Analysing wireless EEG based functional connectivity measures with respect to change in environmental factors

Biswas, Dwaipayan; Bono, Valentina; Scott-South, Michael; Chatterjee, Shre Kumar; Soska, Anna; Snow, Stephen; Noakes, Catherine; Barlow, Janet F.; Maharatna, Koushik; schraefel, m.c.

doi:10.1109/bhi.2016.7455969

Cited by 4 publications

(2 citation statements)

References 13 publications

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“…Artefact rejection was implemented in two stages. The first used the artefact rejection algorithm WPT-EMD [44,45], which uses a sample of minimum variance EEG taken from Condition 2. The second stage of artefact rejection involved an amplitude threshold cut-off of ±100 μV, and replacing outlying data with a 10-second moving median around the extreme value.…”

Section: Methodsmentioning

confidence: 99%

Using EEG to characterise drowsiness during short duration exposure to elevated indoor Carbon Dioxide concentrations

Snow

Boyson

Felipe-King

et al. 2018

Preprint

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1 Abstract: Drowsiness which can affect work performance, is often elicited through self-2 reporting. This paper demonstrates the potential to use EEG to objectively quantify changes to 3 drowsiness due to poor indoor air quality. Continuous EEG data was recorded from 23 4 treatment group participants subject to artificially raised indoor CO 2 concentrations (average 5 2,700 ± 300 ppm) for approximately 10 minutes and 13 control group participants subject to 6 the same protocol without additional CO 2 (average 830 ± 70 ppm). EEG data were analysed 7 for markers of drowsiness according neurophysiological methods at three stages of the 8 experiment, Baseline, High CO 2 and Post-Ventilation. Treatment group participants' EEG data 9 yielded a closer approximation to drowsiness than that of control group participants during the 10 High CO 2 condition, despite no significant group differences in self-reported sleepiness. Future 11 work is required to determine the persistence of these changes to EEG over longer exposures 12 and to better isolate the specific effect of CO 2 on drowsiness compared to other environmental 13 or physiological factors. 14 15 16 17 18 Practical implications: 19 This study introduces EEG as a potential objective indicator of the effect of indoor 20 environmental conditions upon drowsiness 21  Participants exposed to 2,700 ppm for 10 minutes showed greater evidence of a 22 progression towards drowsiness (as measured by EEG) than that of participants who 23 received the same protocol without additional CO 2 (mean 830 ± 70 ppm), despite 24 similar ratings of subjective sleepiness. 25 Subjective and objectively measured indications of drowsiness were reduced following 26 ventilation of the room. Future work could explore the potential of regular ventilation 27 episodes in knowledge work spaces to retain alertness. 3 28 29 Introduction 30 Being a product of human respiration, carbon dioxide (CO 2 ) increases in indoor spaces when 31 ventilation of the space is insufficient to replace stale air [1,2]. CO 2 is thus a useful indicator 32 of ventilation and, by extension air quality indoors, in occupied spaces [3,4]. A large body of 33 literature exists relating poor ventilation to mild health symptoms [2,5-7] and lowered 34 cognitive performance [4,8-10]. Office-realistic levels of CO 2 are reported to be typically < 35 3,000 ppm, but whether CO 2 itself negatively impacts cognitive performance, or whether other 36 pollutants such as volatile organic compounds (VOCs), including human bio-effluents, are 37 responsible, is still unclear [11,12]. Human performance effects have been recorded in studies 38 both where CO 2 is accompanied by human bio-effluents (e.g. the CO 2 concentration is a 39 product of poor ventilation in occupied spaces) [4,13,14] and where pure CO 2 gas is added to 40 a room to achieve steady-state concentrations [12,13,[15][16][17][18].41 At a room concentration of 3,000 ppm, human bio-effluents are found to cause an increase in 42 respired -end-tidal-CO 2 (ETCO 2 ), increased b...

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Section: Methodsmentioning

confidence: 99%

Using EEG to characterise drowsiness during short duration exposure to elevated indoor Carbon Dioxide concentrations

Snow

Boyson

Felipe-King

et al. 2018

Preprint

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“…et al [l46] and Besio, W. et al [47] examined the artifacts that occur when the electrodes were poorly connected. The influence of the environment on the electrode signal was considered by Biswas A. et al [48], muscle artifacts considered Chen, X. et al [49] and Richer, N [50] and eye movement artifacts, the most popular artifacts, presented in papers [69]. To solve this problem, a few researchers started to process EEG signals by neural networks [70,71,72].…”

Section: Introductionmentioning

confidence: 99%

Review Dry and Non-contact EEG Electrodes for 2010-2021 years

Rakhmatulin

Gan²

2021

SSRN Journal

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The basis of the work of electroencephalography (EEG) is the registration of electrical impulses from the brain or some of its individual areas using a special sensor/electrode. This method is used for the treatment and diagnosis of various diseases. The use of wet electrodes in this case does not seem viable, for several well-known reasons. As a result of this, a detailed analysis of modern EEG sensors developed over the past few years is carried out, which will allow researchers to choose this type of sensor more carefully and, as a result, conduct their research more competently. Due to the absence of any standards in the production and testing of dry EEG sensors, the main moment of this manuscript is a detailed description of the necessary steps for testing a dry electrode, which will allow researchers to maximize the potential of the sensor in the various type of research.

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A Novel Architecture Design for Complex Network Measures of Brain Connectivity Aiding Diagnosis

Pal

Acharyya

2021

Wearable/Personal Monitoring Devices Present to Future

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Analysing wireless EEG based functional connectivity measures with respect to change in environmental factors

Cited by 4 publications

References 13 publications

Using EEG to characterise drowsiness during short duration exposure to elevated indoor Carbon Dioxide concentrations

Using EEG to characterise drowsiness during short duration exposure to elevated indoor Carbon Dioxide concentrations

Review Dry and Non-contact EEG Electrodes for 2010-2021 years

A Novel Architecture Design for Complex Network Measures of Brain Connectivity Aiding Diagnosis

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