EEG-based index for engagement level monitoring during sustained attention

Coelli, Stefania; Sclocco, Roberta; Barbieri, Riccardo; Reni, Gianluigi; Zucca, Claudio; Bianchi, Anna Maria

doi:10.1109/embc.2015.7318658

Cited by 59 publications

(44 citation statements)

References 12 publications

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“…Beta band (12-30 Hz) has been linked to visual attention (Wróbel, 2000), short-term memory (Tallon-Baudry et al, 1999;Palva et al, 2011), and hypothesized to react to an increase in working memory (Spitzer and Haegens, 2017). An increase in beta power is associated with elevated mental workload levels during mental tasks (Coelli et al, 2015) and concentration (Kakkos et al, 2019). In addition, beta band activity reflects an arousal of the visual system during increased visual attention (Wróbel, 2000).…”

Section: Eeg Indicators Of Mental Workloadmentioning

confidence: 99%

Electroencephalographic Workload Indicators During Teleoperation of an Unmanned Aerial Vehicle Shepherding a Swarm of Unmanned Ground Vehicles in Contested Environments

et al. 2020

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Background: Although many electroencephalographic (EEG) indicators have been proposed in the literature, it is unclear which of the power bands and various indices are best as indicators of mental workload. Spectral powers (Theta, Alpha, and Beta) and ratios (Beta/(Alpha + Theta), Theta/Alpha, Theta/Beta) were identified in the literature as prominent indicators of cognitive workload. Objective: The aim of the present study is to identify a set of EEG indicators that can be used for the objective assessment of cognitive workload in a multitasking setting and as a foundational step toward a human-autonomy augmented cognition system. Methods: The participants' perceived workload was modulated during a teleoperation task involving an unmanned aerial vehicle (UAV) shepherding a swarm of unmanned ground vehicles (UGVs). Three sources of data were recorded from sixteen participants (n = 16): heart rate (HR), EEG, and subjective indicators of the perceived workload using the Air Traffic Workload Input Technique (ATWIT). Results: The HR data predicted the scores from ATWIT. Nineteen common EEG features offered a discriminatory power of the four workload setups with high classification accuracy (82.23%), exhibiting a higher sensitivity than ATWIT and HR. Conclusion: The identified set of features represents EEG indicators for the objective assessment of cognitive workload across subjects. These common indicators could be used for augmented intelligence in human-autonomy teaming scenarios, and form the basis for our work on designing a closed-loop augmented cognition system for human-swarm teaming.

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Section: Eeg Indicators Of Mental Workloadmentioning

confidence: 99%

Electroencephalographic Workload Indicators During Teleoperation of an Unmanned Aerial Vehicle Shepherding a Swarm of Unmanned Ground Vehicles in Contested Environments

et al. 2020

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“…For the current study, three main cognitive states were assessed: focus (concentration), anxiety, and approach motivation (AM). Focus is a general measure of mental engagement evidenced by beta activity in the frontal lobe (Coelli et al, 2015). Anxiety is associated with gamma waves in the parietal and occipital lobes (Oathes et al, 2008).…”

Section: Cognitive Indicatorsmentioning

confidence: 99%

“…A participant with AM presents more high-frequency waves (or an absence of alpha activity) on the left frontal lobe than the right (i.e., frontal asymmetry). AM is related to high levels of arousal, which not only may indicate positive emotion (e.g., happiness, excitement) but could also indicate aggression or anger (Coelli et al, 2015). Previous research has validated the use of frontal asymmetry to measure AM, associating the EEG markers with self-report items, such as “I go out of my way to get things I want” and “I crave excitement and new sensations” (Amodio, Master, Yee, & Taylor, 2008).…”

Section: Cognitive Indicatorsmentioning

confidence: 99%

Cognitive and Physiological Impacts of Adventure Activities: Beyond Self-Report Data

Bailey

Johann

Kang

2017

Journal of Experiential Education

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Outdoor adventure activities have been used to facilitate a variety of positive outcomes. However, the practical challenge of collecting data in the field and a heavy reliance on self-report data render it difficult to understand the process of the experience. This study examined the association between self-reported valence and arousal and electroencephalography (EEG)-measured anxiety, focus, and approach motivation to determine the physiological and cognitive response to stressful stimuli and compare those objective measures with self-report assessments. Data were collected from 10 participants fitted with an EEG headset during rappelling. Spearman correlations and repeated-measures ANOVA were used to analyze the data. Results indicated significant changes in EEG readings for anxiety and approach motivation, and significant correlations between self-reported valence and EEG-measured approach motivation. The findings illustrated the acute internal response to a common adventure activity and demonstrated the influence of a novel challenge on the mind and body of participants. Significant changes in self-report assessments were reflected in similar changes in objective measures, indicative of the mind/body connection.

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“…Interestingly, another study has suggested that the increase in alpha power spectrum plays an active role in preventing the distracting information into areas which retain the memory items ( Mazaheri et al, 2014 ). Moreover, previous studies have linked beta band to short-term memory ( Tallon-Baudry et al, 1999 ; Palva et al, 2011 ), elevated mental workload ( Coelli et al, 2015 ), or concentration ( Kakkos et al, 2019 ) as well as increasing in working memory ( Spitzer and Haegens, 2017 ). In the same line, the theta band is associated to increases in cognitive workload ( Fuentes-García et al, 2019 ; Diaz-Piedra et al, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

Neurophysiological Differences Between Women With Fibromyalgia and Healthy Controls During Dual Task: A Pilot Study

Villafaina¹,

Fuentes-García²,

Cano-Plasencia³

et al. 2020

Front. Psychol.

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Background Women with FM have a reduced ability to perform two simultaneous tasks. However, the impact of dual task (DT) on the neurophysiological response of women with FM has not been studied. Objective To explore both the neurophysiological response and physical performance of women with FM and healthy controls while performing a DT (motor–cognitive). Design Cross-sectional study. Methods A total of 17 women with FM and 19 age- and sex-matched healthy controls (1:1 ratio) were recruited. The electroencephalographic (EEG) activity was recorded while participants performed two simultaneous tasks: a motor (30 seconds arm-curl test) and a cognitive (remembering three unrelated words). Theta (4–7 Hz), alpha (8–12 Hz), and beta (13–30) frequency bands were analyzed by using EEGLAB. Results Significant differences were obtained in the healthy control group between single task (ST) and DT in the theta, alpha, and beta frequency bands ( p -value < 0.05). Neurophysiological differences between ST and DT were not found in women with FM. In addition, between-group differences were found in the alpha and beta frequency bands between healthy and FM groups, with lower values of beta and alpha in the FM group. Therefore, significant group ∗ condition interactions were detected in the alpha and beta frequency bands. Regarding physical condition performance, between groups, analyses showed that women with FM obtained significantly worse results in the arm curl test than healthy controls, in both ST and DT. Conclusion Women with FM showed the same electrical brain activity pattern during ST and DT conditions, whereas healthy controls seem to adapt their brain activity to task commitment. This is the first study that investigates the neurophysiological response of women with FM while simultaneously performing a motor and a cognitive task.

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EEG-based index for engagement level monitoring during sustained attention

Cited by 59 publications

References 12 publications

Electroencephalographic Workload Indicators During Teleoperation of an Unmanned Aerial Vehicle Shepherding a Swarm of Unmanned Ground Vehicles in Contested Environments

Electroencephalographic Workload Indicators During Teleoperation of an Unmanned Aerial Vehicle Shepherding a Swarm of Unmanned Ground Vehicles in Contested Environments

Cognitive and Physiological Impacts of Adventure Activities: Beyond Self-Report Data

Neurophysiological Differences Between Women With Fibromyalgia and Healthy Controls During Dual Task: A Pilot Study

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