Objectives: The aim of this study was to investigate the usefulness of a simple dietary check sheet to assess the risk of muscle mass reduction in middle-aged and older adults.

Methods: The study participants comprised 1,272 community-dwelling individuals aged 50–89 years (mean age; 68.7 years). Bioelectrical impedance analysis was performed to estimate the appendicular skeletal muscle mass index (SMI, kg/m²). The SMIs were expressed as z-scores and adjusted for age and gender. A simple dietary check sheet was used to assess the daily intake of foods associated with maintaining muscle mass, such as meat, fish, eggs, milk, soybean products, and vegetables.

Results: Individuals with reduced muscle masses (SMI z-scores < –1.0) had significantly lower intakes of meat, fish, eggs, milk, and vegetables, and a lower overall dietary intake than individuals without reduced muscle masses (SMI z-scores ≥ –1.0). Food intake score was calculated to obtain quantitative estimates of the daily intake of these foods. The scores ranged from 0 to 14, with higher scores indicating higher intakes of foods that contribute to maintaining the muscle mass. Compared with the reference group with scores of ≥ 10, the groups with lower scores were at a higher risk of muscle mass reduction. The odds ratios (95% confidence interval) of the groups with scores of 9, 8, 7, 6, and ≤ 5 were 1.15 (0.42–3.13), 2.10 (0.89–4.95), 3.64 (1.61–8.23), 4.49 (1.90–10.58), and 7.53 (3.06–18.51), respectively, after adjusting for age, gender, obesity, alcohol intake, smoking, physical inactivity, hypertriglyceridemia, diabetes mellitus, and liver dysfunction.

Conclusions: As the food intake scores were significantly associated with decreased muscle mass, the proposed simple dietary check sheet may help assess the risk of muscle mass reduction in middle-aged and older adults from a nutritional perspective.

Objectives: In this study, we aimed to develop a risk prediction model and a simple assessment sheet for cold disorder (hiesho) in middle-aged and older adults.

Methods: The 889 participants in this study were from a community-dwelling general population (mean age, 62.4±8.8 years). The skin surface temperatures of the face and hands of the participants were measured by thermography. The cold disorder was objectively defined as having a temperature difference of ≥8°C between the forehead and fingertips. Data on the body regions with cold perception and the various concomitant signs were collected by a self-administered questionnaire and structured interviews.

Results: The objectively assessed cold disorder was observed in 22.7% of participants and strongly associated with coldness of the back of the hand, palms, fingers, dorsal torso, toes, and soles of the feet. Its prevalence was found to increase with the number of signs of coldness. Older age, being female, low body mass index, hypertension, anemia, and physical inactivity were identified as potential risk factors. A logistic model for predicting the cold disorder was designed on the basis of the perceived cold, accompanying signs, and risk factors. The model showed good discrimination (area under the curve=0.737) and calibration capabilities (Hosmer–Lemeshow test, P=0.426). On the basis of this prediction model, a simple assessment sheet was developed to estimate the individual risk of experiencing the cold disorder, in middle-aged and older adults.

Conclusions: With the proposed risk prediction model showing good discrimination capability, the assessment sheet may serve as a prescreening tool to evaluate the potential of middle-aged and older population to develop the cold disorder.

Objectives: In this study, we aimed to clarify the factors associated with breastfeeding at one month postpartum, with focusing on midwives’ nursing guidance and mothers’ breastfeeding behavior.

Methods: A total of 158 mothers who participated in a medical examination two weeks after delivery were followed up with a questionnaire at two weeks and one month postpartum. Furthermore, we conducted multiple logistic regression analyses with breastfeeding at the one-month health checkup as the dependent variable and breastfeeding guidance and mothers’ breastfeeding behavior as independent variables adjusted for birth history and delivery method, which were the confounding factors.

Results: For nursing guidance, we examined 149 individuals without missing data. In total, 71 (47.7%) mothers were found to be breastfeeding at one month postpartum. Breastfeeding probabilities were significantly higher in mothers who received guidance regarding the meaning of their infants’ crying, changes in breast tension, breast care, and mothers’ milk production, which were measured, with odds ratios ranging from 2.47 to 3.68. Breastfeeding odds ratios were significantly higher in mothers who inserted the nipple deeply into the baby’s mouth such that the baby’s lips spread outward, as well as in those who breastfed until the breast felt light and those who breastfed eight times a day than in mothers who did not, with odds ratios ranging from 2.27 to 5.86.

Conclusion: This study indicated that early postpartum support, including guidance regarding the meaning of infants’ crying, changes in breast tension, breast care, lactation measurement, and proper breastfeeding methods, is crucial in establishing breastfeeding.

Objectives: The benefit of using a noncontact eye-tracking system is its low a burden on individuals for measuring biological signals. The goal of this study was to develop a visually induced motion sickness (VIMS) evaluation index using data collected with a noncontact eye-tracking system for driving simulator (DS) experiments.

Methods: The participants included nine elderly people with visual and balance functions that did not interfere with their daily life. The gaze data of the participants were measured at rest—both before and after DS trials. The participants answered followed up the simulator sickness questionnaire (SSQ) before and after each trial. The participants were divided into two groups on the basis of their SSQ results. One group experienced VIMS during the DS trial (four people; average age, 79.0 years), whereas the other group did not experience it (five people; average age, 71.2 years).

Results: The results of VIMS symptoms were confirmed: data concerning the locus of eye-tracking were lengthened, the eye-tracking data were diffused. This experiment demonstrated the usefulness of sparse density as a quantification index based on eye-tracking data in the evaluation of VIMS.

Conclusions: Regarding the application of the findings of this study, it is believed that it will be easier to detect VIMS symptoms induced by DS operations if the index can be used for an eye-tracking data-based evaluation of VIMS.

In this article, we present the following: a background of visually induced motion sickness (VIMS), the goal of our study, and descriptions of three recent studies conducted by our group on the measurement and analysis of eye movement while viewing movies and the relationship of eye movement with VIMS. First, this study focuses on the relationship between eye movement and motion sickness susceptibility. We investigated the relationship between the motion sickness susceptibility and the frequency of optokinetic nystagmus (OKN) with peripheral viewing. It was revealed that susceptible participants showed a lower OKN frequency under conditions that strongly support the occurrence of OKN than insusceptible participants. Second, this study focuses on the relationship between visual information and postural variation such as visually evoked postural responses (VEPRs). In this study, both eye movement and the center of gravity while viewing a movie were measured. Additionally, we evaluated the difference in the transfer gain of the transfer function (vision as input and equilibrium function as output) due to the type of movie content or way of viewing. The gain for the three-dimensional movie with peripheral viewing exceeded that for the two-dimensional movie with central viewing. Third, this study focuses on eye movement and the application of deep-learning technology. In this study, we classified the eye movement as peripheral or central using a convolutional deep neural network with supervised learning. Then, cross validation was performed to test the classification accuracy. The use of >1-s eye movement data yielded an accuracy of >90%.

Objectives: These days, developments in graphical technology have resulted in an increase in the chance to view 3D video clips. Visually induced motion sickness (VIMS) has been widely reported as a negative result of viewing these clips. The onset of VIMS is explained by some hypotheses. However, the root causes of VIMS have not been elucidated yet, whereas dizziness and nausea are regarded as symptoms of VIMS. In this study, we focus on the difference in the pattern of body sway among age groups and examine whether the consistency between the background and the viewpoint motion depends on the severity of VIMS.

Methods: This experiment was conducted with 116 subjects aged 15–89 years. They peripherally viewed a 3D video clip showing a sphere whose motion was consistent with their viewpoint (VC-I) and another 3D video clip of a sphere whose motion was inconsistent with their viewpoint (VC-II). Statokinesigrams (SKGs) were recorded with their eyes open and with their eyes closed for 60 s. The amount of sway was calculated from the SKGs.

Results: Results showed that for all age groups, sway values were significantly higher when viewing the 3D video clip (VC-II) than in the Pre. However, for the elderly, there was no significant difference between the sway values while viewing the VC-I and those in the Pre.

Conclusions: Results suggest that VIMS might not occur in the elderly because of the deterioration of their visual function, such as visual acuity and accommodation, with advancing age.

Objectives: Olfactory stimulation elicits various physiological responses. However, few reports exist on the changes in gastric motility during olfactory stimulation in humans. In this regard, we carried out electrogastrography (EGG) to non-invasively measure the gastric myoelectrical activity, which regulates gastric motility. Moreover, subjective sensory evaluation was performed to determine which characteristics of vanilla odor at two different concentrations affect the myoelectrical activity.

Methods: The participants consisted of eight healthy young males. EGG and electrocardiography (ECG) recordings were obtained approximately 20 min prior to and during olfactory stimulation. Autonomic nervous system activity was evaluated in terms of heart rate variability (HRV) and mean heart rate (HR) from ECG signals. EGG signals were analyzed by spectral analysis. In addition, the translation error was estimated by the Wayland algorithm. Sensory evaluation was performed using the Visual Analog Scale (VAS).

Results: There were no significant differences in HRV and HR values and results of spectral analyses of EGG signals in all sample presentations. The translation error of EGG signals and the rating of perceived odor intensity significantly increased in a concentration-dependent manner. There was a strong positive correlation between translation error and odor intensity.

Conclusions: The correlation found between translation error and odor intensity suggests that the higher the vanilla odor intensity was perceived, the greater the randomness of EGG signals was. Our results suggest that the application of the Wayland algorithm to EGG signals can be used as an objective indicator in odor evaluation.

Objective: The confirmation of abnormal behavior during video monitoring in polysomnography (PSG) and the frequency of rapid eye movement (REM) sleep without atonia (RWA) during REM sleep based on physiological indicators are essential diagnostic criteria for the diagnosis of REM sleep behavior disorder (RBD). However, no clear criteria have been established for the determination of the tonic and phasic activities of RWA. In this study, we investigated an RWA decision program that simulates visual inspection by clinical laboratory technicians.

Methods: We used the measurement data of 25 men and women (average age±standard deviation: 72.7±1.7 years) who visited the Sleep Treatment Center for PSG inspection due to suspected RBD. The chin electromyography (EMG) during REM sleep was divided into 30 s intervals, and RWA decisions were made on the basis of visual inspection by a clinical laboratory technician. We compared and investigated two machine-learning methods namely support vector machine (SVM) and convolutional neural network (CNN) for RWA decisions.

Results: When comparing SVM and CNN, the highest discrimination accuracy for RWA decisions was obtained when using the average rectified value (ARV) processed chin EMG images using CNN as a feature. We also estimated the prevalence of RBD on the basis of the Mahalanobis distance measure using the frequency of occurrence of both tonic and phasic activities calculated from a total of 25 subjects in the patient and healthy groups. Consequently, estimation of RBD prevalence using CNN resulted in misclassification of none of the subjects in the patient group and two subjects in the healthy group.

Conclusions: In this study, we investigated the automatic analysis of PSG results focusing on RBD, which is a parasomnia. As a result, there were no misclassifications of patients in the 25 subjects in the patient or healthy groups based on the estimates of RBD prevalence using CNN. The prevalence estimation based on our proposed automated algorithm is considered effective for the primary screening for RBD.