Reducing Sketch Inhibition During Concept Generation: Psychophysiological Evidence of the Effect of Interventions

2015 ◽  
Author(s):  
Wan-Lin Hu ◽  
Joran Booth ◽  
Tahira Reid
Keyword(s):  
Mental Workload ◽  
Self Report ◽  
Cognitive State ◽  
Concept Generation ◽  
Warm Up ◽  
Cognitive States ◽  
Test Conditions ◽  
Skin Response ◽  
Nasa Tlx ◽  
Art Activities

This research investigated the effect of warm-up activities on cognitive states during concept generation. Psychophysiological tools including electroencephalography (EEG) and galvanic skin response (GSR) were used along with self-report measures (NASA TLX). Participants were divided into 3 test conditions: 1) no warm-up activity; 2) simple warm-up activities; 3) sketch-inhibition reducing activities. All participants did the same short design task. Results show that those who did a warm-up prior to ideation had a decrease in stress, especially for those who were personally familiar with the design problem. The art activities especially improved engagement for younger participants. We also saw that females who used the art-based activities reported lower mental workload during ideation and greater pride in their sketches. However, the warm-ups did not produce any difference in the number of ideas or other metrics of performance. These preliminary results indicate that warm-up activities, especially the art-based ones, help reduce inhibition by calming the cognitive state.

This Is Your Brain on Autopilot: Neural Indices of Driver Workload and Engagement During Partial Vehicle Automation

2021 ◽  
pp. 001872082110390
Author(s):  
Amy S. McDonnell ◽  
Trent G. Simmons ◽  
Gus G. Erickson ◽  
Monika Lohani ◽  
Joel M. Cooper ◽  
...  
Keyword(s):  
Mental Workload ◽  
Cognitive State ◽  
Alpha Power ◽  
Age Cohorts ◽  
Cognitive States ◽  
Driver Workload ◽  
Automated Technology ◽  
Vehicle Automation ◽  
Visual Engagement ◽  
Insight Into

Objective This research explores the effect of partial vehicle automation on neural indices of mental workload and visual engagement during on-road driving. Background There is concern that the introduction of automated technology in vehicles may lead to low driver stimulation and subsequent disengagement from the driving environment. Simulator-based studies have examined the effect of automation on a driver’s cognitive state, but it is unknown how the conclusions translate to on-road driving. Electroencephalographic (EEG) measures of frontal theta and parietal alpha can provide insight into a driver’s mental workload and visual engagement while driving under various conditions. Method EEG was recorded from 71 participants while driving on the roadway. We examined two age cohorts, on two different highway configurations, in four different vehicles, with partial vehicle automation both engaged and disengaged. Results Analysis of frontal theta and parietal alpha power revealed that there was no change in mental workload or visual engagement when driving manually compared with driving under partial vehicle automation. Conclusion Drivers new to the technology remained engaged with the driving environment when operating under partial vehicle automation. These findings suggest that the concern surrounding driver disengagement under vehicle automation may need to be tempered, at least for drivers new to the experience. Application These findings expand our understanding of the effects of partial vehicle automation on drivers’ cognitive states.

scholarly journals Workload assessment for mental arithmetic tasks using the task-evoked pupillary response

2015 ◽  
Author(s):  
Gerhard Marquart ◽  
Joost de Winter
Keyword(s):  
Mental Arithmetic ◽  
Pupil Diameter ◽  
Mental Workload ◽  
Self Report ◽  
Blink Rate ◽  
Eye Tracker ◽  
Practical Applications ◽  
The Mean ◽  
Nasa Tlx ◽  
Diameter Change

Pupillometry is a promising method for assessing mental workload and could be helpful in the optimization of systems that involve human-computer interaction. The present study focuses on replicating the studies by Ahern (1978) and Klingner (2010), which found that for three levels of difficulty of mental multiplications, the more difficult multiplications yielded larger dilations of the pupil. Using a remote eye tracker, our research expands upon these two previous studies by statistically testing for each 1.5 s interval of the calculation period (1) the mean absolute pupil diameter (MPD), (2) the mean pupil diameter change (MPDC) with respect to the pupil diameter during the pre-stimulus accommodation period, and (3) the mean pupil diameter change rate (MPDCR). An additional novelty of our research is that we compared the pupil diameter measure with a self-report measure of workload, the NASA Task Load Index (NASA-TLX), and with the mean blink rate (MBR). The results showed that the findings of Ahern and Klingner were replicated, and that the MPD and MPDC discriminated just as well between the lowest and highest difficulty levels as did the NASA-TLX. The MBR, on the other hand, did not interpretably differentiate between the difficulty levels. Moderate to strong correlations were found between the MPDC and the proportion of incorrect responses, indicating that the MPDC was higher for participants with a poorer performance. For practical applications, validity could be improved by combining pupillometry with other physiological techniques.

scholarly journals Classification of BCI Users Based on Cognition

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
N. Firat Ozkan ◽  
Emin Kahya
Keyword(s):  
Brain Computer Interface ◽  
Computer Interface ◽  
Cognitive State ◽  
Blink Rate ◽  
Computer Interfaces ◽  
Skin Response ◽  
Nasa Tlx ◽  
Healthy Participants ◽  
And Task

Brain-Computer Interfaces (BCI) are systems originally developed to assist paralyzed patients allowing for commands to the computer with brain activities. This study aims to examine cognitive state with an objective, easy-to-use, and easy-to-interpret method utilizing Brain-Computer Interface systems. Seventy healthy participants completed six tasks using a Brain-Computer Interface system and participants’ pupil dilation, blink rate, and Galvanic Skin Response (GSR) data were collected simultaneously. Participants filled Nasa-TLX forms following each task and task performances of participants were also measured. Cognitive state clusters were created from the data collected using the K-means method. Taking these clusters and task performances into account, the general cognitive state of each participant was classified as low risk or high risk. Logistic Regression, Decision Tree, and Neural Networks were also used to classify the same data in order to measure the consistency of this classification with other techniques and the method provided a consistency between 87.1% and 100% with other techniques.

scholarly journals Workload assessment for mental arithmetic tasks using the task-evoked pupillary response

2015 ◽  
Author(s):  
Gerhard Marquart ◽  
Joost de Winter
Keyword(s):  
Mental Arithmetic ◽  
Pupil Diameter ◽  
Mental Workload ◽  
Self Report ◽  
Blink Rate ◽  
Eye Tracker ◽  
Practical Applications ◽  
The Mean ◽  
Nasa Tlx ◽  
Diameter Change

Pupillometry is a promising method for assessing mental workload and could be helpful in the optimization of systems that involve human-computer interaction. The present study focuses on replicating the studies by Ahern (1978) and Klingner (2010), which found that for three levels of difficulty of mental multiplications, the more difficult multiplications yielded larger dilations of the pupil. Using a remote eye tracker, our research expands upon these two previous studies by statistically testing for each 1.5 s interval of the calculation period (1) the mean absolute pupil diameter (MPD), (2) the mean pupil diameter change (MPDC) with respect to the pupil diameter during the pre-stimulus accommodation period, and (3) the mean pupil diameter change rate (MPDCR). An additional novelty of our research is that we compared the pupil diameter measure with a self-report measure of workload, the NASA Task Load Index (NASA-TLX), and with the mean blink rate (MBR). The results showed that the findings of Ahern and Klingner were replicated, and that the MPD and MPDC discriminated just as well between the lowest and highest difficulty levels as did the NASA-TLX. The MBR, on the other hand, did not interpretably differentiate between the difficulty levels. Moderate to strong correlations were found between the MPDC and the proportion of incorrect responses, indicating that the MPDC was higher for participants with a poorer performance. For practical applications, validity could be improved by combining pupillometry with other physiological techniques.

Aligning Brain Activity and Sketch in Multi-Modal CAD Interface

2014 ◽  
Author(s):  
Somayeh B. Shafiei ◽  
Ehsan Tarkesh Esfahani
Keyword(s):  
Time Window ◽  
Mental Workload ◽  
Brain Activity ◽  
Time Lag ◽  
Cognitive State ◽  
Eeg Signals ◽  
Scalp Eeg ◽  
Cognitive States ◽  
Series Of Experiments ◽  
Dynamic Time

This paper investigates the proper synchronization of sketch data and cognitive states in a multi-modal CAD interface. In a series of experiments, 5 subjects were instructed to watch and then explain 6 mechanical mechanisms by sketching them on a touch based screen. Simultaneously, subject’s brain waves were recorded in terms of electroencephalogram (EEG) signals from 9 locations on the scalp. EEG signals were analyzed and translated into mental workload and cognitive state. A dynamic time window was then constructed to align these features with sketch features such that the combination of two modalities maximizes the classification of gesture from non-gesture strokes. Quadratic Discriminant Analysis (QDA) was used as classification method. Our experimental results show that the best temporal alignment for workload and sketch analysis starts from 30% time lag with previous stroke and ends before 30% time lag with next stroke.

scholarly journals A Systematic Review for Cognitive State-Based QoE/UX Evaluation

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3439
Author(s):  
Edgar Bañuelos-Lozoya ◽  
Gabriel González-Serna ◽  
Nimrod González-Franco ◽  
Olivia Fragoso-Diaz ◽  
Noé Castro-Sánchez
Keyword(s):  
Systematic Review ◽  
User Experience ◽  
Mental Workload ◽  
Cognitive State ◽  
Sources Of Information ◽  
Cognitive States ◽  
Starting Point ◽  
The Relationship

Traditional evaluation of user experience is subjective by nature, for what is sought is to use data from physiological and behavioral sensors to interpret the relationship that the user’s cognitive states have with the elements of a graphical interface and interaction mechanisms. This study presents the systematic review that was developed to determine the cognitive states that are being investigated in the context of Quality of Experience (QoE)/User Experience (UX) evaluation, as well as the signals and characteristics obtained, machine learning models used, evaluation architectures proposed, and the results achieved. Twenty-nine papers published in 2014–2019 were selected from eight online sources of information, of which 24% were related to the classification of cognitive states, 17% described evaluation architectures, and 41% presented correlations between different signals, cognitive states, and QoE/UX metrics, among others. The amount of identified studies was low in comparison with cognitive state research in other contexts, such as driving or other critical activities; however, this provides a starting point to analyze and interpret states such as mental workload, confusion, and mental stress from various human signals and propose more robust QoE/UX evaluation architectures.

Context-specific abnormalities of the central executive network in first-episode psychosis: relationship with cognition

2020 ◽  
pp. 1-10
Author(s):  
Deepak K. Sarpal ◽  
Goda Tarcijonas ◽  
Finnegan J. Calabro ◽  
William Foran ◽  
Gretchen L. Haas ◽  
...  
Keyword(s):  
Cognitive Control ◽  
Psychotic Disorders ◽  
First Episode Psychosis ◽  
First Episode ◽  
Cognitive State ◽  
Cognitive States ◽  
Episode Psychosis ◽  
Dorsolateral Prefrontal ◽  
Parietal Lobule ◽  
Context Specific

Abstract Background Cognitive impairments, which contribute to the profound functional deficits observed in psychotic disorders, have found to be associated with abnormalities in trial-level cognitive control. However, neural tasks operate within the context of sustained cognitive states, which can be assessed with ‘background connectivity’ following the removal of task effects. To date, little is known about the integrity of brain processes supporting the maintenance of a cognitive state in individuals with psychotic disorders. Thus, here we examine background connectivity during executive processing in a cohort of participants with first-episode psychosis (FEP). Methods The following fMRI study examined background connectivity of the dorsolateral prefrontal cortex (DLPFC), during working memory engagement in a group of 43 patients with FEP, relative to 35 healthy controls (HC). Findings were also examined in relation to measures of executive function. Results The FEP group relative to HC showed significantly lower background DLPFC connectivity with bilateral superior parietal lobule (SPL) and left inferior parietal lobule. Background connectivity between DLPFC and SPL was also positively associated with overall cognition across all subjects and in our FEP group. In comparison, resting-state frontoparietal connectivity did not differ between groups and was not significantly associated with overall cognition, suggesting that psychosis-related alterations in executive networks only emerged during states of goal-oriented behavior. Conclusions These results provide novel evidence indicating while frontoparietal connectivity at rest appears intact in psychosis, when engaged during a cognitive state, it is impaired possibly undermining cognitive control capacities in FEP.

Evaluation of Subjective Mental Workload: A Comparison of SWAT, NASA-TLX, and Workload Profile Methods

2004 ◽  
Vol 53 (1) ◽  
pp. 61-86 ◽  
Author(s):  
Susana Rubio ◽  
Eva Diaz ◽  
Jesus Martin ◽  
Jose M. Puente
Keyword(s):  
Mental Workload ◽  
Nasa Tlx

scholarly journals Can EEG Be Adopted as a Neuroscience Reference for Assessing Software Programmers’ Cognitive Load?

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2338
Author(s):  
Júlio Medeiros ◽  
Ricardo Couceiro ◽  
Gonçalo Duarte ◽  
João Durães ◽  
João Castelhano ◽  
...  
Keyword(s):  
Software Development ◽  
Cognitive Load ◽  
Mental Effort ◽  
Research Area ◽  
Cognitive State ◽  
Accurate Identification ◽  
Cognitive States ◽  
Code Complexity ◽  
Time Accuracy ◽  
Future Evaluation

An emergent research area in software engineering and software reliability is the use of wearable biosensors to monitor the cognitive state of software developers during software development tasks. The goal is to gather physiologic manifestations that can be linked to error-prone scenarios related to programmers’ cognitive states. In this paper we investigate whether electroencephalography (EEG) can be applied to accurately identify programmers’ cognitive load associated with the comprehension of code with different complexity levels. Therefore, a controlled experiment involving 26 programmers was carried. We found that features related to Theta, Alpha, and Beta brain waves have the highest discriminative power, allowing the identification of code lines and demanding higher mental effort. The EEG results reveal evidence of mental effort saturation as code complexity increases. Conversely, the classic software complexity metrics do not accurately represent the mental effort involved in code comprehension. Finally, EEG is proposed as a reference, in particular, the combination of EEG with eye tracking information allows for an accurate identification of code lines that correspond to peaks of cognitive load, providing a reference to help in the future evaluation of the space and time accuracy of programmers’ cognitive state monitored using wearable devices compatible with software development activities.

The Effects of Practice on Navigation Performance and Mental Workload with a Mirror-In-The-Sky Map

2021 ◽  
Vol 65 (1) ◽  
pp. 1546-1550
Author(s):  
Holland M. Vasquez ◽  
Justin G. Hollands ◽  
Greg A. Jamieson
Keyword(s):  
Task Performance ◽  
Secondary Task ◽  
Mental Workload ◽  
Task Completion ◽  
Practice Performance ◽  
Global Ratings ◽  
Detection Response ◽  
Nasa Tlx ◽  
Response Task ◽  
Completion Times

Some previous research using a new augmented reality map display called Mirror-in-the-Sky (MitS) showed that performance was worse and mental workload (MWL) greater with MitS relative to a track-up map for navigation and wayfinding tasks. The purpose of the current study was to determine—for both MitS and track-up map—how much performance improves and MWL decreases with practice in a simple navigation task. We conducted a three-session experiment in which twenty participants completed a route following task in a virtual environment. Task completion times and collisions decreased, subjective MWL decreased, and secondary task performance improved with practice. The NASA-TLX Global ratings and Detection Response Task Hit Rates showed a larger decrease in MWL with MitS than the track-up map. Additionally, means for performance and workload measures showed that differences between the MitS and track-up map decreased in the first session. In later sessions the differences between the MitS and track-up map were negligible. As such, with practice performance and MWL may be comparable to a traditional track-up map.

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