Affect Measurement: A Roadmap Through Approaches, Technologies, and Data Analysis

Gonzalez-Sanchez, Javier; Baydoğan, Mustafa Gökçe; Chavez-Echeagaray, Maria Elena; Atkinson, Robert K.; Burleson, Winslow

doi:10.1016/b978-0-12-801851-4.00011-2

Cited by 22 publications

(16 citation statements)

References 18 publications

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“…With the replacement of online process, however, “the quality of interaction will be compromised; the spontaneity possible in the lecture hall is likely to be lost” [15] . It is significant to know students’ perspectives, as their input may unveil a number of emotional and readiness issues in facing this new situation [40] , [45] , [48] – [51] . Contacting students can possibly assist in detecting their online issues.…”

Section: Literature Reviewmentioning

confidence: 99%

Understanding Education Difficulty During COVID-19 Lockdown: Reports on Malaysian University Students’ Experience

et al. 2020

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The COVID-19 pandemic has struck the world and forced countries to go into lockdown including education sector. Students have been staying in hostels or houses, unable to go to university campuses. This situation has left university administrators no choice, but to have an online learning channel. Malaysian universities in particular have gone through many challenges to bring their online learning system up and ready to resume education process. However, students have found themselves caught in this situation (pure online learning) with no plan or readiness. Literature reviews showed that students encountered some challenges that could not be easily resolved. This study explored the challenges encountered by students of a government-linked university. This university is one of the largest in Malaysia with over 10 campuses across the country. This study collected 284 valid answers. The findings show that respondents lacked full readiness in this situation physically, environmentally, and psychologically with some differences in perspectives according to their gender, age, and residing state. Respondents were concerned about the implications of lockdown on their performance. The findings of this study indicate that a sudden switch to a pure online alternative creates considerable challenges to students who have no plans to be physically apart from classes. The findings also indicate that the current blended learning process which uses online learning as a support mechanism for face-to-face learning has faced a considerable challenge to replace it, particularly with unprepared students. INDEX TERMS COVID-19 epidemic, country lockdown, online learning, Malaysia This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.

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Section: Literature Reviewmentioning

confidence: 99%

Understanding Education Difficulty During COVID-19 Lockdown: Reports on Malaysian University Students’ Experience

et al. 2020

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“…Eye gaze and eye fixation at the computer screen displaying infant stimuli were tracked with a Tobii Pro 60 Hz eye tracker (Tobii Pro, Sweden) mounted on the test computer. The eye tracker directs near-infrared light towards the participant’s pupils and records eye movements from reflections of the cornea ( Gonzalez-Sanchez et al. , 2017 ; iMotions, 2017a ).…”

Section: Methodsmentioning

confidence: 99%

Neurocognitive processing of infant stimuli in mothers and non-mothers: psychophysiological, cognitive and neuroimaging evidence

Bjertrup

Friis

Væver

et al. 2021

Social Cognitive and Affective Neuroscience

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Emerging evidence indicates that mothers and non-mothers show different neurocognitive responses to infant stimuli. This study investigated mothers’ psychophysiological, cognitive and neuronal responses to emotional infant stimuli. A total of 35 mothers with 4-month-old infants and 18 control women without young children underwent computerized tests assessing neurocognitive processing of infant stimuli. Their eye gazes and eye fixations, galvanic skin responses (GSRs) and facial expressions towards infant emotional stimuli were recorded during the tasks. Participants underwent functional magnetic resonance imaging during which they viewed pictures of an unknown infant and, for mothers, their own infants. Mothers gazed more and had increased GSR towards infant stimuli and displayed more positive facial expressions to infant laughter, and self-reported more positive ratings of infant vocalizations than control women. At a neural level, mothers showed greater neural response in insula, dorsolateral prefrontal cortex and occipital brain regions within a predefined ‘maternal neural network’ while watching images of their own vs unknown infants. This specific neural response to own infants correlated with less negative ratings of own vs unknown infants’ signals of distress. Differences between mothers and control women without young children could be interpreted as neurocognitive adaptation to motherhood in the mothers.

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“…e journal that recorded the most publications is Multimedia Tools and Applications with a whooping sixty-three publications. is was followed by Neurocomputing (18) and Visual Computer (16). It was observed that the majority of our primary studies were obtained from ScienceDirect and SpringerDirect.…”

Section: Publication Sourcementioning

confidence: 99%

“…Emotions can be easily and accurately detected from the face [16,17]. Furthermore, the use of the facial expressions for emotion recognition has several advantages, such as its noninvasiveness and relative cheapness, as it does not involve any physical contact with the user employing sensors in comparison to the case of collecting EEG signals or has any requirement for expensive hardware [18]. Facial expressions are useful in deciphering an individual's thoughts or state of mind during a conversation [19].…”

Section: Introductionmentioning

confidence: 99%

On Facial Expression Recognition Benchmarks

Owusu

Kumi

Appati

2021

Applied Computational Intelligence and Soft Computing

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Facial expression is an important form of nonverbal communication, as it is noted that 55% of what humans communicate is expressed in facial expressions. There are several applications of facial expressions in diverse fields including medicine, security, gaming, and even business enterprises. Thus, currently, automatic facial expression recognition is a hotbed research area that attracts lots of grants and therefore the need to understand the trends very well. This study, as a result, aims to review selected published works in the domain of study and conduct valuable analysis to determine the most common and useful algorithms employed in the study. We selected published works from 2010 to 2021 and extracted, analyzed, and summarized the findings based on the most used techniques in feature extraction, feature selection, validation, databases, and classification. The result of the study indicates strongly that local binary pattern (LBP), principal component analysis (PCA), saturated vector machine (SVM), CK+, and 10-fold cross-validation are the most widely used feature extraction, feature selection, classifier, database, and validation method used, respectively. Therefore, in line with our findings, this study provides recommendations for research specifically for new researchers with little or no background as to which methods they can employ and strive to improve.

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Affect Measurement: A Roadmap Through Approaches, Technologies, and Data Analysis

Cited by 22 publications

References 18 publications

Understanding Education Difficulty During COVID-19 Lockdown: Reports on Malaysian University Students’ Experience

Understanding Education Difficulty During COVID-19 Lockdown: Reports on Malaysian University Students’ Experience

Neurocognitive processing of infant stimuli in mothers and non-mothers: psychophysiological, cognitive and neuroimaging evidence

On Facial Expression Recognition Benchmarks

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