Mental Fatigue Evaluation using Blink Frequency and Pupil Diameter on Human-Robot Collaboration with Different Motion Timing

2021 ◽  
Author(s):  
Moe Urasaki ◽  
Mihoko Niitsuma
Keyword(s):  
Pupil Diameter ◽  
Mental Fatigue ◽  
Fatigue Evaluation ◽  
Human Robot Collaboration ◽  
Blink Frequency

scholarly journals The Maximum Eigenvalue of the Brain Functional Network Adjacency Matrix: Meaning and Application in Mental Fatigue Evaluation

2020 ◽  
Vol 10 (2) ◽  
pp. 92 ◽  
Author(s):  
Gang Li ◽  
Yonghua Jiang ◽  
Weidong Jiao ◽  
Wanxiu Xu ◽  
Shan Huang ◽  
...  
Keyword(s):  
Adjacency Matrix ◽  
Mental Fatigue ◽  
Functional Network ◽  
Maximum Eigenvalue ◽  
Characteristic Path Length ◽  
Brain Functional Network ◽  
Large Maximum ◽  
Fatigue Estimation ◽  
Fatigue Evaluation ◽  
High Degree

The maximum eigenvalue of the adjacency matrix (AM) has been supposed to contain rich information about the corresponding network. An experimental study focused on revealing the meaning and application of the maximum eigenvalue is missing. To this end, AM was constructed using mutual information (MI) to determine the functional connectivity with electroencephalogram (EEG) data recorded with a mental fatigue model, and then was converted into both binary and weighted brain functional network (BFN) and corresponding random networks (RNs). Both maximum eigenvalue and corresponding network characters in BFNs and RNs were considered to explore the changes during the formation of mental fatigue. The results indicated that large maximum eigenvalue means more edges in the corresponding network, along with a high degree and a short characteristic path length both in weighted and binary BFNs. Interestingly, the maximum eigenvalue of AM was always a little larger than that of the corresponding random matrix (RM), and had an obvious linearity with the sum of the AM elements, indicating that the maximum eigenvalue can be able to distinguish the network structures which have the same mean degree. What is more, the maximum eigenvalue, which increased with the deepening of mental fatigue, can become a good indicator for mental fatigue estimation.

scholarly journals The Role of Motivation as a Factor in Mental Fatigue

2019 ◽  
Vol 61 (7) ◽  
pp. 1171-1185 ◽  
Author(s):  
Mega B. Herlambang ◽  
Niels A. Taatgen ◽  
Fokie Cnossen
Keyword(s):  
Pupil Diameter ◽  
Memory Task ◽  
Mental Effort ◽  
Mental Fatigue ◽  
Cognitive Effort ◽  
Physiological Measures ◽  
Monetary Rewards ◽  
Sustained Performance ◽  
Over Time

Objective: The aim of this study was to assess motivation as a factor in mental fatigue using subjective, performance, and physiological measures. Background: Sustained performance on a mentally demanding task can decrease over time. This decrement has two possible causes: a decline in available resources, meaning that performance cannot be sustained, and decrement in motivation, meaning a decline in willingness to sustain performance. However, so far, few experimental paradigms have effectively and continuously manipulated motivation, which is essential to understand its effect on mental fatigue. Method: Twenty participants performed a working memory task with 14 blocks, which alternated between reward and nonreward for 2.5 hr. In the reward blocks, monetary rewards could be gained for good performance. Besides reaction time and accuracy, we used physiological measures (heart rate variability, pupil diameter, eyeblink, eye movements with a video distractor) and subjective measures of fatigue and mental effort. Results: Participants reported becoming fatigued over time and invested more mental effort in the reward blocks. Even though they reported fatigue, their accuracy in the reward blocks remained constant but declined in the nonreward blocks. Furthermore, in the nonreward blocks, participants became more distractable, invested less cognitive effort, blinked more often, and made fewer saccades. These results showed an effect of motivation on mental fatigue. Conclusion: The evidence suggests that motivation is an important factor in explaining the effects of mental fatigue.

scholarly journals Mental fatigue prediction during eye-typing

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246739
Author(s):  
Tanya Bafna ◽  
Per Bækgaard ◽  
John Paulin Hansen
Keyword(s):  
Neurological Disorders ◽  
Task Difficulty ◽  
Absolute Error ◽  
Mental Fatigue ◽  
Random Forest Regression ◽  
Perceived Effort ◽  
Continuous Scale ◽  
Eye Typing ◽  
Variance Explained ◽  
Blink Frequency

Mental fatigue is a common problem associated with neurological disorders. Until now, there has not been a method to assess mental fatigue on a continuous scale. Camera-based eye-typing is commonly used for communication by people with severe neurological disorders. We designed a working memory-based eye-typing experiment with 18 healthy participants, and obtained eye-tracking and typing performance data in addition to their subjective scores on perceived effort for every sentence typed and mental fatigue, to create a model of mental fatigue for eye-typing. The features of the model were the eye-based blink frequency, eye height and baseline-related pupil diameter. We predicted subjective ratings of mental fatigue on a six-point Likert scale, using random forest regression, with 22% lower mean absolute error than using simulations. When additionally including task difficulty (i.e. the difficulty of the sentences typed) as a feature, the variance explained by the model increased by 9%. This indicates that task difficulty plays an important role in modelling mental fatigue. The results demonstrate the feasibility of objective and non-intrusive measurement of fatigue on a continuous scale.

scholarly journals Mental Fatigue Evaluation of Surgical Teams during a Regular Workday in a High-Volume Tertiary Healthcare Center

2020 ◽  
Vol 104 (3-4) ◽  
pp. 301-308
Author(s):  
Bogdan Petrut ◽  
Ioana Berindan-Neagoe ◽  
Dragos I. Feflea ◽  
Maximilian Hogea ◽  
Sergiu Pasca ◽  
...  
Keyword(s):  
High Volume ◽  
Mental Fatigue ◽  
Healthcare Center ◽  
Tertiary Healthcare ◽  
Surgical Teams ◽  
Fatigue Evaluation

Symptom Validity Testing

2018 ◽  
Vol 23 (6) ◽  
pp. 14-15
Author(s):  
Lee H. Ensalada
Keyword(s):  
Memory Deficits ◽  
Symptom Validity ◽  
Sensory Cues ◽  
Validity Testing ◽  
Symptom Validity Testing ◽  
Tunnel Vision ◽  
Blurry Vision ◽  
The Common ◽  
Fatigue Evaluation ◽  
Choice Testing

Abstract Symptom validity testing (SVT), also known as forced-choice testing, is a means of assessing the validity of sensory and memory deficits, including tactile anesthesias, paresthesias, blindness, color blindness, tunnel vision, blurry vision, and deafness. The common feature among these symptoms is a claimed inability to perceive or remember a sensory signal. SVT comprises two elements: a specific ability is assessed by presenting a large number of items in a multiple-choice format, and then the examinee's performance is compared to the statistical likelihood of success based on chance alone. These tests usually present two alternatives; thus the probability of simply guessing the correct response (equivalent to having no ability at all) is 50%. Thus, scores significantly below chance performance indicate that the sensory cues must have been perceived, but the examinee chose not to report the correct answer—alternative explanations are not apparent. SVT also has the capacity to demonstrate that the examinee performed below the probabilities of chance. Scoring below a norm can be explained by fatigue, evaluation anxiety, inattention, or limited intelligence. Scoring below the probabilities of chance alone most likely indicates deliberate deceptions and is evidence of malingering because it provides strong evidence that the examinee received the sensory cues and denied the perception. Even so, malingering must be evaluated from the total clinical context.

Impairment Questions and Answers

1999 ◽  
Vol 4 (4) ◽  
pp. 4-4
Keyword(s):  
Symptom Validity ◽  
Validity Testing ◽  
Symptom Validity Testing ◽  
Negative Results ◽  
Tunnel Vision ◽  
Questions And Answers ◽  
Blurry Vision ◽  
Fatigue Evaluation ◽  
Choice Testing ◽  
Rule Out

Abstract Symptom validity testing, also known as forced-choice testing, is a way to assess the validity of sensory and memory deficits, including tactile anesthesias, paresthesias, blindness, color blindness, tunnel vision, blurry vision, and deafness—the common feature of which is a claimed inability to perceive or remember a sensory signal. Symptom validity testing comprises two elements: A specific ability is assessed by presenting a large number of items in a multiple-choice format, and then the examinee's performance is compared with the statistical likelihood of success based on chance alone. Scoring below a norm can be explained in many different ways (eg, fatigue, evaluation anxiety, limited intelligence, and so on), but scoring below the probabilities of chance alone most likely indicates deliberate deception. The positive predictive value of the symptom validity technique likely is quite high because there is no alternative explanation to deliberate distortion when performance is below the probability of chance. The sensitivity of this technique is not likely to be good because, as with a thermometer, positive findings indicate that a problem is present, but negative results do not rule out a problem. Although a compelling conclusion is that the examinee who scores below probabilities is deliberately motivated to perform poorly, malingering must be concluded from the total clinical context.

How Socially Relevant Visual Characteristics of Avatars Influence Impression Formation

2010 ◽  
Vol 22 (1) ◽  
pp. 37-43 ◽  
Author(s):  
David Weibel ◽  
Daniel Stricker ◽  
Bartholomäus Wissmath ◽  
Fred W. Mast
Keyword(s):  
Impression Formation ◽  
Pupil Size ◽  
Conscious Perception ◽  
Viewing Angle ◽  
Frontal View ◽  
Computer Mediated ◽  
First Impression ◽  
Visual Characteristics ◽  
Socially Relevant ◽  
Blink Frequency

Like in the real world, the first impression a person leaves in a computer-mediated environment depends on his or her online appearance. The present study manipulates an avatar’s pupil size, eyeblink frequency, and the viewing angle to investigate whether nonverbal visual characteristics are responsible for the impression made. We assessed how participants (N = 56) evaluate these avatars in terms of different attributes. The findings show that avatars with large pupils and slow eye blink frequency are perceived as more sociable and more attractive. Compared to avatars seen in full frontal view or from above, avatars seen from below were rated as most sociable, self-confident, and attractive. Moreover, avatars’ pupil size and eyeblink frequency escape the viewer’s conscious perception but still influence how people evaluate them. The findings have wide-ranging applied implications for avatar design.

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