Results 1 to 10 of about 642,698 (257)
The Validity of Physiological Measures to Identify Differences in Intrinsic Cognitive Load [PDF]
A sample of 33 experiments was extracted from the Web-of-Science database over a 5-year period (2016–2020) that used physiological measures to measure intrinsic cognitive load.
Paul Ayres +4 more
doaj +4 more sources
Let Complexity Bring Clarity: A Multidimensional Assessment of Cognitive Load Using Physiological Measures [PDF]
The effects of cognitive load on driver behavior and traffic safety are unclear and in need of further investigation. Reliable measures of cognitive load for use in research and, subsequently, in the development and implementation of driver monitoring ...
Emma J. Nilsson +5 more
doaj +4 more sources
Sensitivity of Physiological Measures of Acute Driver Stress: A Meta-Analytic Review [PDF]
Background: The link between driving performance impairment and driver stress is well-established. Identifying and understanding driver stress is therefore of major interest in terms of safety.
Laora Kerautret +4 more
doaj +2 more sources
Audience immersion: validating attentional and physiological measures against self-report [PDF]
When an audience member becomes immersed, their attention shifts towards the media and story, and they allocate cognitive resources to represent events and characters.
Hugo Hammond +3 more
doaj +2 more sources
The current study aimed to evaluate the impact of increasing cooling sessions from three to five times a day on milk yield and the welfare of dairy buffaloes during a semiarid summer in Pakistan.
Syed Israr Hussain +4 more
doaj +1 more source
A Systematic Review of International Affective Picture System (IAPS) around the World
Standardized Emotion Elicitation Databases (SEEDs) allow studying emotions in laboratory settings by replicating real-life emotions in a controlled environment.
Diogo Branco +2 more
doaj +1 more source
It is a popular belief that colours impact one's psychological and affective functioning. However, clear-cut scientific evidence is still lacking, largely due to methodological challenges.
Marieke Lieve Weijs +4 more
doaj +1 more source
Detection of Driver Cognitive Distraction Using Machine Learning Methods
Driver distraction is one of the primary causes of crashes. As a result, there is a great need to continuously observe driver state and provide appropriate interventions to distracted drivers. Cognitive distraction refers to the “look but not see
Apurva Misra +3 more
doaj +1 more source
Pattern Recognition of Cognitive Load Using EEG and ECG Signals
The matching of cognitive load and working memory is the key for effective learning, and cognitive effort in the learning process has nervous responses which can be quantified in various physiological parameters.
Ronglong Xiong +4 more
doaj +1 more source
Machine Learning for Anxiety Detection Using Biosignals: A Review
Anxiety disorder (AD) is a major mental health illness. However, due to the many symptoms and confounding factors associated with AD, it is difficult to diagnose, and patients remain untreated for a long time.
Lou Ancillon +2 more
doaj +1 more source

