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Simple Summary: Human rhythmicity is subjected to the workings of the internal circadian clock, but it is also influenced by environmental time (mainly the light-dark cycle) and social timing imposed by the official time at our location, as well as by our work schedule. When a misalignment among these times occurs, an internal order impairment appears, which affects our health. Western Spain (GMT+1/+2) and Portugal (GMT0/+1) share similar longitudes (sun time) but have different official times, and thus they provide a "natural experiment" to assess how this discrepancy affects circadian rhythmicity and sleep in people with no work duties (>65 years). Although sleep duration was not affected, the circadian rhythms in the Portuguese were more robust, especially during weekdays, while higher desynchronization tended to occur in the Spaniards. Once official time was corrected by GMT0, meals took place later in Spain than in Portugal, especially as the day progressed, indicating the possible deleterious effect on circadian system robustness when official time is misaligned with its corresponding geographical time zone. Human circadian rhythmicity is subjected to the internal circadian clock, the sun and social clocks (official time, social/work schedules). The discrepancy among these clocks, as occurs when official time does not match its geographical time zone, may produce circadian disruption. Western Spain (GMT+1/+2) and Portugal (GMT0/+1) share similar longitudes (sun time) but have different official times. This provides a unique opportunity to evaluate the effects of official time on circadian rhythmicity and sleep in elderly and retired populations (with no remunerated duties presumed, although other social commitments may be present) at both locations. Although both populations slept enough for their age (7–8 h), circadian robustness (e.g., interdaily stability, relative amplitude) was greater in Portugal, especially during weekdays, while greater desynchronization (both body temperature vs. motor activity and body temperature vs. light exposure) tended to occur in the Spaniards. Once corrected by GMT0, meals took place later in Spain than in Portugal, especially as the day progresses, and a possible interplay between bed/meal timings and internal desynchronization was found. Our results point to the possible deleterious effect on circadian system robustness when official time is misaligned with its geographical time zone. [ABSTRACT FROM AUTHOR]

Currently, people in crowded indoor spaces are required to wear a variety of personal protective equipment to curb the spread of COVID-19. This study aimed to investigate the effects of wearing four types of personal protective equipment (unprotected, wearing masks, wearing face shield and wearing medical protective clothing) on human thermal perception and physiological responses in indoor crowded spaces in summer. The experiment was conducted in a climate chamber designed to simulate the indoor crowded spaces. Environmental parameters of climate chamber (air temperature, relative humidity and wind speed), physiological parameters of subjects (wrist skin temperature and pulse rate), and subjective perceptions (thermal sensation and thermal comfort) were collected during the experiment. The experimental results showed that medical protective clothing has the most obvious blocking effect on heat exchange between human and environment. Thermal sensation in state 4 (wearing medical protective clothing) was significantly (p < 0.05) higher than that in other states. The study of physiological parameters showed that the wrist skin temperature and pulse rate under different protection states increased with the increase of room temperature. Through regression analysis, the thermal sensation estimation model of protective personnel in indoor crowded spaces based on wrist skin temperature and pulse rate was established. The adjusted R2 and RMSE of all models were above 82% and less than 1, indicating that the established thermal sensation model had a good prediction effect. [ABSTRACT FROM AUTHOR]

Thermal comfort is an essential environmental factor related to quality of life and work effectiveness. We assessed the feasibility of wrist skin temperature monitoring for estimating subjective thermal sensation. We invented a wrist band that simultaneously monitors skin temperatures from the wrist (i.e., the radial artery and ulnar artery regions, and upper wrist) and the fingertip. Skin temperatures from eight healthy subjects were acquired while thermal sensation varied. To develop a thermal sensation estimation model, the mean skin temperature, temperature gradient, time differential of the temperatures, and average power of frequency band were calculated. A thermal sensation estimation model using temperatures of the fingertip and wrist showed the highest accuracy (mean root mean square error [RMSE]: 1.26 ± 0.31). An estimation model based on the three wrist skin temperatures showed a slightly better result to the model that used a single fingertip skin temperature (mean RMSE: 1.39 ± 0.18). When a personalized thermal sensation estimation model based on three wrist skin temperatures was used, the mean RMSE was 1.06 ± 0.29, and the correlation coefficient was 0.89. Thermal sensation estimation technology based on wrist skin temperatures, and combined with wearable devices may facilitate intelligent control of one's thermal environment. [ABSTRACT FROM AUTHOR]

Thermal comfort is an essential environmental factor related to quality of life and work effectiveness. We assessed the feasibility of wrist skin temperature monitoring for estimating subjective thermal sensation. We invented a wrist band that simultaneously monitors skin temperatures from the wrist (i.e., the radial artery and ulnar artery regions, and upper wrist) and the fingertip. Skin temperatures from eight healthy subjects were acquired while thermal sensation varied. To develop a thermal sensation estimation model, the mean skin temperature, temperature gradient, time differential of the temperatures, and average power of frequency band were calculated. A thermal sensation estimation model using temperatures of the fingertip and wrist showed the highest accuracy (mean root mean square error [RMSE]: 1.26 ± 0.31). An estimation model based on the three wrist skin temperatures showed a slightly better result to the model that used a single fingertip skin temperature (mean RMSE: 1.39 ± 0.18). When a personalized thermal sensation estimation model based on three wrist skin temperatures was used, the mean RMSE was 1.06 ± 0.29, and the correlation coefficient was 0.89. Thermal sensation estimation technology based on wrist skin temperatures, and combined with wearable devices may facilitate intelligent control of one's thermal environment.