• Nuclear Engineering and Technology
• /
• v.52 no.5
• /
• pp.984-994
• /
• 2020

It is reported that about 20% of accidents at nuclear power plants in Korea and abroad are caused by human error. One of the main factors contributing to human error is fatigue, so it is necessary to prevent human errors that may occur when the task is performed in an improper state by grasping the status of the operator in advance. In this study, we propose a method of evaluating operator's fitness-for-duty (FFD) using various parameters including eye movement data, subjective fatigue ratings, and operator's performance. Parameters for evaluating FFD were selected through a literature survey. We performed experiments that test subjects who felt various levels of fatigue monitor information of indicators and diagnose a system malfunction. In order to find meaningful characteristics in measured data consisting of various parameters, hierarchical clustering analysis, an unsupervised machine-learning technique, is used. The characteristics of each cluster were analyzed; fitness-for-duty of each cluster was evaluated. The appropriateness of the number of clusters obtained through clustering analysis was evaluated using both the Elbow and Silhouette methods. Finally, it was statistically shown that the suggested methodology for evaluating FFD does not generate additional fatigue in subjects. Relevance to industry: The methodology for evaluating an operator's fitness for duty in advance is proposed, and it can prevent human errors that might be caused by inappropriate condition in nuclear industries.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.9C
• /
• pp.887-898
• /
• 2005

In this paper, we introduce a probabilistic model based on Bayesian networks BNs) for recognizing human fatigue. First of all, we measured face feature information such as eyelid movement, gaze, head movement, and facial expression by IR illumination. But, an individual face feature information does not provide enough information to determine human fatigue. Therefore in this paper, a Bayesian network model was constructed to fuse as many as possible fatigue cause parameters and face feature information for probabilistic inferring human fatigue. The MSBNX simulation result ending a 0.95 BN fatigue index threshold. As a result of the experiment, when comparisons are inferred BN fatigue index and the TOVA response time, there is a mutual correlation and from this information we can conclude that this method is very effective at recognizing a human fatigue.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• v.9 no.1
• /
• pp.1145-1148
• /
• 2005

In this paper, we introduce a probabilistic model based on Bayesian networks (BNs) for inferring human fatigue by integrating information from various visual cues and certain relevant contextual information. Visual parameters, typically characterizing the cognitive states of a person including parameters related to eyelid movement, gaze, head movement, and facial expression, serve as the sensory observations. But, an individual visual cue or contextual Information does not provide enough information to determine human fatigue. Therefore in this paper, a Bayesian network model was developed to fuse as many as possible contextual and visual cue information for monitoring human fatigue. At the experiment results, display the utility of the proposed BNs for predicting and modeling fatigue.

• Phonetics and Speech Sciences
• /
• v.5 no.1
• /
• pp.3-10
• /
• 2013

This study proposes a method to measure mental fatigue using speech technology, which has not been used in previous research and is easier than existing complex and difficult methods. It aims at establishing a relationship between the human voice and mental fatigue based on experiments to measure the influence of mental fatigue on the human voice. Two monotonous tasks of simple calculation such as finding the sum of three one digit numbers were used to measure the feeling of monotony and two sets of subjective questionnaires were used to measure mental fatigue. While thirty subjects perform the experiment, responses to the questionnaire and speech data were collected. Speech features related to speech source and the vocal tract filter were extracted from the speech data. According to the results, speech parameters deeply related to mental fatigue are a mean and standard deviation of fundamental frequency, jitter, and shimmer. This study shows that speech technology is a useful method for measuring mental fatigue.

• Phonetics and Speech Sciences
• /
• v.6 no.2
• /
• pp.3-8
• /
• 2014

This paper deals with how mental fatigue has an effect on human voice. For this a monotonous task to increase the feeling of the fatigue and a set of subjective questionnaire for rating the fatigue were designed. From the experiments the designed task was proven to be monotonous based on the results of the questionnaire responses. To investigate a statistical relationship between speech features extracted from the collected speech data and fatigue, the T test for two-related-samples was used. Statistical analysis shows that speech parameters deeply related to the fatigue are the first formant bandwidth, Jitter, H1-H2, cepstral peak prominence, and harmonics-to-noise ratio. According to the experimental results, it can be seen that voice is changed to be breathy as mental fatigue proceeds.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.15 no.3
• /
• pp.15-28
• /
• 2019

Artificial intelligence is evolving rapidly in the ICT field, smart convergence media system and content industry through the fourth industrial revolution, and it is evolving very rapidly through Big Data. In this paper, we propose a face recognition method based on object recognition based on object recognition through artificial intelligence. In this method, Were experimented and studied through the object recognition technique of artificial intelligence. In the conventional 3D image field, general research on object recognition has been carried out variously, and researches have been conducted on the side effects of visual fatigue and dizziness through 3D image. However, in this study, we tried to solve the problem caused by the quantitative difference between object recognition and object recognition for human factor algorithm that measure visual fatigue through cognitive function, morphological analysis and object recognition. Especially, The new method of computer interaction is presented and the results are shown through experiments.

• Safety and Health at Work
• /
• v.6 no.3
• /
• pp.206-210
• /
• 2015

Background: Fatigue has a strong impact on workers' performance and safety, but expedient methods for assessing fatigue on the job are not yet available. Studies discuss posturography as an indicator of fatigue, but further evidence for its use in the workplace is needed. The purpose of the study is to examine whether posturography is a suitable indicator of fatigue in clerical workers. Methods: Thirty-six employees (${\emptyset}$ 34.8 years, standard deviation = 12.5) participated in postural tasks (eyes open, eyes closed, arm swinging, and dual task) in the morning and afternoon. Position of their center of pressure (COP) was registered using a Nintendo Wii Balance Board and commercial software. From registered COP time series, we calculated the following parameters: path length (mm), velocity (mm/s), anterior-posterior variance (mm), mediolateral variance (mm), and confidence area ($mm^2$). These parameters were reduced to two orthogonal factors in a factor analysis with varimax rotation. Results: Statistical analysis of the first factor (path length and velocity) showed a significant effect of time of day: COP moved along a shorter path at a lower velocity in the afternoon compared with that in the morning. There also was a significant effect of task, but no significant interaction. Conclusion: Data suggest that postural stability of clerical workers was comparable in the morning and afternoon, but COP movement was greater in the morning. Within the framework of dynamic systems theory, this could indicate that the postural system explored the state space in more detail, and thus was more ready to respond to unexpected perturbations in the morning.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.3
• /
• pp.1188-1203
• /
• 2020

The human expression contains a lot of information that can be used to detect complex conditions such as pain and fatigue. After deep learning became the mainstream method, the traditional feature extraction method no longer has advantages. However, in order to achieve higher accuracy, researchers continue to stack the number of layers of the neural network, which makes the real-time performance of the model weak. Therefore, this paper proposed an expression recognition framework based on densely concatenated convolutional neural networks to balance accuracy and latency and apply it to humanoid robots. The techniques of feature reuse and parameter compression in the framework improved the learning ability of the model and greatly reduced the parameters. Experiments showed that the proposed model can reduce tens of times the parameters at the expense of little accuracy.

• Korean Journal of Human Ecology
• /
• v.19 no.2
• /
• pp.417-428
• /
• 2010

The purpose of this study was to analyze differences of the indoor environment and student's fatigue response according to ventilation in university lecture hall. The experiments consisted of measuring the indoor environmental parameters and a survey of student's responses. The experiments were in the lecture hall that the actual lecture was conducted in on the $25^{th}$ of May 2009 (not opening windows and door- A) and the $1^{st}$ of June 2009 (opening windows and door- B). The experimental variable was ventilation by opening the windows and door, and the controlled conditions were indoor temperature by air conditioner, volume of the microphone and VTR, lighting conditions and teaching method. The results are as follows: 1) The indoor temperature was maintained in controlling A, B but the $CO_2$ and relative humidity of A (average 3579ppm, 62.6%) was higher than B (average 1697ppm, 48.1%). 2) There were differences in the student's subjective responses and student's fatigue responses between A and B. 3) Therefore, it was found that ventilation by opening the windows and door was a valid way to improve the relative humidity and to reduce $CO_2$ in the lecture hall.

• Korean Journal of Agricultural Science
• /
• v.49 no.2
• /
• pp.269-284
• /
• 2022

The development of radish collectors has the potential to increase radish yields while decreasing the time and dependence on human labor in a variety of field activities. Stress and fatigue analyses are essential to ensure the optimal design and machine life of any agricultural machinery. The objectives of this research were to analyze the stress and fatigue of major components of a tractor-mounted radish collector under dynamic load conditions in an effort to increase the design dependability and dimensions of the materials. An experiment was conducted to measure the shaft torque of stem-cutting and transferring conveyor motors using rotary torque sensors at different tractor ground speeds with and without a load. The Smith-Watson-Topper mean stress equation and the rain-flow counting technique were utilized to determine the required shear stress with the distribution of the fatigue life cycle. The severity of the operation was assessed using Miner's theory. All running conditions produced more than 10⁷ of high cycle fatigue strength. Furthermore, the highest severity levels for motor shafts used for stem cutting and transferring and for transportation joints and cutting blades were 2.20, 4.24, 2.07, and 1.07, and 1.97, 3.81, 1.73, and 1.07, respectively, with and without a load condition, except for 5.24 for a winch motor shaft under a load. The stress and fatigue analysis presented in this study can aid in the selection of the most appropriate design parameters and material sizes for the successful construction of a tractor-mounted radish collector, which is currently under development.