Ramtin Zargari Marandi

The level of mental load during a functional task is reflected in oculometrics

Modern occupations have increasingly become mentally demanding. This underlines the needs for investigation of the interaction of mental and physical workload. This study assessed the effects of mental load on ocular metrics and their consistency across days. Eighteen participants performed a five minute simulated computer work with three different levels of mental load in two days at least seven days apart. Eye movements in response to the task mental load level were recorded. Along with eye movements, task performance, and national aeronautics and space administration task load index (NASA-TLX) scores were acquired. Peak saccade velocity decreased, and pupil dilation range increased with the task load level and the response remained consistent across experimental days. Increased NASA-TLX score and reduced performance were in association with mental load demand. The study shows the feasibility of quantifying the mental load demands by monitoring oculometrics during a functional task such as computer work.

Analysis of folk music preference of people from different ethnic groups using kernel-based methods on EEG signals

Emotional preference of people from different ethnicity would alter multimedia implicit tagging remarkably. It can be speculated that the people from each ethnic group would prefer the folk music of their own ethnicity more than the others. An emotionally intelligent system based on electroencephalography (EEG) is proposed in this study to test this hypothesis. Four channels of EEG signals of 16 healthy subjects from different ethnic groups were recorded during 4 two-minute long excerpts of folk music. Six types of features extracted and a subset of them were selected based on minimum-Redundancy-Maximum-Relevance (mRMR) algorithm. The top-ranked features were fed to the Support Vector Machine (SVM) classifier with Radial Basis Function (RBF) kernel with various similarity metrics. The performance of the proposed method was assessed in terms of F1-score and accuracy (ACC) using random sub-sampling cross validation scheme. The highest performance for the single SVM classifier was achieved by Dynamic Time Warping (DTW) based RBF kernel which was significantly higher than the chance level. These results approve that the tendency of people from each ethnic group to their ethnicity is significantly reflected in their EEG signals which can be automatically detected.

Qualitative modeling of the decision-making process using electrooculography.

A novel method based on electrooculography (EOG) has been introduced in this work to study the decision-making process. An experiment was designed and implemented wherein subjects were asked to choose between two items from the same category that were presented within a limited time. The EOG and voice signals of the subjects were recorded during the experiment. A calibration task was performed to map the EOG signals to their corresponding gaze positions on the screen by using an artificial neural network. To analyze the data, 16 parameters were extracted from the response time and EOG signals of the subjects. Evaluation and comparison of the parameters, together with subjects’ choices, revealed functional information. On the basis of this information, subjects switched their eye gazes between items about three times on average. We also found, according to statistical hypothesis testing—that is, a t test, t(10) = 71.62, SE = 1.25, p < .0001—that the correspondence rate of a subjects’ gaze at the moment of selection with the selected item was significant. Ultimately, on the basis of these results, we propose a qualitative choice model for the decision-making task.

Heart Rate Monitoring for the Detection of Changes in Mental Demands During Computer Work

The detection of variations in mental demands is a key factor for optimizing the balance between occupational health and work performance. With the advances in heart rate acquisition technologies, heart rate monitoring is now easy and affordable. In this study, we recorded the heart rate of 18 healthy young participants while they performed three consecutive 5-min cyclic computer tasks with low, medium and high mental demands in two days with at least one week apart. The cycles began with memorizing a pattern of connected points following by the disappearance of the pattern, and then replicating it using computer mouse clicks on an incomplete version of the pattern. The mental demand of the tasks was manipulated by changing the complexity of the displayed patterns. The participants rated their perceived mental load after each task. The mean, range, and standard deviation of heart rate, MHR, RHR, and SDHR respectively, along with the performance (in terms of accuracy and speed of pattern replication) for each cycle was calculated and averaged for each task. The RHR and SDHR increased with increasing mental demands (p < 0.001), whereas the MHR did not significantly change in response to the different task demands. The responses remained consistent across days for RHR, MHR, but not SDHR. As expected, the performance decreased and the perceived mental load increased as the task demands increased. These results suggest that the variations in heart rate would provide useful information regarding the quantification of mental load.

Eye movement characteristics reflected fatigue development in both young and elderly individuals

Fatigue can develop during prolonged computer work, particularly in elderly individuals. This study investigated eye movement characteristics in relation to fatigue development. Twenty young and 18 elderly healthy adults were recruited to perform a prolonged functional computer task while their eye movements were recorded. The task lasted 40 minutes involving 240 cycles divided into 12 segments. Each cycle consisted of a sequence involving memorization of a pattern, a washout period, and replication of the pattern using a computer mouse. The participants rated their perceived fatigue after each segment. The mean values of blink duration (BD) and frequency (BF), saccade duration (SCD) and peak velocity (SPV), pupil dilation range (PDR), and fixation duration (FD) along with the task performance based on clicking speed and accuracy, were computed for each task segment. An increased subjective evaluation of fatigue suggested the development of fatigue. BD, BF, and PDR increased whereas SPV and SCD decreased over time in the young and elderly groups. Longer FD, shorter SCD, and lower task performance were observed in the elderly compared with the young group. The present findings provide a viable approach to develop a computational model based on oculometrics to track fatigue development during computer work.

Characterization of the Dynamics of Sitting During a Sustained and Mentally Demanding Computer Task

This laboratory study studied the dynamics of sitting during a sustained and mentally demanding computer task. Mental fatigue ratings, overall performance and kinetic were recorded in 20 asymptomatic computer users performing computer work for 40 min divided in 12 time epochs. The displacement of the center of pressure (COP) in anterior-posterior (AP) and medial-lateral (ML) directions was calculated. The average, standard deviation, and sample entropy values were computed from the COP time series to assess respectively, the magnitude, size and complexity of sitting dynamics. Fatigue ratings significantly increased from before to after the computer task while the overall performance did not change significantly over time. Likewise, the direction of displacement of the COP did not affect significantly the AVG but resulted in larger SD and SaEn values in the ML direction compared with AP direction. Time did not play a significant role on any of the outcome measures. The present study demonstrated that the sitting dynamics can be assessed in an ecological environment, e.g. in office chairs. Further, we found that 40 min seated computer work did not changed the dynamics of sitting. On the contrary, we observed increased size and structure of variability in the ML than the AP direction. This latter finding can be used to design office chairs or interventions aiming at preventing discomfort due to long time sitting.

Early Detection of Fatigue Based on Heart Rate in Sedentary Computer Work in Young and Old Adults

Given the growing number of working elderly, monitoring fatigue developing at work is of utmost importance. In this study, 38 participants (18 elderly and 20 young adults) were recruited to perform a prolonged computer task including 240 cycles while their heart rate was measured. In each cycle, the participants memorized a random pattern of connected points then replicated the pattern by clicking on a sequence of points to complete an incomplete version of the pattern. Task performance in each cycle was calculated based on the accuracy and speed in clicking. After each 20 cycles (one segment), participant rated their perceived fatigue on Karolinska Sleepiness Likert scale (KSS). The mean and range of heart rate, HRM and HRR respectively, in each cycle were calculated and together with the performance were averaged across each segment. Statistical analysis revealed that HRR followed an increasing trend in both young and elderly groups as time on task (TOT) increased, p < 0.001. The HRM exhibited a tendency to increase with TOT in both groups, p = 0.063. The performance increased in the elderly group and fluctuated in the young group, p < 0.001. The KSS increased in both groups with TOT, p < 0.001. No interactions between TOT segments and groups were found in any of the measures except in case of performance indicating a higher performance for the young group with a fluctuating temporal pattern. The results provide insights on the feasibility of using heart rate as an index to monitor fatigue in both young and elderly computer users.

The Study of Visual Cueing Effects on Attentional Guidance and Individual's Response Prediction to Proposed Questions with Using Their Eye Movement Analysis

In this study we examine whether it is possible or not to raise learning quality in less time with guiding eyes to target points ?And also whether adding visual cues have effects on prediction correctness of individuals responses to visual-auditory presented questions from analyzing their eye movements. We used electrooculographic signals from nine subjects to analyze individuals eye movements facing with visual- auditory stimuli. The stimuli include one spatial visualization test. The data were collected in an experimental procedure wherein subjects were trained how to solve the incoming problems and answering to the related questions. There were sixteen questions from the same category. A novel algorithm based on signal processing techniques was used to analyze EOG signals. After preprocessing using a band pass filter, 31 features were extracted from horizontal and vertical channel of EOG signals. Then 15 best features were selected using mRMR. Finally the selected features used for classification using SVM classifier. We used leave-one-person-out technique for classification to achieve more accurate results. Results from the experiment show a reduction in classification performance in with visual cues stage with respect to without visual cues stage also a reduction in