Touching is a medical action wherein a practitioner touches a patient’s body. Touching has positive physical and mental effects, and is an important technique for nursing. This study examines the effect of touching on patient frustration. To induce frustration, we adopted a mouse pointer-moving game and a calculation task: the game required moving a mouse pointer from the start to the goal without touching walls or obstacles. We asked the participants’ acquaintance to gently touch their backs during the intervention trials. For evaluation, we used power spectral density (PSD) and electroencephalogram (EEG) event-related potential (ERP), and participants’ self-evaluation scores. Theta, alpha, and beta band PSDs increased in frustrating tasks compared to the resting state, however, PSD increments of touching intervention tasks were less than that of control tasks. These results confirm that an acquaintance’s touching can reduce frustration in difficult tasks, and concomitantly reduce unpleasant emotions.
This study proposes a method for the automatic design of personalized playlists that places a listener in a positive mood (uplifting or relaxing feelings) based on individual’s impressions of audio tracks. This method designs a playlist with gradually changing personal impressions of audio tracks and induces individuals’ moods to be uplifting or relaxing. It estimates the subjective impressions of all audio tracks in the music database using the bagging method, a type of ensemble learning, and creates a personalized playlist. This study investigated the changes in a listener’s mood before and after listening to personalized playlists, non-personalized playlists, and playlists with randomly selected tracks using a psychological scale. Consequently, many personalized playlists have shifted the listener into a positive mood more than non-personalized playlists or random design playlists.
The indoor illumination levels affect emotional states, interpersonal impressions, and psychological distance between the self and others. In this study, we conducted experiment on the effect of the brightness of the room on face-to-face communication between participants as interviewee and the interviewer. Conducting a two-factor mixed analysis of variance on “illumination levels × pre- and post-evaluation,” we observed that in dim conditions, the interpersonal distance between the participants and interviewer became significantly closer. The psychological distance to the interviewer was evaluated to be closer in the dim condition. In terms of the degree of satisfaction with the conversation, in the dim condition, the evaluation of two items-“conversation was friendly” and “conversation was valuable”-increased. These results indicate that the dim condition, such as the lowest allowable level of illuminance according to illumination design guidelines, may have a positive effect on the first face-to-face communication.
This study examines a Kansei retrieval agent (KaRA) model based on fuzzy reasoning in terms of optimizing fuzzy rules. The KaRA model learns the user’s preferences based on the user’s sensory evaluation, and retrieves what the user wants from a large amount of data. The KaRA model based on fuzzy reasoning has information on membership functions and fuzzy rules. Previous studies have demonstrated the effectiveness of the KaRA model in terms of learning the user’s evaluation criteria by optimizing the membership function of fuzzy reasoning using numerical simulation. However, the fuzzy rules of the model have not been optimized. By optimizing fuzzy rules, the KaRA model can acquire the user’s sensibility evaluation information in linguistic expressions (fuzzy rules). Therefore, we confirmed the effectiveness of fuzzy rule optimization in the KaRA model. We conducted numerical simulations using pseudo-users and experiments with real users. Consequently, we examined the effectiveness of fuzzy rule optimization in the KaRA model.
In this study, we evaluate the adaptivity of a mobile robot, controlled by a navigation model, to changes in personal space within dynamic human-robot groups. Several recent attempts have been made to develop robots suitable for human communities. Although human interpersonal space depends on particular contexts and situations, humans occupy their own space while sharing situation-dependent implicit norms on maintaining socially appropriate distance from one another. We have developed a mobile robot that can move in a scenario where group members need to move adaptively by obeying situation-dependent implicit norms of movement. The results show that the mobile robot appears more adaptive to changes in the groups than a comparison robot, although such an approach may appear overly simplistic or relatively straightforward. Such insights suggest that our proposed method enables the robot to move appropriately and find its own appropriate position in the group under scenario constraints.
Recent studies have demonstrated that attractive faces can affect an observer’s time perception. However, it is unclear whether this relationship can be generalized to other visual stimuli. Therefore, we conducted two experiments: one with face images and another with meaningless figures. In Experiment 1, participants performed a temporal bisection task; they judged whether randomly presented images of attractive, neutral, and unattractive faces (five each) were closer to the short or long standard duration for each male and female image. Participants underestimated the display duration of attractive faces relative to unattractive and neutral faces. Experiment 2 presented participants with five attractive and five unattractive meaningless figures using the same procedure as in Experiment 1. No significant difference was found in the perceived time duration between attractive and unattractive meaningless figures. This suggests that the relationship between the attractiveness of visual stimuli and time perception may vary depending on stimuli characteristics.
The methodology of Kansei Engineering can grasp consumer’s subjective affective impressions about a product and turn it into concrete product solutions. The Kansei Food model is a specialized model doing this for food products. The aim of this paper is to interlink it with the more general model on Affective Engineering as well as to validate the findings by applying them in a case study. The general Kansei Engineering model and the Kansei Food model were analyzed, and the key parts of both models merged to a hybrid model. This model is then applied in a study on a development project for chocolate toffee fillings for sport applications. The case yielded valid results and gave an input to a parallel food development process. In conclusion, the Kansei Food model fits together with the general Kansei model. Hence, standardization makes it possible to have a more detailed look on sequential steps. Also, it becomes possible to transfer tools from other branch models (e.g. from automotive industry) in food industry and vice versa.
This study aimed to clarify the status of nurses’ support for outpatient cancer patients’ psychological concerns and related factors/issues. A survey was distributed among 804 outpatient nurses at 402 cancer care hospitals nationwide (as of April 2020). An analysis was conducted utilizing variables related to the characteristics of participants, departments, and hospitals as well as the status of support for cancer patients’ psychological concerns. Of the 212 individuals who responded, 201 (response rate: 25%) were included in the analysis. Approximately 68% of the outpatient nurses reported providing support to cancer patients with psychological concerns. Several respondents, however, indicated that there was ‘insufficient time’ to address their patients’ problems.