Wrist Skin Temperature Research Articles

Association between skin temperature and actigraphic sleep metrics in patients with Parkinson's disease: The PHASE study

Introduction Sleep initiation and maintenance are linked to thermoregulation. In Parkinson's disease (PD), thermoregulatory dysfunction potentially worsens sleep disorders. However, the association between thermoregulation and sleep quality in patients with PD remains unclear. We aimed to examine the association between skin temperature, a measure of heat dissipation, and actigraphic sleep metrics in PD.Methods In this cross-sectional study with 186 outpatients with PD and 580 non-PD controls, we measured wrist skin temperature (WST) and actigraphic sleep quality for seven days in PD and two days in controls in real-life settings. Linear mixed-effect models were used to examine the association between nighttime WST and sleep quality.Results Nighttime WST in PD was significantly lower than that in controls (adjusted difference 0.39 [95 % confidence interval, 0.23–0.54] °C, P < 0.001). In patients with PD, changes in sleep efficiency, wake after sleep onset, total sleep time, and log-transformed fragmentation index per 1 °C increase in nighttime WST were 3.2 (95 % CI, 2.4–3.9) %, −10.3 (95 % CI, −13.6, −7.1) minutes, 13.4 (95 % CI, 9.1–17.8) minutes, and −0.09 (95 % CI: −0.12, −0.06), respectively, independent of potential confounders. Significant interactions were observed between nighttime WST and the presence of PD for sleep efficiency, wake after sleep onset, and total sleep time.Conclusions: Within-individual changes in nighttime WST were significantly associated with changes in actigraphic sleep measures in PD. Interventional studies are necessary that address the limitations and potential biases of this study to elucidate whether cutaneous temperature modulation can enhance the quality of sleep in PD.

Understanding wrist skin temperature changes to hormone variations across the menstrual cycle

Consumer devices are increasingly used to monitor peripheral body temperature (PBT) for menstrual cycle tracking, but the link between PBT and hormone variations remains underexplored. This study examines the relationship between these variables with a focus on nightly wrist skin temperature (WST). Fifty participants provided physiological and self-reported data, including WST, daily step counts, glucose levels, hormone levels (E3G, LH), and diary entries. Results show a negative correlation between WST and hormone levels when E3G and LH are below average, and this trend was robust to demographics and self-reported stress. Increased variance between mid-cycle hormonal peaks and WST fluctuations may stem from differences between basal body temperature (BBT) and WST. This research suggests that algorithms reliant on body temperature for tracking hormonal changes or other aspects of the menstrual cycle may need to account for increased variance in WST trends if they are meant to be deployed on wearable devices.

Physiological Response to the COVID-19 Vaccine: Insights From a Prospective, Randomized, Single-Blinded, Crossover Trial.

Rapid development and implementation of vaccines constituted a crucial step in containing the COVID-19 pandemic. A comprehensive understanding of physiological responses to these vaccines is important to build trust in medicine. This study aims to investigate temporal dynamics before and after COVID-19 vaccination in 4 physiological parameters as well as the duration of menstrual cycle phases. In a prospective trial, 17,825 adults in the Netherlands wore a medical device on their wrist for up to 9 months. The device recorded their physiological signals and synchronized with a complementary smartphone app. By means of multilevel quadratic regression, we examined changes in wearable-recorded breathing rate, wrist skin temperature, heart rate, heart rate variability, and objectively assessed the duration of menstrual cycle phases in menstruating participants to assess the effects of COVID-19 vaccination. The recorded physiological signals demonstrated short-term increases in breathing rate and heart rate after COVID-19 vaccination followed by a prompt rebound to baseline levels likely reflecting biological mechanisms accompanying the immune response to vaccination. No sex differences were evident in the measured physiological responses. In menstruating participants, we found a 0.8% decrease in the duration of the menstrual phase following vaccination. The observed short-term changes suggest that COVID-19 vaccines are not associated with long-term biophysical issues. Taken together, our work provides valuable insights into continuous fluctuations of physiological responses to vaccination and highlights the importance of digital solutions in health care. RR2-10.1186/s13063-021-05241-5.

Students’ thermal comfort and cognitive performance in fan-assisted naturally ventilated classrooms in tropical Singapore

Fan-assisted cooling strategies are widely employed in tropical climates due to their energy-saving benefits while ensuring thermal comfort through increased air temperature and air velocity. This study conducted experiments involving secondary school students in fan-assisted naturally ventilated classrooms in tropical Singapore. A total of thirty-six students from two secondary schools participated in this study. The classroom thermal environment was measured, students' thermal comfort was surveyed, physiological responses were monitored, and students' cognitive performance was assessed in different classrooms with various fan configurations. Thermal comfort survey results indicated that students' thermal comfort can be maintained at neutral with elevated air velocity, when classroom temperature remained at or below 30 °C. Students’ wrist skin temperature, arm skin temperature, and heart rate showed significant differences under various thermal conditions and thermal sensations, suggesting the potential use of physiological parameters to predict students' thermal comfort in fan-assisted naturally ventilated classrooms. This study also observed a significant impact of classroom thermal condition on students' cognitive performance. It was found in both schools that students' cognitive performance scores decreased significantly with increased temperature and decreased air velocity. Additionally, students' cognitive performance decreased by 9.2 % and 18.1 % in slightly warm and warm sensations, respectively, compared to the neutral sensation. These findings underscore the significance of air velocity as a crucial factor in the design of classroom environments, particularly in tropical climates, to enhance students' thermal comfort and optimize their cognitive performance.

Sex-specific differences in physiological parameters related to SARS-CoV-2 infections among a national cohort (COVI-GAPP study).

Considering sex as a biological variable in modern digital health solutions, we investigated sex-specific differences in the trajectory of four physiological parameters across a COVID-19 infection. A wearable medical device measured breathing rate, heart rate, heart rate variability, and wrist skin temperature in 1163 participants (mean age = 44.1 years, standard deviation [SD] = 5.6; 667 [57%] females). Participants reported daily symptoms and confounders in a complementary app. A machine learning algorithm retrospectively ingested daily biophysical parameters to detect COVID-19 infections. COVID-19 serology samples were collected from all participants at baseline and follow-up. We analysed potential sex-specific differences in physiology and antibody titres using multilevel modelling and t-tests. Over 1.5 million hours of physiological data were recorded. During the symptomatic period of infection, men demonstrated larger increases in skin temperature, breathing rate, and heart rate as well as larger decreases in heart rate variability than women. The COVID-19 infection detection algorithm performed similarly well for men and women. Our study belongs to the first research to provide evidence for differential physiological responses to COVID-19 between females and males, highlighting the potential of wearable technology to inform future precision medicine approaches.

Response to Melatonin Treatment in Children With Autism spectrum Disorder and Relationship to Sleep Parameters and Melatonin Levels.

Melatonin is one of the most used pharmacologic treatments for sleep problems in autism spectrum disorder, though its relationship with circadian and sleep parameters is still not well stablished. A naturalistic study was conducted in children with autism spectrum disorder, previously drug-naïve, before and after treatment with immediate-release melatonin. Circadian rhythms and sleep parameters were studied using an ambulatory circadian-monitoring device, and saliva samples were collected enabling determination of dim light melatonin onset. Twenty-six children with autism spectrum disorder (age 10.50 ± 2.91) were included. Immediate-release melatonin modified circadian rhythm as indicated by wrist skin temperature, showing an increase at night. A positive correlation was found between time of peak melatonin and sleep efficiency improvement values. Sleep-onset latency and efficiency improved with immediate-release melatonin. Immediate-release melatonin could be an effective treatment to improve sleep onset and restore a typical pattern of wrist temperature, which appears to be lost in autism spectrum disorder.

A novel theoretical model for predicting the individuals’ thermal sensations based on air temperature and biomarkers measured by wearable devices

Optimal control of indoor thermal environments based on real-time monitoring of occupants' feeling of warmth (a.k.a. thermal sensation) is one of the effective strategies to improve building energy efficiency and occupant comfort. Accordingly, developing an individual (or personal) thermal comfort model based on continuous observation of biomarkers (often measured by wearable devices) has received much research attention in recent years. Whilst almost all the comfort prediction models presented in the literature are based on a data-driven approach and machine learning techniques, this paper presents a novel theoretical model aimed at explaining the causal relationship in the prediction of thermal sensations based on key environmental and physiological parameters, incl. skin temperature, heart rate, and air temperature. The proposed model is grounded on the ASHRAE thermal sensation index (TSENS) and is based on mediating effects of thermoregulatory and cardiac responses. The new model's performance was evaluated under different thermal environmental conditions by comparing it against the PMV values and the experimental data available from the literature. Results showed that the proposed model could accurately predict individual thermal sensations by monitoring the air temperature, overall or wrist skin temperature, and heart rate (or metabolic rate). This model can provide new insight into individual thermal comfort assessment and can be used alone or in combination with data-driven machine learning models for continuous monitoring of thermal comfort conditions.

Correlation analysis and modeling of human thermal sensation with multiple physiological markers: An experimental study

This paper investigates the correlation of human thermal sensation with multiple physiological information in stable indoor thermal environment. Fifteen young male subjects from East China participate in the experimental study. The thermal sensation votes (TSVs) are collected by subjective questionnaire, and six physiological information are measured simultaneously, i.e., wrist skin temperature, blood pressure, heart rate, heart rate variability (ECG), skin conductance and blood oxygen saturation. A total of nine different physiological markers including four ECG signals are recorded. The deviation analysis between TSV and PMV standard is conducted. A detailed correlation analysis of nine physiological markers with thermal sensation is performed. It is found that young males of East China prefer lower ambient temperature in summer than PMV’s prediction. Two environmental and seven physiological variables have obvious correlations with TSV. Among them, wrist skin temperature, heart rate and ECG (pNN50) are three physiological markers that have high correlations with TSV. On this basis, a data-driven thermal sensation predictive model based on multiple physiological information is designed. The accuracy is better than that of skin temperature based predictive model or PMV evaluation.

Experimental study of the negative effects of raised bedroom temperature and reduced ventilation on the sleep quality of elderly subjects.

This study investigated the effects of air temperature and ventilation on the sleep quality of elderly subjects and elucidated the mechanisms involved. Sixteen subjects aged over 65 years old were exposed to four conditions in a 2 × 2 design: air temperatures of 27°C and 30°C (with a ceiling fan in operation at 30°C) and two ventilation conditions (with and without mechanical ventilation) in experimental bedrooms. Their electroencephalogram, electrooculogram, chin electromyogram, electrocardiogram, respiration, oxygen saturation, and wrist skin temperature were measured continuously during sleep. Saliva samples were collected, and blood pressure was measured both before and after sleep. The results showed that at the temperature of 30°C, the total sleep time, sleep efficiency, and duration of REM sleep of the elderly decreased by 26.3min, 5.5%, and 5.3min, respectively, and time awake increased by 27.0min, in comparison with 27°C, indicating that the sleep quality of the elderly is very vulnerable to heat exposure. Even a small heat load led to an overactive sympathetic nervous system and increased wrist skin temperature, which reduced sleep quality. Improving the ventilation increased the duration of deep sleep and REM sleep by 10.3min and 3.7min, respectively. Higher pollutant concentrations affected the respiration and autonomous nervous systems to reduce sleep quality. The benefits of improved thermal environment and ventilation on sleep quality were found to be additive. Good ventilation and the avoidance of raised temperatures in the bedroom are thus both important for the sleep quality of the elderly.

Wearable sensors for prediction of intraamniotic infection in women with preterm premature rupture of membranes: a prospective proof of principle study

PurposeTo evaluate the use of wearable sensors for prediction of intraamniotic infection in pregnant women with PPROM.Materials and methodsIn a prospective proof of principle study, we included 50 patients diagnosed with PPROM at the University Hospital Zurich between November 2017 and May 2020. Patients were instructed to wear a bracelet during the night, which measures physiological parameters including wrist skin temperature, heart rate, heart rate variability, and breathing rate. A two-way repeated measures ANOVA was performed to evaluate the difference over time of both the wearable device measured parameters and standard clinical monitoring values, such as body temperature, pulse, leucocytes, and C-reactive protein, between women with and without intraamniotic infection.ResultsAltogether, 23 patients (46%) were diagnosed with intraamniotic infection. Regarding the physiological parameters measured with the bracelet, we observed a significant difference in breathing rate (19 vs 16 per min, P < .01) and heart rate (72 vs 67 beats per min, P = .03) in women with intraamniotic infection compared to those without during the 3 days prior to birth.In parallel to these changes standard clinical monitoring values were significantly different in the intraamniotic infection group compared to women without infection in the 3 days preceding birth.ConclusionOur results suggest that wearable sensors are a promising, noninvasive, patient friendly approach to support the early detection of intraamniotic infection in women with PPROM. However, confirmation of our findings in larger studies is required before implementing this technique in standard clinical management.

Investigation of personal thermal comfort in office building by implementation of smart bracelet: A case study

Thermal comfort is significant factor in the overall satisfaction level and affects directly the building energy performance within heating and cooling systems. Through this work, the short-term field investigation of smart monitoring devices was applied for personal thermal comfort investigation. The conceptual approach was presented for the case of specific office building. The low cost sensing technology was implemented in this investigation as key advantage of herein considered approach. The users wore smart bracelets which monitored physiological parameters, i.e. skin wrist temperature and heart rate during the day in office facility. Simultaneously, the environmental parameters were measured (air temperature, relative air humidity and CO2 concentration). Field survey (subjective response from occupants) was conducted as well. Wrist skin temperature from the individual users has a positive correlation with thermal comfort evaluation for female (0.54) and male (0.36) user. Additionally, for the data from male user, the CO2 concentration in the office had a positive correlation as well (0.45). The positive correlation between examined parameters endorse the application of the proposed measuring technology (wearable device) for detection of personal thermal comfort. The proposed approach represents a basis for further development of novel regulation approach for heating/cooling systems in buildings, since it allows more complex evaluation of the personal thermal comfort factors.

Thermal Perception and Physiological Responses under Different Protection States in Indoor Crowded Spaces during the COVID-19 Pandemic in Summer

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 &lt; 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.

Investigation of the use of a sensor bracelet for the presymptomatic detection of changes in physiological parameters related to COVID-19: an interim analysis of a prospective cohort study (COVI-GAPP)

ObjectivesWe investigated machinelearningbased identification of presymptomatic COVID-19 and detection of infection-related changes in physiology using a wearable device.DesignInterim analysis of a prospective cohort study.Setting, participants and interventionsParticipants from a national...

Comparison of wrist skin temperature with mean skin temperature calculated with Hardy and Dubois's seven-point method while sleeping

Wrist skin temperature has been validated to be sensitive to the thermal state of awake people, but its correlation with thermal state of sleeping people has not been investigated. In the present study four human subject experiments were performed on both young and elderly subjects in different seasons (winter, transition, summer). Their skin temperatures were continuously measured during the whole night sleep at wrist (WST) and at the normally accepted seven points (forehead, chest, posterior forearm, hand, anterior thigh, anterior calf, and foot) proposed by Hardy & Dubois. The WST was compared with the mean skin temperature (MST) calculated with Hardy & Dubois’s seven-point method. The results show that the WST was moderately and positively correlated with MST, with the Pearson's R value ranged from 0.44 to 0.63. When comparing the variation of WST and MST throughout the whole-night sleep, the averaged maximum crossing correlation coefficient was 0.56 (Q1 = 0.4, Q3 = 0.7) and the lag time was on average −10.4 min (Q1 = -11.0, Q3 = 0.0 min), indicating that the WST was synchronically correlated with MST. Similar to MST, the WST could differentiate sleeping micro thermal environments which were created by different combinations of indoor temperature and bedding thermal insulation. These results suggest that the WST was linearly and synchronically correlated with the MST calculated using Hardy & Dubois’s seven-point method. Thus, the skin temperature at wrist could provide information on thermal state of human body when people asleep, making it possible to measure skin temperature in field studies and to personally and energy efficiently control the thermal environment for sleep.

The effects of ventilation and temperature on sleep quality and next-day work performance: pilot measurements in a climate chamber

Ten healthy young adults slept one by one in a specially designed and constructed sleep capsule located in a climate chamber at two temperatures (24 °C and 28 °C) and two ventilation rates that ensured that the resulting CO2 concentrations were 800 and 1700 ppm. Subjectively rated sleep quality was reduced at 28 °C and reduced ventilation, while sleep onset latency was longer under these conditions. Sleep efficiency was lower at 28 °C. Subjectively rated fatigue and sleepiness decreased after sleeping under all conditions but less so after sleeping at 28 °C. The subjects indicated that their work performance improved after sleeping at 24 °C but not when ventilation was reduced and the temperature increased. Both objectively measured and subjectively rated work performance was worse after sleeping in the condition with increased temperature. The subjects felt warmer at 28 °C although the thermal environment was still rated as acceptable but the air in the capsule was rated stuffier, the acceptability of the air quality decreased and the rated odour intensity increased at this condition. The wrist skin temperature was always higher at 28 °C with reduced ventilation but only during the sleep onset latency period. The subjects felt slightly warm and rated the air stuffier when ventilation was reduced. The present results, albeit from a small exploratory pilot study, show that increased temperature and reduced ventilation both have negative effects on sleep quality, which may have consequences for next-day work performance. These pilot experiment results require validation due to the low number of subjects.

Association of bedroom environment with the sleep quality of elderly subjects in summer: A field measurement in Shanghai, China

Sleep is essential for the health of elderly people, but few studies have made connection between their sleep quality and their bedroom environment. This study performed field measurements in Shanghai, China, to investigate the bedroom thermal environment and ventilation and their associations with the sleep quality of elderly subjects in summer. Forty-five elderly subjects participated in this study for six consecutive days. Their bedroom air temperature, relative humidity and CO2 concentration were measured continuously and their sleep quality was objectively measured using a wrist-worn sleep tracker. Wrist skin temperature was measured continuously at night. Each morning after waking up the subjects assessed their sleep quality, recalled their thermal sensation, and recorded their bed covering, sleepwear and cooling/ventilation arrangements during that night. The results show that higher air temperature and CO2 concentration were both negatively correlated with objective sleep quality. Air temperature was the key factor influencing objective sleep quality. When air temperature increased by 1 °C, sleep efficiency (SE) decreased by 0.7%, duration of Rapid Eye Movement (REM) sleep decreased by 2.1min, and time awake increased by 2.3min. The sleep quality of elderly subjects was more negatively affected by heat exposure than has been previously reported for younger subjects. As CO2 concentration increased by 100 ppm, the Total Sleep Time (TST) decreased by 11min. The combined effects of air temperature, relative humidity and CO2 concentration were analyzed: TST and duration of REM sleep were reduced at higher air temperature, relative humidity and CO2 concentration.

The Accuracy of Wrist Skin Temperature in Detecting Ovulation Compared to Basal Body Temperature: Prospective Comparative Diagnostic Accuracy Study

BackgroundAs a daily point measurement, basal body temperature (BBT) might not be able to capture the temperature shift in the menstrual cycle because a single temperature measurement is present on the sliding scale of the circadian rhythm. Wrist skin temperature measured continuously during sleep has the potential to overcome this limitation.ObjectiveThis study compares the diagnostic accuracy of these two temperatures for detecting ovulation and to investigate the correlation and agreement between these two temperatures in describing thermal changes in menstrual cycles.MethodsThis prospective study included 193 cycles (170 ovulatory and 23 anovulatory) collected from 57 healthy women. Participants wore a wearable device (Ava Fertility Tracker bracelet 2.0) that continuously measured the wrist skin temperature during sleep. Daily BBT was measured orally and immediately upon waking up using a computerized fertility tracker with a digital thermometer (Lady-Comp). An at-home luteinizing hormone test was used as the reference standard for ovulation. The diagnostic accuracy of using at least one temperature shift detected by the two temperatures in detecting ovulation was evaluated. For ovulatory cycles, repeated measures correlation was used to examine the correlation between the two temperatures, and mixed effect models were used to determine the agreement between the two temperature curves at different menstrual phases.ResultsWrist skin temperature was more sensitive than BBT (sensitivity 0.62 vs 0.23; P<.001) and had a higher true-positive rate (54.9% vs 20.2%) for detecting ovulation; however, it also had a higher false-positive rate (8.8% vs 3.6%), resulting in lower specificity (0.26 vs 0.70; P=.002). The probability that ovulation occurred when at least one temperature shift was detected was 86.2% for wrist skin temperature and 84.8% for BBT. Both temperatures had low negative predictive values (8.8% for wrist skin temperature and 10.9% for BBT). Significant positive correlation between the two temperatures was only found in the follicular phase (rmcorr correlation coefficient=0.294; P=.001). Both temperatures increased during the postovulatory phase with a greater increase in the wrist skin temperature (range of increase: 0.50 °C vs 0.20 °C). During the menstrual phase, the wrist skin temperature exhibited a greater and more rapid decrease (from 36.13 °C to 35.80 °C) than BBT (from 36.31 °C to 36.27 °C). During the preovulatory phase, there were minimal changes in both temperatures and small variations in the estimated daily difference between the two temperatures, indicating an agreement between the two curves.ConclusionsFor women interested in maximizing the chances of pregnancy, wrist skin temperature continuously measured during sleep is more sensitive than BBT for detecting ovulation. The difference in the diagnostic accuracy of these methods was likely attributed to the greater temperature increase in the postovulatory phase and greater temperature decrease during the menstrual phase for the wrist skin temperatures.

Evaluation of individual thermal sensation at raised indoor temperatures based on skin temperature

In this study, we further investigate whether skin temperature can also assess individual thermal sensation as an effective physiological index while previous studies did not draw broadly generalizable conclusions at high temperature. The climate-controlled experiments include five temperature levels of 26, 30, 33, 37 and 39 °C, two relative humidity levels of 50% and 70%, and two activity levels with light and moderate and in which the estimated average metabolic rate were respectively 58 W/m2 and 165 W/m2. A total of 136 healthy subjects who lived in hot-humid climate for a long time participated in these experiments. During the experiments, the ratings of thermal sensation, comfort and acceptability were documented, local skin temperatures were continuously monitored, and five mean skin temperatures were calculated. Using Fisher discriminant analysis to model thermal sensation from skin temperature, then obtaining the thresholds of local and mean skin temperatures corresponding to different thermal sensation categories, and finally verifying the accuracy of the models assessment. The results show that the skin temperature can also predict thermal sensation at high temperatures of 30–39 °C beyond the range of normal temperatures. The proposed evaluation models show a high accuracy to predict the “hot/very hot” category, and up to 93% accuracy of predicting thermal sensation from wrist skin temperature. Additionally, thermal adaptation to high temperature and humidity can affect the prediction accuracy of “hot/very hot” category from skin temperature. The results of this study provide an important basis for early warning when human's safety risk occurs under high temperatures.

Thermal comfort modeling when personalized comfort systems are in use: Comparison of sensing and learning methods

Centralized HVAC systems are usually unable to cater to individual requirements when multiple occupants are present in the same zone. Personalized Comfort Systems (PCS) such as local fans and heaters, heated/cooled chairs, local ventilation systems, have shown to be useful for maintaining comfortable thermal conditions by creating a microclimate around each occupant. Previous studies have mostly focused on personalized thermal comfort modeling under regular HVAC operations, and there is a lack of work that focuses on personalized thermal comfort modeling when PCS devices are in use. In this study, we compare different sensing and machine learning methods to build personal comfort models when a local fan or heater is in use. The experiment was conducted in a controlled environment with three segments: regular (no fan/heater), fan on, and heater on. Our results indicate that the data from environmental sensors results in 2%–5% higher prediction accuracy compared to using a wearable device to monitor wrist skin temperature or thermal imaging to monitor skin temperature from different regions of the face. Furthermore, environmental sensors are more affordable and have relatively fewer privacy concerns compared to the physiological sensors. Overall, the results of this study support the use of environmental sensors for building personalized thermal comfort models with or without PCS. Furthermore, the results also highlight the need for building separate personalized thermal comfort models when PCS devices are in use, and when PCS devices are not in use.

Assessment of time window for sleep onset on the basis of continuous wrist temperature measurement

ABSTRACT The interactions of the principal circadian clock with the homeostatic sleep process create the time-sensitive window for easy falling asleep in the evening, which is affected by a thermoregulatory process. It has been hypothesized that the changes in skin and core body temperatures before the sleep onset might play a direct role in sleep regulation. To determine this time window, we recorded from 20 healthy participants (11 women and 9 men), aged 26–58 years, one overnight own-home ambulatory polysomnography and measured continuously wrist skin temperature with a wrist-worn accelerometer containing a skin temperature thermometer. Wrist skin temperatures which were read out from the thermometer of the accelerometers were modeled using linear mixed models, and the linear effect of time before the sleep onset on wrist temperature was analyzed using a mixed model with the sex and age as the covariates. We found that wrist skin temperatures increased on average by 0.6° (of Celcius) in 10 min prior to the sleep onset and could be tracked robustly along a slope of time (p = 0.004). Our current findings may be useful in further characterizing the window of time and its boundaries for easy falling asleep.