.500.14365/5850 |
ISBN: | 979-833152981-9 |
Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
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