Abstract.[Purpose] The objective of this study was to compare the effect of underwater and overground treadmill walking, which affect gait pattern and muscle strength in people with hemiparesis following a stroke. [Subjects] Twenty chronic stroke patients were included in this study.[Methods] The subjects were randomly allocated to one of two groups, the underwater treadmill walking (UTW) and overground treadmill walking (OTW) groups. The amount of weight the subjects exerted on the foot on the affected side, as well as the joint angle values and muscle strengths on the affected side, were measured. Intervention was performed 4 times per week, and each session lasted 30 minutes. [Results] It was shown that the weight exerted on both the entire foot and hindfoot increased more in the UTW group than in the OTW group. However, the weight put on the forefoot was not found to increase for either group. In terms of the joint angle values, the angle between the hip and the knee showed a greater increase in the UTW group than in the OTW group. In contrast, the ankle joint angle did not show significant change in either of the groups. Muscle strength showed a similar increase in both groups. [Conclusion] These results suggest that after a stroke underwater treadmill walking has a more positive effect on gait pattern than overground treadmill walking.

[Purpose] The purpose of this study was to assess the effect of eye movements and proprioceptive neuromuscular facilitation (PNF) on patients with neglect syndrome. [Subjects and Methods] The subjects were randomly allocated to 2 groups: the eye movements (EM) group; and the PNF with eye movements (PEM) group. The program was conducted five times each week for 6 weeks. Balance (both static and dynamic) and head alignment (craniovertebral angle and cranial rotation angle) were measured before and after testing. [Results] In measurements of static balance, the EM group showed significant improvement in sway length and sway area when examined in the eyes-open condition, but not when examined in the eyes-closed condition. The PEM group showed significant improvement when examined under both conditions. In the assessment of dynamic balance, both groups showed significant improvement in measurements of sway areas. With respect to head alignment, there were no significant differences pre- and post-testing in either the craniovertebral angle or the cranial rotation angle in the EM group, but the PEM group showed significant differences in both measurements. [Conclusion] These results suggest that in stroke patients with neglect syndrome, PNF with eye movements, rather than eye movements alone, has a greater positive effect on balance and head alignment.

[Purpose] The aim of this study was to determine the effects of central and unilateral posteroanterior (PA) mobilization on cervical lordosis, muscle stiffness and range of motion in a patient with ankylosing spondylitis (AS). [Subject and Methods] The subject of this case study was diagnosed with AS in 1997. At baseline, variance was measured without any intervention during the first 3 days (2016.6.13–2016.6.15). Cervical PA mobilization was applied to each segment from C2–C7 from the 4th to the 11th day for 8 days. Intervention was not performed from the 12th to the 15th days for 4 days. Variances were measured a final time without intervention on the 16th day (2016.6.28). [Results] Cervical lordosis was seen to have increased. Muscle stiffness was significantly decreased after intervention and the effect of treatment lasted for five days without any additional intervention. The cervical flexion and extension angles were increased. However these increases were not statistically significant. Both the lateral flexion and left rotation angle were significantly increased and the effects of treatment lasted for five days without any additional intervention. [Conclusion] These results suggest that central and unilateral PA mobilization is effective in increasing cervical lordosis and range of motion, and decreasing muscle stiffness in patients with AS.

This study examined the impact of the number of painful stimuli on life satisfaction among workers who experienced an industrial accident and investigated how self-esteem and sleeping time affected life satisfaction. The Korea Workers’ Compensation & Welfare Service conducted the first nationwide panel survey on occupational health and safety insurance in 2013–2014 through a stratified systematic sampling on 2,000 industrial accident workers who completed convalescence. Based on the dataset, our study analyzed 1,832 workers experiencing an industrial accident after excluding 168 disease patients. For the research model analysis, a four-stage hierarchical regression analysis technique was applied using the SPSS regression analysis Macro program of PROCESS Procedure. To test mediated indirect effects of the self-esteem and sleeping time, the bootstrapping technique was applied. Life satisfaction, self-esteem and sleeping time decreased as the number of painful stimuli increased. Life satisfaction decreased as self-esteem and sleeping time decreased. On balance, the partial mediation model confirmed that self-esteem and sleeping time both mediate the impact of the number of painful stimuli on life satisfaction.

The purpose of this study was to classify ULTT videos through transfer learning with pre-trained deep learning models and compare the performance of the models. We conducted transfer learning by combining a pre-trained convolution neural network (CNN) model into a Python-produced deep learning process. Videos were processed on YouTube and 103,116 frames converted from video clips were analyzed. In the modeling implementation, the process of importing the required modules, performing the necessary data preprocessing for training, defining the model, compiling, model creation, and model fit were applied in sequence. Comparative models were Xception, InceptionV3, DenseNet201, NASNetMobile, DenseNet121, VGG16, VGG19, and ResNet101, and fine tuning was performed. They were trained in a high-performance computing environment, and validation and loss were measured as comparative indicators of performance. Relatively low validation loss and high validation accuracy were obtained from Xception, InceptionV3, and DenseNet201 models, which is evaluated as an excellent model compared with other models. On the other hand, from VGG16, VGG19, and ResNet101, relatively high validation loss and low validation accuracy were obtained compared with other models. There was a narrow range of difference between the validation accuracy and the validation loss of the Xception, InceptionV3, and DensNet201 models. This study suggests that training applied with transfer learning can classify ULTT videos, and that there is a difference in performance between models.