Purpose: The commercialization of sleep activity tracking devices has made it possible to manage sleep quality at home. However, it is necessary to verify the reliability and accuracy of wearable devices through comparison with polysomnography (PSG), which is the standard for tracking sleep activity. This study aimed to monitor overall sleep activity using Fitbit Inspire 2™ (FBI2) and to evaluate its performance and effectiveness through PSG under the same conditions. Patients and Methods: We compared the FBI2 and PSG data of nine participants (four male and five female participants; average age, 39 years) without severe sleeping problems. The participants wore FBI2 continuously for 14 days, considering the period of adaptation to the device. FBI2 and PSG sleep data were compared using paired t-tests, Bland–Altman plots, and epoch-by-epoch analysis for 18 samples by pooling data from two replicates. Results: The average values for each sleep stage obtained from FBI2 and PSG showed significant differences in the total sleep time (TST), deep sleep, and rapid eye motion (REM). In the Bland–Altman analysis, TST (P = 0.02), deep sleep (P = 0.05), and REM (P = 0.03) were significantly overstated in FBI2 compared to PSG. In addition, time in bed, sleep efficiency, and wake after sleep onset were overestimated, while light sleep was underestimated. However, these differences were not statistically significant. FBI2 showed a high sensitivity (93.9%) and low specificity (13.1%), with an accuracy of 76%. The sensitivity and specificity of each sleep stage was 54.3% and 62.3%, respectively, for light sleep, 84.8% and 50.1%, respectively, for deep sleep, and 86.4% and 59.1%, respectively for REM sleep. Conclusion: The use of FBI2 as an objective tool for measuring sleep in daily life can be considered appropriate. However, further research is warranted on its application in participants with sleep-wake problems.

Cold hypersensitivity in the hands and feet (CHHF) is a common symptom in Korea and patients with CHHF complain of coldness in the hands and feet in an environment that is not considered cold by unaffected people. In traditional East Asian medicine, CHHF is believed to be accompanied by various diseases and symptoms, and is considered a symptom that needs active treatment. CHHF is used for pattern identification in the cold pattern, yang deficiency, and constitution. This study aimed to examine the differences in frequencies of chronic diseases with respect to the presence of CHHF. Disease history, CHHF, body measurements, and blood test survey data from 6149 patients collected by 25 medical institutes in Korea were obtained from the Korean Medicine Data Center. The participants were divided into CHHF (n = 1909) and non-CHHF groups (n = 3017) according to the CHHF survey. The differences in frequencies of 18 diseases were analysed using chi-square tests, and the odds ratios (ORs) for each disease according to CHHF status were examined via logistic regression with adjustment for age, sex, and body mass index (BMI). Based on chi-square test results, the CHHF group showed a higher frequency of the following diseases: anaemia, hypotension, chronic gastritis, reflux oesophagitis, chronic rhinitis, dysmenorrhoea, and gastroduodenal ulcer. Diseases found in lower frequencies were as follows: hypertension, diabetes mellitus, impaired fasting glucose, dyslipidaemia, stroke, fatty liver, and angina pectoris. In addition, from the logistic regression with adjustment for age, sex, and BMI, the CHHF group showed a lower OR in diabetes mellitus and dyslipidaemia than the non-CHHF group, but a higher OR in degenerative arthritis, chronic gastritis, gastroduodenal ulcer, reflux oesophagitis, and chronic rhinitis. This study showed that CHHF is associated with chronic disease. Further large-scale prospective studies are needed to validate these associations.

Background: Cold hypersensitivity (CH) and sleep disorders are not limited to patients with specific diseases, as they are also commonly observed in the general population. The objective of this study was to investigate the relationship between CH and sleep quality.Methods: This cross-sectional study analyzed data from a cohort of 5,052 individuals living in South Korea. Based on the results of a questionnaire on CH, the participants were classified into four groups: non-CH, CH in the hands (CHH), CH in the feet (CHF), and CH in the hands and feet (CHHF). Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI). Multiple regression was used for groupwise comparisons of total PSQI scores and the scores for each component, and logistic regression was used to find the odds ratios of being a “poor sleeper” (PSQI≥8.5).Results: The CHF and CHHF groups showed significantly higher scores than the non-CH group on the overall PSQI as well as on the following sleep components: subjective sleep quality, sleep latency, habitual sleep efficiency, sleep disturbance, and sleep medication use. The odds ratios for being a “poor sleeper” were significant in the CHF (1.84; CI=1.38-2.43) and CHHF groups (1.54; CI=1.25-1.89), but the CHH group did not show any difference from the non-CH group. We identified a correlation between CH in the feet and poor sleep quality.Conclusions: These findings help to elucidate the relationship between sleep and CH and highlight the need to clarify the underlying mechanism.

Objectives: Cold extremities have been suggested to correlate with sleep disturbances. This study aims to explore the relationship between thermal sensations in body, encompassing both cold and heat sensations, with sleep quality and insomnia.Methods: Self-administered questionnaires were utilized to assess thermal sensations in body, sleep quality and symptoms of insomnia in middle-aged women. A multiple logistic regression analysis was performed to ascertain the association between thermal sensations in body and both sleep quality and insomnia symptoms.Results: Among 899 participants, 255 (28.4%) were categorized in the cold sensation group, 95 (10.6%) in the heat sensation group, 70 (7.8%) in the group with both cold and heat sensations, and 479 (53.3%) in the no-sensation group. Pittsburgh Sleep Quality Index and Insomnia Severity Index were notably higher in the group experiencing both sensations when compared to the no-sensation group. After adjustments for covariates, the odds ratios for poor sleep quality, moderate/severe insomnia, and long sleep latency were significantly elevated in the group with both sensations when compared to the no-sensation group. The odds ratios for poor sleep quality in the cold sensation group and for moderate/severe insomnia and low sleep efficiency in the heat sensation group were significantly higher when compared to the no-sensation group.Conclusions: The risk for sleep disturbances varied depending on the presence of thermal sensations in body, with the greatest risk observed for low sleep quality and insomnia in individuals experiencing both cold and heat sensations.

Objectives: The aim of this study was to investigate the differences in the prevalence of metabolic syndrome (MetS) according to the Sasang constitution (SC) and cold and heat pattern identification (CHPI). Methods: SC, CHPI, MetS, and component data were obtained from 2,561 participants in 26 Korean medical clinics from 2007 to 2013. SC, diagnosed by Korean medicine doctors, was confirmed by positive responses to herbal medicines administered according to that constitution. The CHPI was verified by a questionnaire about thermal sensitivity and drinking habits. The diagnosis criteria for MetS were: 1) waist circumference (WC) ≥90 cm (male) and ≥80 cm (female); 2) triglycerides ≥150 mg/dL; 3) high density lipoprotein cholesterol (HDL) <40 mg/dL (male) and <50 mg/dL (female); 4) blood pressure ≧130/85 mmHg; and 5) fasting blood glucose ≥100 mg/dL. Odds ratios (ORs) and differences in MetS and its components were compared using logistic regression and ANCOVA. Results: The MetS prevalence rates were 54.1%, 22.0%, and 33.3% for Taeeumin (TE), Soeumin (SE), and Soyangin (SY), respectively, and 30.5% and 44.5% for the cold and heat patterns, respectively. ANCOVA for MetS components showed significantly higher WC in TE than in SE or SY, and all components except HDL were higher in the heat pattern group than in the cold pattern group. Logistic regression for MetS prevalence showed a significant association between TE and the heat pattern group (OR=1.653) but not for non-TE and the cold pattern group. Conclusions: Considering SC and CHPI together may be more effective in managing MetS than considering SC alone.

Objectives: Facial diagnosis is an important part of clinical diagnosis in traditional East Asian Medicine. In this paper, we proposed a model to quantitatively classify cold sensitivity using a fully automated facial image analysis system.Methods: We investigated cold sensitivity in 452 subjects. Cold sensitivity was determined using a questionnaire and the Cold Pattern Score (CPS) was used for analysis. Subjects with a CPS score below the first quartile (low CPS group) belonged to the cold non-sensitivity group, and subjects with a CPS score above the third quartile (high CPS group) belonged to the cold sensitivity group. After splitting the facial images into train/validation/test sets, the train and validation set were input into a convolutional neural network to learn the model, and then the classification accuracy was calculated for the test set.Results: The classification accuracy of the low CPS group and high CPS group using facial images in all subjects was 76.17%. The classification accuracy by sex was 69.91% for female and 62.86% for male. It is presumed that the deep learning model used facial color or facial shape to classify the low CPS group and the high CPS group, but it is difficult to specifically determine which feature was more important.Conclusions: The experimental results of this study showed that the low CPS group and the high CPS group can be classified with a modest level of accuracy using only facial images. There was a need to develop more advanced models to increase classification accuracy.