The Effect of Noise Exposure on Cognitive Performance and Brain Activity Patterns
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2021.12.1.24Keywords:
Noise; Cognitive Performance; Attention; Brain Activity; ElectroencephalogramDimensions Badge
Issue
Section
It seems qualitative measurements of subjective reactions are not appropriate indicators to assess the effect of noise on cognitive performance. In this study, quantitative and combined indicators were applied to study the effect of noise on cognitive performance. A total of 54 young subjects were included in this experimental study. The participants’ mental workload and attention were evaluated under different levels of noise exposure including, background noise, 75, 85 and 95 dBA noise levels. The study subject’s EEG signals were recorded for 10 minutes while they were performing the IVA test. The EEG signals were used to estimate the relative power of their brain frequency bands.Abstract
Results revealed that mental workload and visual/auditory attention is significantly reduced when the participants are exposed to noise at 95 dBA level (P < 0.05). Results also showed that with the rise in noise levels, the relative power of the Alpha band increases while the relative power of the Beta band decreases as compared to background noise. The most prominent change in the relative power of the Alpha and Beta bands occurs in the occipital and frontal regions of the brain respectively.
The application of new indicators, including brain signal analysis and power spectral density analysis, is strongly recommended in the assessment of cognitive performance during noise exposure. Further studies are suggested regarding the effects of other psychoacoustic parameters such as tonality, noise pitch (treble or bass) at extended exposure levels.
How to Cite
Downloads
Similar Articles
- ALKA SRIVASTAVA, SANJAY KUMAR, STUDY OF NUTRIENT VALUE IN POST HARVESTED INFECTED ORANGE (CITRUS SINENSIS) FRUIT , The Scientific Temper: Vol. 3 No. 1&2 (2012): The Scientific Temper
- R. Thiagarajan, S. Prakash Kumar, Performance of public transport appraisal using machine learning , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Shaik Abdulla P., Abdul Razak T., Retrieval-Based Inception V3-Net Algorithm and Invariant Data Classification using Enhanced Deep Belief Networks for Content-Based Image Retrieval , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- M. Iniyan, A. Banumathi, Brower blowfish nash secured stochastic neural network based disease diagnosis for medical WBAN in cloud environment , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Ankeeta Vispute, Muskaan Vasaya, Sagar Deshpande , Impact of rheumatoid arthrtis on functional limitations of wrist and hand , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- C. Agilan, Lakshna Arun, Optimization-based clustering feature extraction approach for human emotion recognition , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- M. Prabhu, A. Chandrabose, Optimization based energy aware scheduling in wireless sensor networks , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Lakshminarayani A, A Shaik Abdul Khadir, A blockchain-integrated smart healthcare framework utilizing dynamic hunting leadership algorithm with deep learning-based disease detection and classification model , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- Shapali Devi, Sadguru Prakash, Ravindra Pratap Singh, Rahul Singh, Polylactic Acid: A Bio-Based Polymer as an Emerging Substitute for Plastics , The Scientific Temper: Vol. 13 No. 02 (2022): The Scientific Temper
- Hemamalini V., Victoria Priscilla C, Deep learning driven image steganalysis approach with the impact of dilation rate using DDS_SE-net on diverse datasets , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
<< < 1 2 3 4 5 6 7 8 9 10 > >>
You may also start an advanced similarity search for this article.