Excessive stress can lead to mental disorders, and in the worst cases, to suicide. The type of stress that is especially harmful to mind and body is known as distress. It is important for people to properly understand their own mental health condition to prevent distress-induced disorders. Recent studies have investigated this issue by developing indices for measuring distress levels by using physiological signals which reflect a person's sympathetic nervous system activity during a task that induces distress. However, in applying these technologies to real life, many factors can impact these stress indices including eustress, stress which induces positive responses caused by activities such as concentration on tasks. It is therefore, difficult to determine an actual distress level. To distinguish distress from eustress, we propose a new active distress sensing system. In this system, users are exposed to emotional stimuli and are expected to experience psychological responses depending on their distress levels. We developed this system using musical mood induction as the emotional stimuli. We established that the psychological response during a state of distress leads to specific skin conductance responses that are not the same as those under a eustress.

Guidelines devised to ensure that multiple and highly functional in-vehicle information systems (IVISs) are designed to present a distraction-free interface at the same time, need to consider the safety, functionality, and usability of image displays. However, no guidelines exist for quantitatively assessing drivers' cognitive workloads, and this includes usability and memorability. In this paper, we propose a method to measure drivers' visuospatial workload quantitatively. The method is incorporated in various interface tests including driving and human machine interface evaluations. The results indicated that the success rates of visuospatial working memory tasks can be used to rank the relative difficulties of the tasks, and the ranking order of these rates tended to be similar to that of the subjective difficulties.

Because of rapid population aging, it is necessary to design and develop senior-friendly or disability-friendly interfaces that can decrease the cognitive workload caused by an interface. At that time, the design implications and evaluation criteria of an interface should be needed for creating senior-friendly and disability-friendly interfaces. One of the elements that relate to memory functions for manipulating interfaces include working memory. However, rough standard of visuospatial memory remains unknown. Particularly, there are little reports about the relations between the age and the volume of visuospatial memory. In this paper, we aim to clarify this relations for proposing interface implications by using a visual pattern span test. For effective measurement of the memory, we implemented a gamified measurement application based on visual pattern span tests. The results indicated that the median numbers of memorable buttons on visuospatial memory were and 7.0 (interquartile range: 5.0-9.0). Also, the number of memorable buttons increases as the age increases until the age ranged 21-25 and then decreases gradually as the age increases after 21-25 years. Our evaluation suggest that it can be effective to measure memory performance of, especially, children by the applications that are designed based on the entertainment concepts including a gamification.

Indoor thermal quality affects not only a person's perception of comfort, but also their level of arousal, work performance and health. Therefore, it is important that thermal factors are controlled and that a thermal environment is designed in accordance with its purpose. In this study, we aim to design a thermal environment that improves both the arousal level and thermal comfort of the occupants. In order to confirm the possibility that changes in thermal factors can improve both the arousal level and thermal comfort, we investigated the relationships between the physiological parameters, subjective sensation, and the performance of tasks. Specifically, we directed participants to perform a mathematical task and an evaluation of subjective sensation relating to their comfort level and arousal level. Simultaneously, the physiological indices of the participants such as their skin temperature and respiration rate were measured, and tests such as electroencephalography (EEG) and electrocardiography (ECG) were conducted throughout several conditions of changes in the thermal factors. Through the results of our study, we confirm that the relationship between comfort sensation and arousal level corresponds to changes in the thermal factors, we carried out a quantitative and continuous evaluation of a person's comfort sensation and arousal level using physiological indices.

To understand the brain mechanisms involved in reward prediction on different time scales, we developed a Markov decision task that requires prediction of both immediate and future rewards, and ana- lyzed subjects’ brain activities using functional MRI. We estimated the time course of reward prediction and reward prediction error on different time scales from subjects' performance data, and used them as the explanatory variables for SPM analysis. We found topog- raphic maps of different time scales in medial frontal cortex and striatum. The result suggests that different cortico-basal ganglia loops are specialized for reward prediction on different time scales.