This study was designed to evaluate localized muscular fatigue induced during mouse operation in a VDT task. Ten male undergraduates from 19 to 23 years old participated in the experiment. The subject performed a pointing task with a PC mouse for about 4 hours. The EMG measurements and psychological rating of fatigue were conducted before the experimental task and after each 30-minutes block during the experimental task. The changes in the Mean Power Frequency (MPF) and Percentage Maximum Voluntary Contraction (%MVC)-shift for the constant cumulative probability in the Amplitude Probability Distribution Function (APDF) with time were explored. The correspondence between the index (MPF or APDF) and the subjective rating of localized muscular fatigue was also examined. The performance was nearly constant across all blocks. The psychological rating of fatigue tended to increase with time. The MPF tended to increase with time, although the main effect of block (time) was not statistically significant. The %MVC-shift tended to increase with time. The correspondence with the perceived sensation of localized muscular fatigue was higher when using the %MVC-shift than when using the MPF. Based on the results, the effectiveness of the indexes used for evaluating localized muscular fatigue was discussed. The %MVC-shift obtained from the APDF was found to be a sensitive index of localized muscular fatigue and corresponded well with the subjective rating of localized muscular fatigue.

In this paper, the effects of the grouping and the addressing methods on the accuracy and the response time in a visual search task were investigated. Four grouping conditions (4, 8, 16 and 32 groups) and four addressing methods (random, ordered, cartesian and polar) were selected in the experiment. For each combination of grouping and addressing methods, subjects repeated the search task 30 times. No remarkable differences of the percent correct were observed both among the levels of grouping and among the addressing methods. The mean response time increased with the increase of the number of groups. Moreover, the interaction between addressing methods and grouping for both percent correct and response time was clarified.

The aim of this study is to evaluate mental workload (MWL) quantitatively by HRV (Heart Rate Variability) measures. The electrocardiography and the respiration curve were recorded in five different epochs (1) during a rest condition and (2) during mental arithmetic tasks (addition). In the experiment, subjects added two numbers. The work levels (figures of the number in the addition) were set to one figure, two figures, three figures and four figures. The work level had effects on the mean percent correct, the number of answers and the mean processing time. The psychological evaluation on mental workload obtained by the method of paired comparison increased with the work level. Among the statistical HRV measures, the number of peak and trough waves could distinguish between the rest and the mental loading. However, mental workload for each work level was not evaluated quantitatively by the measure. The HRV measures were also calculated from the power spectrum estimated by the autoregressive (AR) model identification. The ratio of the low frequency power to the high frequency power increased linearly with the work level. In conclusion, the HRV measures obtained by the AR power spectrum analysis were found to be sensitive to changes of mental workload.

Making information technology (IT) more accessible to elderly users is an important objective, in particular, concerning input devices. In this study, it has been investigated how the aging factor and the letter (character) size of a keyboard affects the efficiency in data entry. In addition, computer experience by the elderly was examined relative to efficiency. The performance measures (entry speed and correctly entered number per min) were twice better in a young group of computer users than in middle-aged and elderly groups. The effect of the size of the keyboard letters on performance was observed for the middle-aged and elderly groups who had no experience using a computer. The young, middle-aged, and elderly groups with computer experience were not affected by the size of the keyboard letters.

It is generally known that the autonomic nervous system regulates the pupil. In this study, we attempted to assess mental workload on the basis of the fluctuation rhythm in the pupil area. Controlling the respiration interval, we measured the pupil area during mental tasking for one minute. We simultaneously measured the respiration curve to monitor the respiration interval. We required the subject to perform two mental tasks. One was a mathematical division task, the difficulty of which was set to two, three, four, and five dividends. The other was a Sternberg memory search task, which had four work levels defined by the number of memory sets. In the Sternberg memory search, the number of memory set changed from five to eight. In such a way, we changed the mental workload induced by mental loading. As a result of calculating an autoregressive (AR) power spectrum, we could observe two peaks which corresponded to the blood pressure variation and respiratory sinus arrhythmia under a low workload. With an increased workload, the spectral peak related to the respiratory sinus arrhythmia disappeared. The ratio of the power at the low frequency band, from 0.05-0.15Hz, to the power at the respiration frequency band, from 0.35-0.4Hz, increased with the work level. In conclusion, the fluctuation of the pupil area is a promising means for the evaluation of mental workload or autonomic nervous function.

The purpose of this study is to show the chaotic features of rhythmic joint movement. Depending on the experimental conditions, one (or both) elbow angle(s) was (were) measured by one (or two) goniometer(s). Pacing was provided for six different frequencies presented in random order. When the frequency of the pace increased, the fractal dimension and first Lyapunov exponent tended to increase. Moreover, the first Lyapunov exponent obtained positive values for all of the observed data. These results indicate that there is chaos in rhythmic joint movement and that the larger the frequency, the more chaotic the joint movement becomes.

In this study, we clarified the differences in the pointing time required when using a touch panel and a PC mouse for three age groups: young, middle-aged, and elderly. We constructed a performance model for a touch panel operation (Experiment 1). Moreover, we investigated the visual interference caused by a multi-target presentation (Experiment 2). The delay caused by visual interference for the right-hand target was longer than that for the left-hand target, and that for the upper target was longer than that for the lower target.

Two method to predict targets which a user is about to point with a mouse on the basis of the trajectory of the mouse cursor were proposed. The effects of the interval between targets, the position of targets, the sampling interval and the number of sampling on the pointing time and the prediction accuracy were investigated. In both methods, the distance between targets had little effects on the pointing time. The prediction accuracy was found to be affected by the position of targets. In both prediction methods, the angle between the cursor movement vector and the vector which connects the current cursor position and the center of each target is calculated every st. As for Prediction Method1 that regards the target which correspond to the minimum angle continuously 5 times as the candidate target, the optimal condition of the sampling interval was found to be 0.06 sec or 0.08 sec. Concerning Prediction Method2 that calculates the angle n times and determines the minimum cumulative value as the candidate, the optimal condition of the number of sampling was 8.

The purpose of this research is to show that the stress during the VDT task could be evaluated using the chaotic features for the focal accommodation system and the pupil area. The result of this experiment shows that the fractal dimension for the pupil area can be used to evaluate the stress during the VDT task. Moreover, it is shown that the chaotic property in the fixed target measurement is higher than that in the linear control and step control measurements. However, the first Lyapunov exponent hardly changed over time for all of three accommodation measurements.

In this paper, an attempt was made to evaluate mental workload using chaotic analysis of EEG. EEG signals registered from Fz and Cz during a mental task (mental addition) were recorded and analyzed using attractor plots, fractal dimensions, and Lyapunov exponents in order to clarify chaotic dynamics and to investigate whether mental workload can be assessed using these chaotic measures. The largest Lyapunov exponent for all experimental conditions took positive values, which indicated chaotic dynamics in the EEG signals. However, we could not evaluate mental workload using the largest Lyapunov exponent or attractor plot. The fractal dimension, on the other hand, tended to increase with the work level. We concluded that the fractal dimension might be used to evaluate a mental state, especially a mental workload induced by mental task loading.

The present study investigated the human ability to selectively process pictures and words in free recall. We explored whether successful bias towards a subset of priority items occurs at the expense of the remaining items-i.e., whether successful priority item bias necessitates the dumping of information related to non-priority items. It has been shown that an increase in the percentage of correct recalls to items given priority in the pre-test instructions induces a decrease in the percentage of correct recalls for non-priority items. Even in a free recall experimental paradigm, the information dumping phenomenon was observed. However, there were no effects of stimulus presentation time and stimulus modality (picture vs. word) on the percentage of correct recalls detected.

In this study, we developed a new performance model that uses an index of difficulty to predict the pointing time required for a pointing task when using a PC mouse. Forty-nine subjects were classified into three age groups: young, middle-aged, and elderly. Experimental factors were the target size, the target distance, and the approach angle to the target. The time for pointing and the coordination of the pointer (mouse cursor) were measured in all conditions. The pointing time was significantly longer for the elderly group than for the young and middle-aged groups. Moreover, the pointing time in each age group tended to increase linearly with an increase in target distance and to decrease as a logarithmic function with an increase in target size. Based on these results, we proposed a new model for measuring performance when operating a PC mouse. Our model received a higher rating for ease-of-use than conventional models. It was clarified that the performance model for elderly persons was different from that for other age groups using the proposed model.

This study was conducted to assess the relationship between fatigue and pupillary responses. Pupillary responses, ECG and blood pressure were measured for 24 hours every 30 min in 8 subjects. A questionnaire was used to rate subjective feeling of fatigue. Twenty-four hours were divided equally into four 6-hour blocks. Subjective feeling of fatigue increased markedly in the fourth block, and the difference in subjective fatigue between fourth and first blocks was significant. Of nine pupillary responses, the pupil diameter was found to decrease with time. With respect to the function of the autonomic nervous system such as heart rate, systolic blood pressure and diastolic blood pressure, only heart rate was found to be sensitive to the increased subjective feeling of fatigue. A significant difference was found in the mean pupil diameter and mean heart rate between the last and first blocks. This result indicates that pupil diameter is related to fatigue and can be used to assess fatigue. Possible implications for fatigue assessment are discussed.

Using event-related potential (P300 and CNV), the cognitive function of elderly subjects was compared with that of young subjects. It was found that the prolonged cognitive information processing induced by aging was reflected in the P300 and N400 latency. The effects of aging were not observed in the P300 amplitude. The CNV measurements, in the range of this study, did not reflect the effects of aging. This might be because the CNV reflects a higher cognitive function as compared with P300 and the effects of aging do not appear in such a function. The data also suggested that the cognitive style must be taken into account when evaluating the deterioration of cognitive functions with aging.