Literature DB >> 33451080

Comparison of Smoothing Filters' Influence on Quality of Data Recorded with the Emotiv EPOC Flex Brain-Computer Interface Headset during Audio Stimulation.

Natalia Browarska1, Aleksandra Kawala-Sterniuk1, Jaroslaw Zygarlicki1, Michal Podpora1, Mariusz Pelc1,2, Radek Martinek3, Edward Jacek Gorzelańczyk4,5,6.   

Abstract

Off-the-shelf, consumer-grade EEG equipment is nowadays becoming the first-choice equipment for many scientists when it comes to recording brain waves for research purposes. On one hand, this is perfectly understandable due to its availability and relatively low cost (especially in comparison to some clinical-level EEG devices), but, on the other hand, quality of the recorded signals is gradually increasing and reaching levels that were offered just a few years ago by much more expensive devices used in medicine for diagnostic purposes. In many cases, a well-designed filter and/or a well-thought signal acquisition method improve the signal quality to the level that it becomes good enough to become subject of further analysis allowing to formulate some valid scientific theories and draw far-fetched conclusions related to human brain operation. In this paper, we propose a smoothing filter based upon the Savitzky-Golay filter for the purpose of EEG signal filtering. Additionally, we provide a summary and comparison of the applied filter to some other approaches to EEG data filtering. All the analyzed signals were acquired from subjects performing visually involving high-concentration tasks with audio stimuli using Emotiv EPOC Flex equipment.

Entities:  

Keywords:  Brain-Computer Interfaces; Emotiv Flex; digital filtering; electroencephalography; signal processing

Year:  2021        PMID: 33451080      PMCID: PMC7828570          DOI: 10.3390/brainsci11010098

Source DB:  PubMed          Journal:  Brain Sci        ISSN: 2076-3425


  37 in total

1.  Differences in event-related and induced EEG patterns in the theta and alpha frequency bands related to human emotional intelligence.

Authors:  N Jausovec; K Jausovec; I Gerlic
Journal:  Neurosci Lett       Date:  2001-09-28       Impact factor: 3.046

2.  Towards a neural basis of music perception.

Authors:  Stefan Koelsch; Walter A Siebel
Journal:  Trends Cogn Sci       Date:  2005-11-03       Impact factor: 20.229

3.  Tactile and bone-conduction auditory brain computer interface for vision and hearing impaired users.

Authors:  Tomasz M Rutkowski; Hiromu Mori
Journal:  J Neurosci Methods       Date:  2014-04-21       Impact factor: 2.390

4.  Subject-specific EEG channel selection using non-negative matrix factorization for lower-limb motor imagery recognition.

Authors:  Dharmendra Gurve; Denis Delisle-Rodriguez; Maria Romero-Laiseca; Vivianne Cardoso; Flavia Loterio; Teodiano Bastos; Sri Krishnan
Journal:  J Neural Eng       Date:  2020-04-08       Impact factor: 5.379

5.  A validation of Emotiv EPOC Flex saline for EEG and ERP research.

Authors:  Nikolas S Williams; Genevieve M McArthur; Bianca de Wit; George Ibrahim; Nicholas A Badcock
Journal:  PeerJ       Date:  2020-08-11       Impact factor: 2.984

6.  Effects of diazepam and zolpidem on EEG beta frequencies are behavior-specific in rats.

Authors:  Hester van Lier; Wilhelmus H I M Drinkenburg; Yvonne J W van Eeten; Anton M L Coenen
Journal:  Neuropharmacology       Date:  2004-08       Impact factor: 5.250

7.  Pitch Syntax Violations Are Linked to Greater Skin Conductance Changes, Relative to Timbral Violations - The Predictive Role of the Reward System in Perspective of Cortico-subcortical Loops.

Authors:  Edward J Gorzelańczyk; Piotr Podlipniak; Piotr Walecki; Maciej Karpiński; Emilia Tarnowska
Journal:  Front Psychol       Date:  2017-04-18

8.  Music Improvisation Is Characterized by Increase EEG Spectral Power in Prefrontal and Perceptual Motor Cortical Sources and Can be Reliably Classified From Non-improvisatory Performance.

Authors:  Masaru Sasaki; John Iversen; Daniel E Callan
Journal:  Front Hum Neurosci       Date:  2019-12-10       Impact factor: 3.169

Review 9.  Summary of over Fifty Years with Brain-Computer Interfaces-A Review.

Authors:  Aleksandra Kawala-Sterniuk; Natalia Browarska; Amir Al-Bakri; Mariusz Pelc; Jaroslaw Zygarlicki; Michaela Sidikova; Radek Martinek; Edward Jacek Gorzelanczyk
Journal:  Brain Sci       Date:  2021-01-03

10.  Toward a compact hybrid brain-computer interface (BCI): Performance evaluation of multi-class hybrid EEG-fNIRS BCIs with limited number of channels.

Authors:  Jinuk Kwon; Jaeyoung Shin; Chang-Hwan Im
Journal:  PLoS One       Date:  2020-03-18       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.