Exploring the Linkage between Facial Expression and Mental Workload for Arithmetic Tasks

Stone, Richard; Wei, Chen-Shuang

doi:10.1037/e578902012-129

Cited by 7 publications

(3 citation statements)

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“…All results were positive integers. We decided to implement mental arithmetic because these tasks are suitable for inducing cognitive processing 58 , and the task allows usto vary difficulty levels of the task 59 , 60 . Additionally, this stimulus is suited to simulate office work 43 , 61 .…”

Section: Methodsmentioning

confidence: 99%

The tiny effects of respiratory masks on physiological, subjective, and behavioral measures under mental load in a randomized controlled trial

Spang

Pieper

2021

Sci Rep

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Since the outbreak of the coronavirus disease (COVID-19), face coverings are recommended to diminish person-to-person transmission of the SARS-CoV-2 virus. Some public debates concern claims regarding risks caused by wearing face masks, like, e.g., decreased blood oxygen levels and impaired cognitive capabilities. The present, pre-registered study aims to contribute clarity by delivering a direct comparison of wearing an N95 respirator and wearing no face covering. We focused on a demanding situation to show that cognitive efficacy and individual states are equivalent in both conditions. We conducted a randomized-controlled crossover trial with 44 participants. Participants performed the task while wearing an N95 FFR versus wearing none. We measured physiological (blood oxygen saturation and heart rate variability), behavioral (parameters of performance in the task), and subjective (perceived mental load) data to substantiate our assumption as broadly as possible. We analyzed data regarding both statistical equivalence and differences. All of the investigated dimensions showed statistical equivalence given our pre-registered equivalence boundaries. None of the dimensions showed a significant difference between wearing an FFR and not wearing an FFR.Trial Registration: Preregistered with the Open Science Framework: https://osf.io/c2xp5 (15/11/2020). Retrospectively registered with German Clinical Trials Register: DRKS00024806 (18/03/2021).

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Section: Methodsmentioning

confidence: 99%

The tiny effects of respiratory masks on physiological, subjective, and behavioral measures under mental load in a randomized controlled trial

Spang

Pieper

2021

Sci Rep

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“…MWL involves human factors that determine what resources may be required to perform a specific task [ 211 ]. Moreover, prior studies have accepted the role of human mental activities (i.e., human behavior) in human cognitive abilities such as working memory [ 231 , 232 , 233 ]. In this respect, Garofalo et al [ 234 ] have indicated that individual differences are highly associated with the human behavior required by the task.…”

Section: Discussionmentioning

confidence: 99%

Neural Decoding of EEG Signals with Machine Learning: A Systematic Review

et al. 2021

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Electroencephalography (EEG) is a non-invasive technique used to record the brain’s evoked and induced electrical activity from the scalp. Artificial intelligence, particularly machine learning (ML) and deep learning (DL) algorithms, are increasingly being applied to EEG data for pattern analysis, group membership classification, and brain-computer interface purposes. This study aimed to systematically review recent advances in ML and DL supervised models for decoding and classifying EEG signals. Moreover, this article provides a comprehensive review of the state-of-the-art techniques used for EEG signal preprocessing and feature extraction. To this end, several academic databases were searched to explore relevant studies from the year 2000 to the present. Our results showed that the application of ML and DL in both mental workload and motor imagery tasks has received substantial attention in recent years. A total of 75% of DL studies applied convolutional neural networks with various learning algorithms, and 36% of ML studies achieved competitive accuracy by using a support vector machine algorithm. Wavelet transform was found to be the most common feature extraction method used for all types of tasks. We further examined the specific feature extraction methods and end classifier recommendations discovered in this systematic review.

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“…face behavior) occur to accompany and support task-performing body behavior. Recently, a study by Stone and Wei (2011) indicated that facial expression can be a effective index of workload for arithmetic tasks. Hence, the same behavior in terms of rates for tasks and types can occur as in human-human communication, where facial expression is the most innate (Argyle 1998, cited from King 1997).…”

Section: Introductionmentioning

confidence: 99%

Human Aspects of IT for the Aged Population. Design for Aging

2016

Lecture Notes in Computer Science

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Exploring the Linkage between Facial Expression and Mental Workload for Arithmetic Tasks

Cited by 7 publications

References 0 publications

The tiny effects of respiratory masks on physiological, subjective, and behavioral measures under mental load in a randomized controlled trial

The tiny effects of respiratory masks on physiological, subjective, and behavioral measures under mental load in a randomized controlled trial

Neural Decoding of EEG Signals with Machine Learning: A Systematic Review

Human Aspects of IT for the Aged Population. Design for Aging

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