Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

258
Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
258
Subliminal Perception01:15

Subliminal Perception

794
Subliminal perception refers to the processing of sensory information that occurs below the level of conscious awareness. Researchers study subliminal perception by presenting a stimulus, such as a word or image, very quickly, typically around 50 milliseconds. This rapid presentation is often followed by another stimulus, such as a pattern of dots or lines, which blocks further mental processing of the initial stimulus. As a result, if participants cannot identify the initial stimulus better...
794
Factors Affecting Perception01:25

Factors Affecting Perception

2.7K
Perception is influenced by perceptual set, context, motivation, and emotion. Perceptual set, or perceptual expectancy, refers to the tendency to perceive things in a particular way, influenced by previous experiences and expectations. This phenomenon affects the interpretation of stimuli, creating a set of mental tendencies and assumptions that impact sensory perceptions of sound, taste, touch, and sight.
An illustrative example of a perceptual set is the scenario where an airline pilot told...
2.7K
Perception01:28

Perception

1.2K
Perception is a fundamental psychological process that enables individuals to organize, interpret, and consciously experience sensory information. This process is crucial for understanding and interacting with the world around us. It includes both bottom-up and top-down processing, each playing a distinct role in how we perceive our environment.
Bottom-up processing begins at the sensory level, where receptors detect external environmental stimuli. These could include the tactile sensation of...
1.2K
Healthcare Agencies II01:17

Healthcare Agencies II

1.1K
There are various healthcare agencies in the United States—some of which are managed by religious institutions and others by different government branches.
Parish nursing is a growing specialty nursing profession that focuses on holistic healthcare, health promotion, and illness prevention. It blends professional nursing practice with a health ministry, focusing on health and healing within the context of a Christian community. Parish nurses serve as health educators, referral sources,...
1.1K
Secondary Healthcare System01:11

Secondary Healthcare System

2.1K
Secondary healthcare is offered by a specialist, generally in hospitals or clinics for patients referred by primary healthcare providers. It occurs when a person has an illness or injury that requires specific medical care. Secondary care is often referred to as acute care. Secondary care can range from uncomplicated care to repair a minor laceration or treat a strep throat infection to more complicated emergent care, such as treating a head injury sustained in an automobile accident. Whatever...
2.1K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

TMacaque-FaceNet: Automatic Facial Recognition Based on Vision Transformer for Wild Tibetan Macaques.

Animals : an open access journal from MDPI·2026
Same author

MCTGNet: A Multi-Scale Convolution and Hybrid Attention Network for Robust Motor Imagery EEG Decoding.

Bioengineering (Basel, Switzerland)·2025
Same author

Temporal Relation Modeling and Multimodal Adversarial Alignment Network for Pilot Workload Evaluation.

IEEE journal of translational engineering in health and medicine·2025
Same author

CBR-Net: A Multisensory Emotional Electroencephalography (EEG)-Based Personal Identification Model with Olfactory-Enhanced Video Stimulation.

Bioengineering (Basel, Switzerland)·2025
Same author

Pd-catalyzed C-H functionalizations of O-methyl oximes with arylboronic acids.

Organic letters·2009
Same author

[Effects of simulated soil warming on the growth and physiological characters of Deyeuxia angustifolia].

Ying yong sheng tai xue bao = The journal of applied ecology·2009

Related Experiment Video

Updated: Feb 6, 2026

Author Spotlight: Exploring the Link Between Time Perception of Visual Stimuli and Reading Skills
09:27

Author Spotlight: Exploring the Link Between Time Perception of Visual Stimuli and Reading Skills

Published on: January 19, 2024

1.8K

Automatic Emotion Perception Using Eye Movement Information for E-Healthcare Systems.

Yang Wang1, Zhao Lv2,3, Yongjun Zheng4

  • 1School of Computer Science and Technology, Anhui University, Hefei 230601, China. e16201094@stu.ahu.edu.cn.

Sensors (Basel, Switzerland)
|August 29, 2018
PubMed
Summary
This summary is machine-generated.

Detecting adolescent emotions via eye movement analysis is key for E-Healthcare rehabilitation. This study uses electrooculography (EOG) signals and video to accurately perceive emotional states, improving E-Healthcare systems.

Keywords:
EOGadolescenceemotion recognitioneye movement videohealthcare

More Related Videos

Eye Movement Monitoring of Memory
08:06

Eye Movement Monitoring of Memory

Published on: August 15, 2010

15.2K
Using Eye Movements to Evaluate the Cognitive Processes Involved in Text Comprehension
06:49

Using Eye Movements to Evaluate the Cognitive Processes Involved in Text Comprehension

Published on: January 10, 2014

28.1K

Related Experiment Videos

Last Updated: Feb 6, 2026

Author Spotlight: Exploring the Link Between Time Perception of Visual Stimuli and Reading Skills
09:27

Author Spotlight: Exploring the Link Between Time Perception of Visual Stimuli and Reading Skills

Published on: January 19, 2024

1.8K
Eye Movement Monitoring of Memory
08:06

Eye Movement Monitoring of Memory

Published on: August 15, 2010

15.2K
Using Eye Movements to Evaluate the Cognitive Processes Involved in Text Comprehension
06:49

Using Eye Movements to Evaluate the Cognitive Processes Involved in Text Comprehension

Published on: January 10, 2014

28.1K

Area of Science:

  • Biomedical Engineering
  • Affective Computing
  • Human-Computer Interaction

Background:

  • Adolescent emotional state detection is crucial for effective E-Healthcare rehabilitation.
  • Current E-Healthcare systems require improved methods for real-time emotional monitoring.
  • Eye movement patterns offer a potential biomarker for emotional states.

Purpose of the Study:

  • To develop and validate an eye movement-based algorithm for adolescent emotion perception.
  • To integrate electrooculography (EOG) signals and eye movement video for enhanced emotion recognition.
  • To compare feature-level fusion (FLF) and decision-level fusion (DLF) strategies for emotion classification.

Main Methods:

  • Synchronous collection and analysis of electrooculography (EOG) signals and eye movement video.
  • Extraction of time-frequency eye movement features using Short-Time Fourier Transform (STFT).
  • Integration of time-domain features (saccade duration, fixation duration, pupil diameter) using FLF and DLF.

Main Results:

  • The proposed algorithm achieved high accuracy in recognizing positive, neutral, and negative emotional states.
  • Feature level fusion (FLF) yielded an average accuracy of 88.64%.
  • Decision level fusion (DLF) with a maximal rule achieved an average accuracy of 88.35%.

Conclusions:

  • Eye movement information effectively reflects adolescent emotional states.
  • The developed algorithm provides a promising tool for enhancing E-Healthcare systems.
  • Synchronous EOG and video analysis offers a robust approach for emotion perception in E-Healthcare.