THE IMPLEMENTATION EFFECTS OF LEARNER'S EMOTION RECOGNITION AND VISUALIZATION BASED ON BRAIN WAVES AND AUGMENTED REALITY

2021 ◽  
Author(s):  
Rui Jiang ◽  
Buwen Xing ◽  
Su Cai
Keyword(s):  
Augmented Reality ◽  
Emotion Recognition ◽  
Brain Waves

EEG-Based Emotion Recognition and Its Interface with Augmented Reality

2021 ◽  
pp. 41-56
Author(s):  
Gali Amoolya ◽  
Ashna KK ◽  
Gadde Sai Venkata Swetha ◽  
Ganga Das ◽  
Jalada Geeta ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Emotion Recognition

scholarly journals Analysis of cognitive states in response to stimuli from augmented reality applications for teaching physics

2021 ◽  
Vol 2102 (1) ◽  
pp. 012004
Author(s):  
M Rojas-Contreras ◽  
C A Peña-Cortés ◽  
L A Moreno-Cuevas
Keyword(s):  
Augmented Reality ◽  
Teaching Method ◽  
Traditional Teaching ◽  
Physics Teaching ◽  
Brain Waves ◽  
Cognitive States ◽  
Augmented Reality Application ◽  
Measurement Concept ◽  
Teaching Physics ◽  
The Brain

Abstract The scope of this article is to analyze the behavior of children’s brain waves in response to interaction with an augmented reality application that aims to support the concept of measurement in physics teaching. In particular, the analysis of brain waves is carried out through a brain-computer interface that measures 6 cognitive states such as engagement, interest, stress, focus, excitation, and relaxation. The method used to perform the analysis is carried out by means of electroencephalography, which is an electrophysiological process to record the electrical activity of the brain, and which is captured by means of sensors located on the scalp. Once the signals are captured, they are amplified, digitized, and stored in a computer for processing and analysis. Initially, electrical signals are recorded in response to a measurement stimulus with traditional methods and later with an augmented reality application stimulus. Among the most relevant findings, it was possible to establish that interest and commitment increase in response to the teaching method supported with an augmented reality application for the measurement concept with respect to the traditional teaching method. The use of vision technologies in teaching the concept of measurement improves cognitive states of interest, commitment and reduces the level of stress.

scholarly journals Augmented reality emotion recognition for autism spectrum disorder children

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 1217
Author(s):  
Han Foon Neo ◽  
Chuan Chin Teo ◽  
Quan Fong Yeo
Keyword(s):  
Autism Spectrum Disorder ◽  
Social Skills ◽  
Augmented Reality ◽  
Social Interactions ◽  
Emotion Recognition ◽  
Neurodevelopmental Disorder ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Three Dimensions ◽  
Children With Asd

Autism spectrum disorder (ASD) is a lifelong neurodevelopmental disorder that affects brain development. The prevalence of ASD is one in 68 children. Low social motivation is the main cause in developing social communication skills deficiency. As a result, it is becoming difficult for them to express themselves, to be able to manage social interactions, and they lack the ability to comfort others and even share their own feelings. This study aimed to design a mobile application based on augmented reality (AR) focusing on social interactions and communication aspect for children with ASD. The scope is in emotion recognition, which makes use of emotional icons to help them improve their social skills, more specifically on helping them to recognize various emotions. The emotions are represented by emojis inspired by Dr. Paul Ekman who has created the basic six emotions, namely happiness, sadness, disgust, fear, surprise, and angry. Additional emotions such as confound face, winking with tongue, cold sweat, blowing kiss, flushed, sleepy, disappointed, and winking are included. AR is able to gage the children’s attention when they view the animated emojis. The application enables the children with ASD to be more willing in recognizing different emotional expressions and improve their social skills by expressing their own feelings. The scope of the study is limited to emotion recognition. It is developed based on literature reviews without guidance of any certified ASD specialist. AR is an interactive technology that places digital information in our physical world in real time, providing precise registration in all three dimensions. Existing literature proved that the traditional face-to-face teaching methods have failed to increase the interest and ability of ASD children because the teacher has full control in the classroom. This study adds value to the existing works to incorporate AR as additional intervention in treating ASD children.

Amp Up Your Treatment With Augmented Reality

ASHA Leader ◽  
2013 ◽  
Vol 18 (9) ◽  
pp. 14-14 ◽  
Keyword(s):  
Augmented Reality

Amp Up Your Treatment With Augmented Reality

Planning, simulation, and augmented reality for robotic cardiac procedures: The STARS system of the ChIR team

2003 ◽  
Vol 15 (2) ◽  
pp. 141-156 ◽  
Author(s):  
eve Coste-Maniere ◽  
Louai Adhami ◽  
Fabien Mourgues ◽  
Alain Carpentier
Keyword(s):  
Augmented Reality ◽  
Cardiac Procedures

Beeinträchtigtes Erkennen emotionaler Gesichtsausdrücke durch psychiatrische Patientinnen bei Alexithymie

2013 ◽  
Vol 61 (1) ◽  
pp. 7-15 ◽  
Author(s):  
Daniel Dittrich ◽  
Gregor Domes ◽  
Susi Loebel ◽  
Christoph Berger ◽  
Carsten Spitzer ◽  
...  
Keyword(s):  
Emotion Recognition ◽  
Emotional Expression ◽  
Depression Scale ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Check List ◽  
Psychosomatische Erkrankungen ◽  
Psychiatrische Patienten ◽  
Symptom Check List ◽  
Tas 20

Die vorliegende Studie untersucht die Hypothese eines mit Alexithymie assoziierten Defizits beim Erkennen emotionaler Gesichtsaudrücke an einer klinischen Population. Darüber hinaus werden Hypothesen zur Bedeutung spezifischer Emotionsqualitäten sowie zu Gender-Unterschieden getestet. 68 ambulante und stationäre psychiatrische Patienten (44 Frauen und 24 Männer) wurden mit der Toronto-Alexithymie-Skala (TAS-20), der Montgomery-Åsberg Depression Scale (MADRS), der Symptom-Check-List (SCL-90-R) und der Emotional Expression Multimorph Task (EEMT) untersucht. Als Stimuli des Gesichtererkennungsparadigmas dienten Gesichtsausdrücke von Basisemotionen nach Ekman und Friesen, die zu Sequenzen mit sich graduell steigernder Ausdrucksstärke angeordnet waren. Mittels multipler Regressionsanalyse untersuchten wir die Assoziation von TAS-20 Punktzahl und facial emotion recognition (FER). Während sich für die Gesamtstichprobe und den männlichen Stichprobenteil kein signifikanter Zusammenhang zwischen TAS-20-Punktzahl und FER zeigte, sahen wir im weiblichen Stichprobenteil durch die TAS-20 Punktzahl eine signifikante Prädiktion der Gesamtfehlerzahl (β = .38, t = 2.055, p < 0.05) und den Fehlern im Erkennen der Emotionen Wut und Ekel (Wut: β = .40, t = 2.240, p < 0.05, Ekel: β = .41, t = 2.214, p < 0.05). Für wütende Gesichter betrug die Varianzaufklärung durch die TAS-20-Punktzahl 13.3 %, für angeekelte Gesichter 19.7 %. Kein Zusammenhang bestand zwischen der Zeit, nach der die Probanden die emotionalen Sequenzen stoppten, um ihre Bewertung abzugeben (Antwortlatenz) und Alexithymie. Die Ergebnisse der Arbeit unterstützen das Vorliegen eines mit Alexithymie assoziierten Defizits im Erkennen emotionaler Gesichtsausdrücke bei weiblchen Probanden in einer heterogenen, klinischen Stichprobe. Dieses Defizit könnte die Schwierigkeiten Hochalexithymer im Bereich sozialer Interaktionen zumindest teilweise begründen und so eine Prädisposition für psychische sowie psychosomatische Erkrankungen erklären.

Brain Waves Can Shed Some Light

1981 ◽  
Vol 26 (6) ◽  
pp. 469-470
Author(s):  
Rafael Klorma
Keyword(s):  
Brain Waves
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