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Background Spinal alignment evaluation is commonly performed in the clinical setting during rehabilitation. However, there is no simple method for its quantitative measurement. Recently, the depth cameras in Kinect sensors have been employed in various commercial and research projects in the healthcare field. We hypothesized that the time-of-flight technology of the Kinect sensor could be applied to quantitatively evaluate spinal alignment. The purpose of this study was to develop a simple and noninvasive evaluation for spinal alignment using the Kinect sensor and to investigate its validity. Methods Twenty-four healthy men participated in the study. Measurement outcomes were the thoracic kyphosis and lumbar lordosis angles in the standing position, using a Spinal Mouse, the validity of which has been previously reported, and the Kinect sensor. In the measurement by the Kinect sensor, a program was created to obtain the three-dimensional coordinates of each point within an area marked on the monitor, and the sums of the angles at each vertebral level were calculated for the thoracic and lumbar areas. Pearson's correlation coefficient was used to analyze the relationship between the Kinect sensor and Spinal Mouse measurements of thoracic kyphosis and lumbar lordosis angles. Results There was a significant positive and moderate correlation between the thoracic kyphosis measurements taken by each device. Contrarily, there was no significant correlation in the lordosis angle between measurements using the Kinect sensor and Spinal Mouse. Conclusions Our results demonstrated the validity of measuring the thoracic kyphosis angle using the Kinect sensor. This indicates that the depth camera in the Kinect sensor is able to perform accurate thoracic alignment measurements quickly and noninvasively.

In recent years, the number of bedridden patients, including amyotrophic lateral sclerosis (ALS) patients, has been increasing with the aging of the population, owing to advances in medical and long-term care technology. Eye movements are physical functions that are relatively difficult to be affected, even if the symptoms of ALS progress. Focusing on this point, in this paper, in order to improve the quality of life (QOL) of bedridden patients, including ALS patients, we propose a drone system connected to the Internet that can be remotely controlled using only their eyes. In order to control the drone by using only their eyes, a control screen and an eye-tracking device were used in this system. By using this system, for example, the patients in New York can operate the drone in Kyoto using only their eyes, enjoy the scenery, and talk with people in Kyoto. In this drone system, since a time delay could occur depending on the Internet usage environment, agile operation is required for remotely controlling the drone. Therefore, we introduce the design of the control screen focused on remote control operability and human eye movements (microsaccades). Furthermore, considering the widespread future use of this system, it is desirable to use a commercial drone. Accordingly, we describe the design of a joystick control device to physically control the joysticks of various drone controllers. Finally, we present experimental results to verify the effectiveness of this system, including the control screen and the joystick control device.

Background/Objectives: Posture is a significant indicator of health status in older adults. This study aimed to develop an automatic posture assessment tool based on sagittal photographs by validating recognition models using convolutional neural networks. Methods: A total of 9140 images were collected with data augmentation, and each image was labeled as either Ideal or Non-Ideal posture by physical therapists. The hidden and output layers of the models remained unchanged, while the loss function and optimizer were varied to construct four different model configurations: mean squared error and Adam (MSE & Adam), mean squared error and stochastic gradient descent (MSE & SGD), binary cross-entropy and Adam (BCE & Adam), and binary cross-entropy and stochastic gradient descent (BCE & SGD). Results: All four models demonstrated an improved accuracy in both the training and validation phases. However, the two BCE models exhibited divergence in validation loss, suggesting overfitting. Conversely, the two MSE models showed stability during learning. Therefore, we focused on the MSE models and evaluated their reliability using sensitivity, specificity, and Prevalence-Adjusted Bias-Adjusted Kappa (PABAK) based on the model’s output and correct label. Sensitivity and specificity were 85% and 84% for MSE & Adam and 67% and 77% for MSE & SGD, respectively. Moreover, PABAK values for agreement with the correct label were 0.69 and 0.43 for MSE & Adam and MSE & SGD, respectively. Conclusions: Our findings indicate that the MSE & Adam model, in particular, can serve as a useful tool for screening inspections.

In recent years, Japan has experienced numerous natural disasters, such as typhoons and earthquakes. Teleoperated ground robots (including construction equipment) are effective tools for restoration work at disaster sites and other locations that are dangerous and inaccessible to humans. Using visual information obtained from various viewpoints by a drone can allow for more effective remote control of a teleoperated ground robot, making it easier for the robot to perform a task. We previously proposed and developed a remote-controlled drone system using only human eyes. However, the effectiveness of using this drone system during the remote control of a robot has never been verified. In this paper, as the first step in verifying the effectiveness of the remote-controlled drone system using only the eyes when remote-controlling a robot, we consider its effectiveness in a simple task based on the task times, subjects’ eye fatigue, and subjective evaluations of subjects. First, the previously proposed drone system is briefly described. Next, we describe an experiment in which a drone was controlled by the eyes using the drone system while a robot was controlled by hand, and an experiment in which both the drone and robot were controlled by hand without using the drone system. Based on the experimental results, we evaluate the effectiveness of the remote-controlled drone system using only the eyes when remote-controlling a robot.

Postural assessment is one of the indicators of health status in older adults. Since the number of older adults is on the rise, it is essential to assess simpler methods and automated ones in the future. Therefore, we focused on a visual method (imaging method). The purpose of this study is to determine the degree of agreement between the imaging method and the palpation and visual methods (clinical method). In addition, the influence of differences in the information content of the sagittal plane images on the assessment was also investigated. In this experiment, 28 sagittal photographs of older adults whose posture had already been assessed using the clinical method were used. Furthermore, based on these photographs, 28 gray and silhouette images (G and S images) were generated, respectively. The G and S images were assessed by 28 physical therapists (PTs) using the imaging method. The assessment was based on the Kendall classification, with one of four categories selected for each image: ideal, kyphosis lordosis, sway back, and flat back. Cross-tabulation matrices of the assessments using the clinical method and imaging method were created. In this table, four categories and two categories of ideal and non-ideal (KL, SB, and FB) were created. The agreement was evaluated using the prevalence-adjusted bias-adjusted kappa (PABAK). In addition, sensitivity and specificity were calculated to confirm the reliability. When comparing the clinical and imaging methods in the four posture categories, the PABAK values were −0.14 and −0.29 for the S and G images, respectively. In the case of the two categories, the PABAK values were 0.57 and 0.5 for the S and G images, respectively. The sensitivity and specificity were 86% and 57% for the S images and 76% and 71% for the G images, respectively. The four categories show that the imaging method is difficult to assess regardless of the image processing. However, in the case of the two categories, the same assessment of the clinical method applied to the imaging method for both the S and G images. Therefore, no differences in image processing were observed, suggesting that PTs can identify posture using the visual method.

The purpose of this study was to devise a tilt sensation measurement method to evaluate ankle proprioception and to examine its reliability. It was also used to determine the relationship among tilt sensation abilities, physical development, and lower limb injuries in junior athletes. In this study, a step platform created tilt angles. Participants with eye masks answered “yes” or “no” to sensing a tilt, evaluated over nine or seven trials. Experiment 1 involved 22 university students (20.6 ± 0.9 years). The minimum angle at which a tilt could be sensed while standing on both feet was determined, and measurements were taken again to examine reliability. Experiment 2 involved 40 junior athletes (12.3 ± 2.0 years), where the minimum angle for tilt sensation was obtained, and medical checks were conducted to assess injuries in the knee, lower leg, and foot. Reliability studies showed a moderately significant correlation between the first and second sessions (r = 0.504, p = 0.017), suggesting the reliability of the experimental method. The proportion capable of sensing a tilt of 1.1° and 1.6° was significantly higher in junior high school students than in elementary school students (1.1°; χ2 = 8.839, p = 0.003. 1.6°; χ2 = 4.038, p = 0.044). The group unable to sense a tilt of 1.6° and 2.1° had a significantly higher positive rate of knee injuries compared to the sensed group among junior high school students (1.6°; χ2 = 4.622, p = 0.032. 2.1°; χ2 = 4.622, p = 0.032). Our findings suggested that a reduced tilt sensation ability was associated with knee injuries in junior high school students. Utilizing our devised tilt sensation assessment could play a crucial role in preventing and detecting early injuries in junior high school students.

This study aimed to determine the validity of specific knee varus alignment measurement methods. We measured the femorotibial angle (FTA) using radiography and optical motion capture and validated the FTA measurement using markerless motion capture. The subjects included 34 legs of 19 patients with knee osteoarthritis (OA). One-way analysis of variance and multiple comparison tests were used to compare the FTA values between the Kellgren–Lawrence classification (KL) and Pearson’s correlation coefficient for validity. The analysis showed that the FTA measured by markerless motion capture had a significant correlation to the FTA measured by radiography (r = 0.869, p < 0.01) and significantly increased with increasing KL (p < 0.05). These results indicate that markerless motion capture is a valid outcome measure for varus alignment in patients with knee OA.

Objective Sitting or standing for hours decreases the blood flow in the legs and results in increased pressure on the veins, leading to the development of chronic venous disease. This study aimed to investigate the effects of insoles with a toe‐grip bar on occupational leg swelling and lower limb muscle activity. Methods This randomized cross‐over study enrolled 12 healthy men who work in a sitting or standing position. They were randomly divided into groups A (wore shoes with insoles with a toe‐grip bar for 8 hours each) and B (wore shoes with regular insoles for 8 hours each). After 1 week, groups A and B wore shoes with regular insoles and shoes with insoles with a toe‐grip bar, respectively, for 8 hours each. Lower leg volume was measured before and after each intervention, and lower limb muscle activity was measured at the start of each intervention. Results Occupational leg swelling was significantly smaller in men wearing insoles with a toe‐grip bar (P < .05). Moreover, the integrated electromyogram value of the tibialis anterior muscle and medial and lateral gastrocnemius muscles during the stance phase of walking, and tibialis anterior muscle during the swing phase of walking was significantly greater in men wearing insoles with a toe‐grip bar (all P < .05). Conclusion Insoles with a toe‐grip bar contribute to increased lower limb muscle activity, attenuating occupational leg swelling.

Motor imagery (MI) is a method of imagining movement without actual movement, and its use in combination with motor execution (ME) enhances the effects of motor learning. Neurofeedback (NFB) is another method that promotes the effects of MI. This study aimed to investigate the effects of NFB on combined MI and ME (MIME) training in a standing postural control task. Sixteen participants were randomly divided into MIME and MIME + NFB groups and performed 10 trials of a postural control task on an unstable board, with nine trials of MI in between. Electroencephalogram was assessed during MI, and the MIME + NFB group received neurofeedback on the degree of MI via auditory stimulation. A postural control task using an unstable board was performed before and after the MIME task, during which postural instability was evaluated. Postural instability was reduced after the MIME task in both groups. In addition, the root mean square, which indicates the sway of the unstable board, was significantly reduced in the MIME + NFB group compared to that in the MIME group. Our results indicate that MIME training is effective for motor learning of standing postural control. Furthermore, when MI and ME are combined, the feedback on the degree of MI enhances the learning effect.

The growing use of robots in nursing and healthcare facilities has prompted increasing research on human–robot interactions. However, specific research designs that can guide researchers to conduct rigorous investigations on human–robot interactions are limited. This paper aims to discuss the development and application of a new research design—the Intentional Observational Clinical Research Design (IOCRD). Data sources to develop the IOCRD were derived from surveyed literature of the past decade, focusing on clinical nursing research and theories relating robotics to nursing and healthcare practice. The distinction between IOCRD and other research design is the simultaneous data generation collected using advanced technological devices, for example, the wireless Bonaly-light electrocardiogram (ECG) to track heart rate variability of research subjects, robot application programs on the iPad mini to control robot speech and gestures, and Natural Language Processing programs. Even though IOCRD was developed for human–robot research, there remain vast opportunities for its use in nursing practice and healthcare. With the unique feature of simultaneous data generation and analysis, an interdisciplinary collaborative research team is strongly suggested. The IOCRD is expected to contribute guidance for researchers in conducting clinical research related to robotics in nursing and healthcare.