Cognitive State Estimation Based on EEG for Augmented Cognition

Erdoğmuş, Deni̇z; Adami, André Gustavo; Pavel, M.; Lan, Tian; Mathan, Santosh; Whitlow, Stephen D.; Dorneich, Michael C.

doi:10.1109/cne.2005.1419686

Cited by 18 publications

(16 citation statements)

References 8 publications

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“…The process of selecting the training data set is repeated 5 times, generating 5 different sets, and the average and standard deviations of the classification results are calculated and reported. The exact numbers of feature vectors for subjects [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16] …”

Section: Resultsmentioning

confidence: 99%

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Novel Classification System for Classifying Cognitive Workload Levels Under Vague Visual Stimulation

et al. 2017

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Abstract-This paper presents a novel method for classifying four different levels of cognitive workload. The workload levels are generated using visual stimuli degradation. EEG signals recorded from 16 subjects were used for workload classification. The proposed solution includes preprocessing of EEG signals and feature extraction based on statistical features. This is followed by variable selection using stepwise regression and multiclass linear classification. The presented method achieved an average classification accuracy of 93.4%. The effect of EEG channel selection on the classification accuracy is also investigated. In comparison to the existing work, we show that the proposed solution is more accurate and computationally less demanding.

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Section: Resultsmentioning

confidence: 99%

“…Such degradation can affect the memory, the learning process and decision-making process. Internal and external factors, such as the level of noise in the environment, can affect the current cognitive state and workload [6].…”

Section: Introductionmentioning

confidence: 99%

Novel Classification System for Classifying Cognitive Workload Levels Under Vague Visual Stimulation

et al. 2017

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“…In such studies of augmented cognition, assistance often involves detection and utilization of the human operator's mental state to optimize performance (Dorneich et al, 2003;Schmorrow and McBride, 2004;Erdogmus et al, 2005;Greitzer, 2005;Ivory et al, 2005;Miller and Dorneich, 2006;Carlson et al, 2007;Fuchs et al, 2007b;Kollmorgen, 2007;Schmorrow and Reeves, 2007;Barber et al, 2008;Ushakov and Bubeev, 2008;Vogel-Walcutt et al, 2008;Agarwal and Dagli, 2013;Kolsch et al, 2013;Abbass et al, 2014;Putze and Schultz, 2014).…”

Section: Augmented Cognition Human-agent Human-robot Human-swarm Imentioning

confidence: 99%

Human Strategies for Multitasking, Search, and Control Improved via Real-Time Memory Aid for Gaze Location

Taylor

Bilgrien

et al. 2015

Front. ICT

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Objective: We aimed to elucidate how our domain-general cuing algorithm improved multitasking performance and changed behavioral strategies in human operators.Background: Though many gaze-control systems have been designed, previous realtime gaze-aware assistance systems were not both successful and domain-general. It is largely unknown what constitutes optimal search efficiency using the eyes, or ideal control using the mouse. It is unclear what the best coordinating strategies are between these two modalities. Our previously developed closed-loop multitasking aid drastically improved multitasking performance, though the behavioral mechanisms through which it acted were unknown. Methods:We performed in-depth analyses and generated novel eye tracking and mouse movement measures, to explore the complex effects of our helpful system on gaze and motor behavior.Results: Our overlay cuing algorithm improved control efficiency and reduced wellknown biases in search patterns. This system also reduced micromanaging behavior, with humans rationally relying more on imperfect automation in experimental assistance cue conditions. We showed that mouse and gaze were more independently specialized in the helpful cuing condition than in control conditions. Specifically, with our aid, the gaze performed more global movement, and the mouse performed more local clustered movement. Further, the gaze shifted toward search over processing with the helpful cuing system. We also illustrated a relationship between the mouse and the gaze, such that in these studies, "the hand was quicker than the eye." Conclusion:Overall, results suggested that our cuing system improved performance and reduced short-term working memory load on humans by delegating it to the computer in real time. Further, it reduced the number of required repeated decisions by an estimate of about one per second. It also enabled the gaze to specialize for improved visual search behavior, and the mouse to specialize for improved control.

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“…Attempts have been made to study and model Cognition using EEG waves [1][2]. Cognitive state estimations have been done using EEG waves [3]. Neural signals are obtained by placing electrodes on the scalp and measuring small electrical signals called EEG brainwaves.…”

Section: Introductionmentioning

confidence: 99%

Quantifying cognitive impairment due to physical or mental stress

Gupta

Dantu

2013

Proceedings of the 6th International Conference on PErvasive Technologies Related to Assistive Environments

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In this paper, we study impairment caused by physical stress and impairment caused by alcohol consumption. We first base line the EEG waves in a meditation state. Then we measure the EEG waves during the physical activities such as walking, climbing stairs and doing sit-ups. We also measure the effect on brain as a person spins while sitting in a revolving chair (simulating a mental stress). Finally, we measure the EEG waves after consumption of alcohol. Our study shows that EEG waves do capture the physical activities that cause impairment. The magnitude of EEG waves increases with increased intensity of stress as measured by physical exercise or alcohol consumption. The magnitude is highest for sit-ups as compared to other activities and the magnitude for sit-ups after alcohol is even higher when compared with magnitude before alcohol consumption. A higher magnitude means lower level of alertness. The results could be used to improve the care of elderly and plan the intensity of their physical activity.

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Cognitive State Estimation Based on EEG for Augmented Cognition

Cited by 18 publications

References 8 publications

Novel Classification System for Classifying Cognitive Workload Levels Under Vague Visual Stimulation

Novel Classification System for Classifying Cognitive Workload Levels Under Vague Visual Stimulation

Human Strategies for Multitasking, Search, and Control Improved via Real-Time Memory Aid for Gaze Location

Quantifying cognitive impairment due to physical or mental stress

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