Study on the Effect of Man-Machine Response Mode to Relieve Driving Fatigue Based on EEG and EOG

Wang, Fuwang; Xu, Qing; Fu, Rongrong

doi:10.3390/s19224883

Cited by 17 publications

(19 citation statements)

References 60 publications

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“…From a total score of 8, the studies that obtained a score of 5 or above (>60%) were considered acceptable in terms of scientific quality. Only 19 of the 34 studies obtained a score of 5 or above, and three studies obtained the highest score of 7.5 (Di Stasi, McCamy, Catena, et al., 2013; Di Stasi et al., 2012; Wang et al., 2019). Twenty studies obtained a full score on the quality assessment criterion 1 and provided an explicit definition of the metrics and the signal processing techniques used on the metric.…”

Section: Resultsmentioning

confidence: 99%

“…Nine of the studies conducted multi-modal measurement of fatigue using EEG (Gergelyfi et al, 2015;Guo et al, 2018;Hopstaken et al, ,2015Hopstaken et al, , , 2015aHopstaken et al, , , 2016Sengupta et al, 2017;Wang et al, 2019), ECG (Abbasi et al, 2018;Horiuchi et al, 2018), and functional near-infrared spectroscopy (fNIRS; Borragán et al, 2018) and were able to confirm the corresponding measurements of mental fatigue using eyebased metrics.…”

Section: Mental Fatigue Recording Methodsmentioning

confidence: 99%

“…However, the use of the equipment for fatigue detection has not been brought into real-time scenarios. This is also discernible when reading the papers that used real-life scenarios of fatigue development and detection, in fields like health care , the military (Diaz-Piedra et al, 2016;LeDuc et al, 2005), or transportation Li, Chen et al, 2019;Wang et al, 2019). These would be the ideal situations where non-invasive, wearable equipment could continuously track the physiological signals.…”

Section: Taking Advantage Of Noninvasive Equipmentmentioning

confidence: 99%

“…The use of the fourth method of physiological signals and gaze behavior for mental fatigue measurement has increased in frequency, with the increasingly mobile and accurate technologies of electroencephalography (EEGGergelyfi et al., 2015; Guo et al., 2018; Hopstaken et al., ,2015, 2015a, 2016; Sengupta et al., 2017; Wang et al., 2019), electrocardiography (ECG; Abbasi et al., 2018; Horiuchi et al., 2018), EOG and eye‐tracking. Continuous fatigue measurement using these technologies provides data that is unhampered by subjective bias and does not require taking a break from an ongoing task.…”

Section: Introductionmentioning

confidence: 99%

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Mental fatigue measurement using eye metrics: A systematic literature review

Bafna

Hansen

2021

Psychophysiology

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Mental fatigue measurement techniques utilize one or a combination of the cognitive, affective, and behavioral responses of the body. Eye-tracking and electrooculography, which are used to compute eye-based features, have gained momentum with increases in accuracy and robustness of the lightweight equipment emerging in the markets and can be used for objective and continuous assessment of mental fatigue. The main goal of this systematic review was to summarize the various eye-based features that have been used to measure mental fatigue and explore the relation of eye-based features to mental fatigue. The review process, following the preferred reporting items for systematic reviews and meta-analyses, used the electronic databases Web of Science, Scopus, ACM digital library, IEEE Xplore, and PubMed. Of the 1,385 retrieved documents, 34 studies met the inclusion criteria, resulting in 21 useful eye-based features. Categorizing these into eight groups revealed saccades as the most promising category, with saccade mean and peak velocity providing quick access to the cognitive states within 30 min of fatiguing activity. Complex brain networks involving sympathetic and parasympathetic nervous systems control the relation of mental fatigue to tonic pupil size and have the potential to indicate mental fatigue in controlled experimental conditions. Other categories, like blinks, are derived from the field of sleep research and should be used with caution. Several limitations emerged in the analysis, including varied experimental methods, use of dim lighting during the experiment (that could possibly also induce sleepiness), and use of unclear data analysis techniques, thereby complicating comparisons between studies.

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Section: Resultsmentioning

confidence: 99%

Section: Mental Fatigue Recording Methodsmentioning

confidence: 99%

Section: Taking Advantage Of Noninvasive Equipmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mental fatigue measurement using eye metrics: A systematic literature review

Bafna

Hansen

2021

Psychophysiology

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“…Frontiers in Neuroergonomics | www.frontiersin.org Wang et al (2019) List of all references from 2010 to that used combined EEG-EOG methods. The references are classified by domain of application.…”

Section: Methodology Of the Reviewmentioning

confidence: 99%

Electro-Encephalography and Electro-Oculography in Aeronautics: A Review Over the Last Decade (2010–2020)

Belkhiria¹,

Peysakhovich²

2020

Front. Neuroergonomics

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Electro-encephalography (EEG) and electro-oculography (EOG) are methods of electrophysiological monitoring that have potentially fruitful applications in neuroscience, clinical exploration, the aeronautical industry, and other sectors. These methods are often the most straightforward way of evaluating brain oscillations and eye movements, as they use standard laboratory or mobile techniques. This review describes the potential of EEG and EOG systems and the application of these methods in aeronautics. For example, EEG and EOG signals can be used to design brain-computer interfaces (BCI) and to interpret brain activity, such as monitoring the mental state of a pilot in determining their workload. The main objectives of this review are to, (i) offer an in-depth review of literature on the basics of EEG and EOG and their application in aeronautics; (ii) to explore the methodology and trends of research in combined EEG-EOG studies over the last decade; and (iii) to provide methodological guidelines for beginners and experts when applying these methods in environments outside the laboratory, with a particular focus on human factors and aeronautics. The study used databases from scientific, clinical, and neural engineering fields. The review first introduces the characteristics and the application of both EEG and EOG in aeronautics, undertaking a large review of relevant literature, from early to more recent studies. We then built a novel taxonomy model that includes 150 combined EEG-EOG papers published in peer-reviewed scientific journals and conferences from January 2010 to March 2020. Several data elements were reviewed for each study (e.g., pre-processing, extracted features and performance metrics), which were then examined to uncover trends in aeronautics and summarize interesting methods from this important body of literature. Finally, the review considers the advantages and limitations of these methods as well as future challenges.

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