Noncontact Evaluation Method for Autonomic Nervous System Activity during Exercise Using RGB Camera.

For efficient exercise, motor functions, heart rate, oxygen uptake (which are controlled by autonomic nervous system activity), heat acclimation-related functions, such as sweating, and thermoregulation must work properly during exercise. In this research, a noncontact method of measuring capillary contraction and dilation, one of the autonomic nervous system activities, using only a commercial web camera was developed. The absorption rate by haemoglobin in blood differs for each wavelength of light. When the capillaries in the face contract or dilate, the colour component of the light reflected from the face changes. The focus of this study was on the changes in the green and blue values of the face image. Green light reaches the dermis, where capillaries are located, while blue light reaches only the epidermis. The G/B ratio, the green value divided by the blue value, shows the changes in capillary contraction and dilation. An experiment was conducted to validate the G/B ratio method. Ten subjects (23 ± 1.6 years of age) participated in the experiment, and face movement and heart rate were measured during an aerobic bike exercise test. The results showed that, when the heart rate increased, the G/B ratio decreased immediately after the start of exercise. After the exercise stopped, the heart rate decreased immediately, and the G/B ratio increased. The G/B ratio revealed that the sympathetic nervous system became dominant during exercise, causing facial capillaries to dilate, and that the parasympathetic nervous system became dominant after exercise, causing facial capillaries to constrict.

Menstruation-related symptoms are associated with physical activity and midpoint of sleep: a pilot study.

Introduction: Menstruation-related symptoms (MRSs) significantly impact women's health and contribute to economic burdens worldwide. Current interventions, primarily pharmacological ones, have limitations and side effects that underscore the need for alternative management strategies. This study explores the association between MRSs and lifestyle factors, specifically physical activity and sleep timing across menstrual cycle phases, to inform non-pharmacological intervention development. Methods: Fourteen female students from Ritsumeikan University, Japan, with regular menstrual cycles (25-38 days), not on hormonal treatment or engaged in shift work, participated in this observational study. Using a Fitbit Inspire 2, total daily energy expenditure (TDEE) and sleep timing were monitored over a complete cycle. Menstrual cycle phases were defined based on ovulation day, predicted using home luteinizing hormone tests. Participants completed daily electronic questionnaires rating MRSs using a modified menstrual distress questionnaire. Data were analyzed using a generalized linear mixed model with a gamma distribution and logarithmic link function, examining the relationship of TDEE and the midpoint of sleep time (MS time) with MRS severity. Results and discussion: The following observations were noted: first, MRS severity, except for behavioral change symptoms, significantly increased during the menstrual and luteal phases compared to the follicular phase. Second, delayed MS time was associated with reduced pain, concentration symptoms, water retention, and negative affect during the menstrual phase and reduced negative affect during the luteal phase. Finally, an increase in TDEE was associated with reduced concentration symptoms, autonomic reaction symptoms, and negative affect during the menstrual and luteal phases and reduced water retention only during the luteal phase. This study provides insights into the relationship between MRSs and TDEE/MS time, suggesting potential non-therapeutic approaches for symptom management, though further research is needed to substantiate these findings for practical applications.

Bending Angle Sensor Based on Double-Layer Capacitance Suitable for Human Joint.

Goal: To develop bending angle sensors based on double-layer capacitance for monitoring joint angles during cycling exercises. Methods: We develop a bending angle sensor based on double-layer capacitive and conducted three stretching, bending, and cycling tests to evaluate its validity. Results: We demonstrate that the bending angle sensor based on double-layer capacitance minimizes the change in the capacitance difference in the stretching test. The hysteresis and root mean square error (RMSE) compared with the optical motion capture show hysteresis: 8.0% RMSE and 3.1° in the bending test. Moreover, a cycling experiment for human joint angle measurements confirm the changes in accuracy. The RMSEs ranged from 4.7° to 7.0°, even when a human wears leggings fixed with the developed bending-angle sensor in the cycling test. Conclusion: The developed bending angle sensor provides a practical application of the quantitative and observational evaluation tool for knee joint angles.

Development of a non-contact sleep monitoring system for children.

Daily monitoring is important, even for healthy children, because sleep plays a critical role in their development and growth. Polysomnography is necessary for sleep monitoring. However, measuring sleep requires specialized equipment and knowledge and is difficult to do at home. In recent years, smartwatches and other devices have been developed to easily measure sleep. However, they cannot measure children's sleep, and contact devices may disturb their sleep. A non-contact method of measuring sleep is the use of video during sleep. This is most suitable for the daily monitoring of children's sleep, as it is simple and inexpensive. However, the algorithms have been developed only based on adult sleep, whereas children's sleep is known to differ considerably from that of adults. For this reason, we conducted a non-contact estimation of sleep stages for children using video. The participants were children between the ages of 0-6 years old. We estimated the four stages of sleep using the body movement information calculated from the videos recorded. Six parameters were calculated from body movement information. As children's sleep is known to change significantly as they grow, estimation was divided into two groups (0-2 and 3-6 years). The results show average estimation accuracies of 46.7 ± 6.6 and 49.0 ± 4.8% and kappa coefficients of 0.24 ± 0.11 and 0.28 ± 0.06 in the age groups of 0-2 and 3-6 years, respectively. This performance is comparable to or better than that reported in previous adult studies.

Postural sway reduction by weak electrical noise into the wrist median nerve using portable stimulator.

Stochastic resonance (SR) is a weak noise stimulation that improves the function of standing balance by increasing sensitivity to somatosensory information. SR implemented in the lower limbs may increase the standing balance function, but the effect of noise stimulation on upper limbs has not been investigated to date. This study aims to investigate the effect of weak electrical noise stimulation of the median nerve at the wrist on the balance control system function using a portable stimulator. Ten healthy individuals participated in the study. Each subject maintained quiet standing with their eyes closed for 40 s while receiving white noise electrical stimulation to the median nerve at the wrist. Center of pressure (COP) displacement and change in the joint position (left and right waist) were measured and compared between a no-stimulus trial (control trial) and a stimulus intensity trial that maximized the effect of SR (optimal trial). Experimental results show that weak electrical noise stimulation of the median nerve at the wrist stabilized the COP and joint position. The anteroposterior (AP) standard deviation of the optimal trial were significantly reduced compared to the control trial in terms of COP and left and right waist, and AP low-frequency range power of the optimal trial were significantly reduced compared to the control trial in terms of COP and left waist. AP mean velocity and AP high-frequency range power at the left waist were significantly reduced in the optimal trial. It was concluded that weak electrical noise stimulation applied to the median nerve can reduce static postural sway.

Effects of subthreshold electrical stimulation with white noise, pink noise, and chaotic signals on postural control during quiet standing.

BACKGROUND: The stochastic resonance (SR) phenomenon has been used to improve postural control through the application of imperceptible noise to the somatosensory system. White noise signals have been applied in numerous SR studies on postural control. However, because the SR effect depends on the noise structure, the stimulation effects of signals with different structures, such as pink noise and chaotic signals, on postural control, must be determined to achieve better clinical applications of SR technology. RESEARCH QUESTION: During quiet standing, how is postural control affected by subthreshold electrical stimulation to the knee joints when signals with different structures (white noise, pink noise, and chaotic signals) are used? METHODS: Sixteen healthy young adults stood quietly for 40 s with their eyes closed. To evaluate postural sway, we calculated the mean velocity, root mean square (CoPRMS), and range (CoPRange) values for the center of pressure (CoP) in the anteroposterior direction. The standing task was conducted under subthreshold electrical stimulation with white noise, pink noise, and chaotic signals based on the Lorenz system, in addition to the no-stimulation condition. The four stimulation conditions were randomized within each set and repeated seven times. RESULTS: Significant effects of stimulation were observed in the CoPRMS and CoPRange values. The CoPRMS value under the pink noise signal was significantly lower than that under the no-stimulation condition. The CoPRange value also tended to decrease under the pink noise signal compared with the no-stimulation condition; however, the differences were not statistically significant. No significant changes were found with the white noise and chaotic signals compared with the no-stimulation condition. SIGNIFICANCE: We demonstrated that the pink noise signal was more effective in reducing postural sway than the white noise and chaotic signals based on the Lorenz system during quiet standing.

Convolutional neural network-based computer-aided diagnosis in Hiesho (cold sensation).

Hiesho (cold sensation) is a worldwide health problem primarily occurring in women. Females who suffered from Hiesho reported cold feeling at the extremities, which was also related to other chronic diseases. However, the diagnosis of Hiesho is still controversial because it depends on subjective approaches such as questionnaires. Quantitative and automatic Hiesho diagnosis is expected to increase diagnostic accuracy and lower the burden on patients and doctors. Following our previous study, which found that the temperature difference between females' foreheads and plantar soles was significant in Hiesho patients, it was considered that training a convolutional neural network (CNN) with thermographic images can contribute to a computer-aided diagnosis (CAD) for Hiesho. Thus, this study proposes a CNN-based Hiesho CAD system. A total of 5612 thermographic images from 46 subjects (23 Hiesho patients and 23 healthy subjects) were used to train AlexNet, and the performance of the proposed CNN model was evaluated and compared with other machine learning-based models using accuracy, precision, sensitivity, specificity, and F1 score. The experimental results showed that the proposed CNN-based Hiesho CAD model had the highest performance (100%) for all evaluated items. In addition, it was concluded that thermographic images showed high feasibility for discriminating Hiesho, and CNN-based CAD showed high accuracy and reliability for automatic Hiesho diagnosis.

Movement Coordination during Forward and Backward Rope Jumping: A Relative Phase Study.

Rope jumping is a popular training method in athletic programs, fitness, and physical education. Forward and backward rope jumping has been used for evaluating athlete's performance. Both of these two jumps require coordination in the upper and lower limbs. However, no study has focused on movement coordination during forward and backward rope jumping. Relative phase (RP) analysis was widely known as an innovative method for evaluating human movement coordination. Thus we aimed to investigate the movement coordination during forward and backward rope jumping by using RP analysis. 78 elementary and junior high school students participated in this study. 30 seconds rope jumping was recorded for both forward and backward by using iPhone video. Pose estimation software was used for jump motion tacking. Movement coordination was analyzed through RP analysis, absolute maximum value, mean absolute RP, and deviation phase were calculated for evaluating movement coordination, the trend of in or out-of-phase, as well as movement stability. As a result, 3994 forward and 3961 backward jumps were analyzed. There was a significant difference in movement coordination between forward and backward rope jumping. Compared to forward, backward jumps showed worse movement coordination, a trend to be out-of-phase, and less stability. It was the first time that movement coordination during rope jumping was studied. We considered that further research on coordination during rope jumping can provide new insight into athlete performance management, fitness guidance, and physical education.

Design and Evaluation of an Online Squat Fitness System: Lessons Learned During the Early COVID-19 Pandemic in Japan.

COVID-19 has changed our lives and limited our ability to have adequate physical activity (PA). It is necessary to replace outdoor PA with home-based fitness. However, people lack access, skills, and even motivation for home-based fitness. To address these issues, we designed a free access self-monitoring and coaching and music-based interactive online squat fitness system. Body weight squat was utilized for fitness exercise and evaluated based on three indices: knee width, hip depth, and rhythm. An online survey on changes in exercise due to the COVID-19 pandemic and exercise habits was conducted to investigate the effect of the COVID-19 pandemic on PA. We collected data from 557 respondents 5 months after the system first released and analyzed 200 visitors' performance on squat exercise and the other relevant parameters. Visitors were divided into three groups according to their age: younger, middle, and older groups. Results showed that the younger group had better squat performance than the middle and older groups in terms of hip depth and rhythm. We highlighted the lessons learned about the system design, fitness performance evaluation, and social aspects, for future study of the design and development of similar home-based fitness systems. We provided first-hand results on the relation between the COVID-19 pandemic and physical exercise among different age groups in Japan, which was valuable for policy making in the post-COVID-19 era.

Estimating Sleep Stages Using a Head Acceleration Sensor.

Sleep disruption from causes, such as changes in lifestyle, stress from aging, family issues, or life pressures are a growing phenomenon that can lead to serious health problems. As such, sleep disorders need to be identified and addressed early on. In recent years, studies have investigated sleep patterns through body movement information collected by wristwatch-type devices or cameras. However, these methods capture only the individual's awake and sleep states and lack sufficient information to identify specific sleep stages. The aim of this study was to use a 3-axis accelerometer attached to an individual's head to capture information that can identify three specific sleep stages: rapid eye movement (REM) sleep, light sleep, and deep sleep. These stages are measured by heart rate features captured by a ballistocardiogram and body movement. The sleep experiment was conducted for two nights among eight healthy adult men. According to the leave-one-out cross-validation results, the F-scores were: awake 76.6%, REM sleep 52.7%, light sleep 78.2%, and deep sleep 67.8%. The accuracy was 74.6% for the four estimates. This proposed measurement system was able to estimate the sleep stages with high accuracy simply by using the acceleration in the individual's head.

The Estimation of Circadian Rhythm Using Smart Wear.

In this study, we have developed a new practical system for estimating circadian rhythm by using smart wear that can measure electrocardiogram (ECG) during sleep. This system can estimate the time and heart rate (HR) value to reach the lowest point in circadian rhythm. We show the system in detail. And for further application, we conducted the experiment for showing the effects of jet lag on the circadian rhythm by using the developed system. The results showed that the time of the lowest HR shifted earlier and the lowest HR was higher in case of traveling in a westward direction.

Sleep stage estimation method using a camera for home use.

Recent studies have developed simple techniques for monitoring and assessing sleep. However, several issues remain to be solved for example high-cost sensor and algorithm as a home-use device. In this study, we aimed to develop an inexpensive and simple sleep monitoring system using a camera and video processing. Polysomnography (PSG) recordings were performed in six subjects for four consecutive nights. Subjects' body movements were simultaneously recorded by the web camera. Body movement was extracted by video processing from the video data and five parameters were calculated for machine learning. Four sleep stages (WAKE, LIGHT, DEEP and REM) were estimated by applying these five parameters to a support vector machine. The overall estimation accuracy was 70.3 ± 11.3% with the highest accuracy for DEEP (82.8 ± 4.7%) and the lowest for LIGHT (53.0 ± 4.0%) compared with correct sleep stages manually scored on PSG data by a sleep technician. Estimation accuracy for REM sleep was 68.0 ± 6.8%. The kappa was 0.19 ± 0.04 for all subjects. The present non-contact sleep monitoring system showed sufficient accuracy in sleep stage estimation with REM sleep detection being accomplished. Low-cost computing power of this system can be advantageous for mobile application and modularization into home-device.

Development of wearable muscle fatigue detection system using capacitance coupling electrodes.

Bio-information is important to confirm the body condition. Especially, the muscle fatigue is related to injury or decrease of concentration. Therefore, it is required to evaluate muscle fatigue to make subject enjoy sports. In previous study, muscle fatigue is evaluated by using electromyogram (EMG). However, the electrode for EMG measurement is generally used for contact manor. The electrodes are disposable and it might cause the irritation of skin. Therefore, it isn't fitted for measurement of muscle fatigue. We developed wearable muscle fatigue detection system using capacitance coupling electrodes. Developed system isn't caused the irritation by electrodes and can reuse it. We compared the conventional system using disposable electrode system and our system to evaluate performance. We evaluated muscle fatigue from electromyogram before and after futsal. An integrated electromyogram and an intermediate frequency were used for the evaluation of muscle fatigue. As a result, half of subjects showed tendency of muscle fatigue. Therefore, we showed the possibility as muscle fatigue detection system using the capacity coupling electrodes.

Analysis of Difference in Center-of-Pressure Positions Between Experts and Novices During Asymmetric Lifting.

Although numerous studies have analyzed the relationship between manual material handling (MMH) and the forces acting on the lumbar spine, the difference in the MMH between experts and novices through the analysis of measured data has not been well studied. The purpose of this paper was to analyze the difference in the MMH positions between ten skilled experts working at a freight transport company (Group 1) and five unskilled novices without any experience (Group 2) during asymmetric lifting. All the human subjects performed asymmetric lifting experiments with closed eyes; the experiments involved moving loads (6 and 18 kg) to the left side. Time series data of the vertical ground reaction force were measured, using a Wii Balance Board, and then, the center-of-pressure (CoP) trajectories were calculated. The balance board was used for the measurement, because it was reliable, inexpensive, and portable and provided good repeatability even on rough surfaces, and all the information pertaining to the load and worker under various conditions was captured without any omissions. Under the 18 kg load condition, the CoP positions for Group 2 were located on the same side during left asymmetric lifting; however, those for Group 1 were located on the opposite side during left asymmetric lifting ([Formula: see text]). Furthermore, under the 6 kg load condition, the load weight influenced asymmetric lifting for most subjects of Group 2 such that the CoP positions were located on the opposite side ([Formula: see text]). Based on the simulation and electromyography measurement results, we inferred that the difference in the CoP positions between the two different groups could be attributed to the difference in the hip positions. Most skilled experts position their hips in such a way that their CoP trajectories move toward the opposite side during left asymmetric lifting. Although the skillful characteristics of experts may be responsible for the lightening of the burden on the waist during asymmetric lifting, there are still two points that this paper does not clarify: the relationship between the experts' adjustment of the hip position and the load of the weight, and the influence of an imbalance of the CoP position on the forces acting on the lumbar spine.

Classification of forearm and finger motions using electromyogram and arm-shape-changes.

Robot arms for humanoid are widely developed for medical, welfare and education use. Surface electromyogram (sEMG) signals which are the electrical signals obtained from surface of human skin using electrodes have been mainly used for classification of hand motions. However, it is difficult to classify detailed motions such as finger motions and wrist pronation or supination. Moreover, Kinect is an integration sensor device which can capture human joints movement. It also has been widely used for recognition of body motions in many fields. However, it has some problems such as setting of camera and restriction of detection range. In this study, we propose an advanced method of motion classification by combining arm-shape-changes with sEMG to classify the detailed motions. Arm-shape-changes are forearm deformation caused by a bulge of muscle when subjects move an arm or a finger. Experimental results showed classification accuracies of 90% or more in wrist pronation and supination which are difficult to classify using only sEMG signals. As the result, our method could classify the detailed motions and contribute to expansion of classifiable hand motions.

Measurement of swallowing using flexible polymer sensor.

We proposed a new method to measure swallowing in this study. A flexible polymer sensor was used to measure human swallowing. Electromyogram (EMG) of suprahyoid muscles were measured as a reference of swallowing. We also developed a measurement system for the flexible polymer sensor, which consists of two measurement circuits; the 1(st) one measures the voltage of flexible polymer sensor, and the 2(nd) one EMG of suprahyoid muscles. We conducted measurement experiments focused on human swallowing to confirm the ability of this sensor. At the experiment one subject was asked to sit in three different postures and to drink a cup of water. Results show that human swallowing can be detected by this flexible polymer sensor.

Body movement analysis during sleep for children with ADHD using video image processing.

In recent years, the amount of children with sleep disorders that cause arousal during sleep or light sleep is increasing. Attention-deficit hyperactivity disorder (ADHD) is a cause of this sleep disorder; children with ADHD have frequent body movement during sleep. Therefore, we investigated the body movement during sleep of children with and without ADHD using video imaging. We analysed large gross body movements (GM) that occur and obtained the GM rate and the rest duration. There were differences between the body movements of children with ADHD and normally developed children. The children with ADHD moved frequently, so their rest duration was shorter than that of the normally developed children. Additionally, the rate of gross body movement indicated a significant difference in REM sleep (p < 0.05). In the future, we will develop a new device that can easily diagnose children with ADHD, using video image processing.

Examination of non-restrictive and non-invasive sleep evaluation technique for children using difference images.

In recent years, the inappropriate sleep style for children has become known as one of the important causes of behavioral disorders, for example inattentiveness during waking hours or hyperactivity. Consequently, screening for the children having sleep disorders is needed to treat in the early stage of the behavioral disorders. From the point of view of evaluation for children's sleep, there are three problems. First, the conventional polysomnogram (PSG) requires great investment in facility and high personnel cost so that hospitals equipped with the PSG examination are rare. Next, the sleep-check examination system such as PSG and so on requires many sensors to be attached to the client's face and body. So the client feels suffering severe stress and the wires of sensors trigger some accidents. At last, it is very difficult to get ordinary sleep style in the sleep examination room because of above factors. It is strongly desirable to develop a new method of sleep evaluation system in place of conventional PSG that is non-restrictive and non-contact. Taking these problems into account, we devised a technique with these characteristics that is completely separated from sensors. It determines the sleep condition from body movement information by measuring movements using difference processing of video image. Our study of using this technique on pediatric patients indicated that this non-restrictive technique could be effective for evaluating body movement during sleep. It was looked for a relationship between movements information and sleep conditions.

Proposal for a method of non-restrictive measurement of resting heart rate in a lying position.

Daily monitoring of heart rates is important in health management. Many researchers have analysed heart rate variability by using the resting heart rate because such an analysis can facilitate the early discovery of a variety of illnesses and health conditions. Some problems that arise in measuring heart rate are the feeling of confinement. Therefore, we required a system that could measure the resting heart rate in a static position in such a way that the subject is completely unaware that the measurement is being recorded. We propose a non-restrictive measurement method that uses only an acceleration sensor placed inside a down quilt. This method is easy for home use. The acceleration sensor was placed inside the quilt such that it was positioned opposite to the left-hand side of the subject's chest. Six healthy subjects were requested to lie in the supine position and were covered with the quilt equipped with the acceleration sensor. Mechanical vibrations that resulted from heart activity were carried through the quilt to the acceleration sensor. As a result, periodic vibrations were measured successfully, and in the six subjects, these vibrations were proved to be highly correlated with the R wave of electrocardiograms. The same results were obtained even when the subjects were lying in the left lateral position. The results indicated that our new method, which used an acceleration sensor placed inside a down quilt, was simple and could be used to measure the resting heart rate in a lying position.

Non-restrictive heart rate monitoring using an acceleration sensor.

Daily long-term monitoring of heart rates is important for health management. An analysis of heart rate variability can facilitate the early discovery of illnesses. In this study, we paid attention to the method of measuring resting heart rate over long term. An acceleration sensor was set inside the down kilt as it opposing to subject's left chest. Mechanical vibration from heart activity is carried to the acceleration sensor through the down quilt. As a result, periodic vibration was measured successfully and this vibration was proved to be in high correlation with the R wave of ECG. The same results were obtained even in case of lying in a left lateral position.