Effects of green tea and roasted green tea on human responses.

Our objective was to elucidate the effects of tea consumption on refreshment and stress reduction/recovery through examining the multiple associations among factors such as various physiological responses and task performance. Participants included 20 healthy young men who performed a mental arithmetic task while 11 physiological responses were measured. The experiments were conducted twice under different beverage consumption conditions on separate days. The mental arithmetic task was executed six times in 1 day; participants ingested hot water, green tea, or roasted green tea (hojicha) before each task. Several subjective assessments: subjective fatigue, stress, mental workload, and flow were evaluated after each task. The R-R intervals, heart rate variability spectral components, the Poincaré plot indices (SD1 and SD2) and plethysmogram amplitude tended to decrease during task periods compared to resting periods. Tissue blood volume/flow (TBV, TBF) and near-infrared spectroscopy responses (NIRS) were lower in the tea condition than in the hot water condition. By scrutinizing various indicators, we found that aromatic stimulation of Japanese tea beverages has the potential to induce positive effects, enhance mental task performance, promote refreshment, and alleviate feelings of fatigue. These positive effects were observed even in small quantities and within a short duration, mirroring responses observed in daily consumption.

Mental workload task modeled on office work: Focusing on the flow state for well-being.

This research aimed to objectively evaluate the optimal state of desk work (flow state) through physiological measurements and use the data to support workers' mental health and well-being. We suppose that the flow state evaluation in real-time can contribute to a concentrated work environment, improved work efficiency, and stabilize worker's minds. This study reports on the development of the mental task modeled on daily work for the physiological measurement experiment. In the first phase of the research, a field survey was conducted with 55 desk workers to understand the details of their jobs and develop suitable mental tasks. Further, the relationship between daily work content and subjective stress was clarified. In the second phase, based on the results of the field survey, a task inducing the flow state was developed for practical use. Through empirical experiments with 35 participants (22 adults and 13 students), the developed task was evaluated for its usefulness and possible issues by examining the relationships among subjective assessment, task performance, degree of flow state, and individual characteristics. The study results showed that the proposed mental task developed in this study constitutes practical work that can be used for concentrated and goal-directed efforts. The task also demonstrated the property of inducing a flow state. Further, the results suggest that it is necessary to adjust the task difficulty level and implement effective feedback methods to induce the flow state more effectively.

Estimating core body temperature using electrocardiogram signals.

Suppressing the elevation in core body temperature is an important factor in preventing heatstroke. However, there is still no non-invasive method to sense core body temperature. This study proposed an algorithm that estimates core body temperature based on electrocardiogram signals. A total of 12 healthy men (mean age ± SD = 39.6 ± 13.4) performed an ergometric exercise load test under two conditions of exercise load in an environmental chamber adjusted to a temperature of 35°C and humidity of 50%. Vital sensing data such as electrocardiograms, core body temperatures, and body surface temperatures were continuously measured, and physical data such as body weight were obtained from participants pre- and post-experiment. According to basic physiological knowledge, heart rate and body temperature are closely related. We analyzed the relationship between core body temperature and several indexes obtained from electrocardiograms and found that the amount of change in core body temperature had a strong relationship with analyzed data from electrocardiograms. Based on these findings, we developed the amount of change in core body temperature estimation model using multiple regression analysis including the Poincaré plot index of the ECG R-R interval. The estimation model showed an average estimation error of -0.007°C (average error rate = -0.02%) and an error range of 0.457-0.445°C. It is suggested that continuous core body temperature change can be estimated using electrocardiogram signals regardless of individual characteristics such as age and physique. Based on this applicable estimation model, we plan to enhance estimation accuracy and further verify efficacy by considering clothing and environmental conditions.