• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.4
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• pp.215-223
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• 2018

Recently, as interest of wearable devices has increased, commercially available smart wristbands and applications have been used as a tool for personal healthy management. However most previous studies have focused on evaluating the accuracy and reliability of the technical problems of wearable devices, especially step counts, walking distance, and energy consumption measured from the smart wristbands. In this study, we propose a physical activity evaluation model using classification rules, induced from the associative classification mining approach. These rules associated with five physical activities were generated by considering activities and walking times in target heart rate zones such as 'Out-of Zone', 'Fat Burn Zone', 'Cardio Zone', and 'Peak Zone'. In the experiment, we evaluated the prediction power of classification rules and verified its effectiveness by comparing classification accuracies between the proposed model and support vector machine.

• The Journal of Korean Academy of Orthopedic Manual Physical Therapy
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• v.18 no.2
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• pp.31-39
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• 2012

Background: The purpose of this study was to develop a problem-based learning model for orthopedic manual physical therapy. A problem-based learning (PBL) model for orthopedic manual physical therapy developed from PBL module of Jeju C university (Halla-Newcastle PBL Center). A summary of this study is as follows: 1) PBL model is comprised of a class of 30 students, operated small group as of 4~5 students. 2) PBL is suggested a scenario of clinical case, induced variety reaction through group discussion and presentation. 3) PBL is occurred wide variety learning through group work activity and self-directed learning. 4) The tutor as a facilitator is played a guide for group discussion, work activity and team learning. 5) The evaluation for PBL is performed such as student self-evaluation, group activity evaluation, individual presentation, and practice. This model is considered wide variety learning through team learning and self-directed learning by clinical reasoning and problem solving for musculoskeletal clinical case. We suggest problem based learning for the education of orthopedic manual physical therapy in which the learners are very interested in and has the effective outcome.

• Tuberculosis and Respiratory Diseases
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• v.82 no.4
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• pp.311-318
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• 2019

Background: Although physical activity is known to be beneficial to lung function, few studies have been conducted to investigate the correlation between physical activity and lung function in dusty areas. Therefore, the purpose of this study is to investigate the correlation between physical activity and lung function in a Korean cohort including normal and COPD-diagnosed participants. Methods: Data obtained from the COPD in dusty areas (CODA) cohort was analyzed for the following factors: lung function, symptoms, and information about physical activity. Information on physical activity was valuated using questionnaires, and participants were categorized into two groups: active and inactive. The evaluation of the mean lung function, modified Medical Research Council dyspnea grade scores, and COPD assessment test scores was done based on the participant physical activity using a general linear model after adjusting for age, sex, smoking status, pack-years, height, and weight. In addition, a stratification analysis was performed based on the smoking status and COPD. Results: Physical activity had a correlation with high forced expiratory volume in 1 second ($FEV_1$) among CODA cohort (p=0.03). While the active group exhibited significantly higher $FEV_1$ compared to one exhibited by the inactive group among past smokers (p=0.02), no such correlation existed among current smokers. There was no significant difference observed in lung function after it was stratified by COPD. Conclusion: This study established a positive correlation between regular physical activity in dusty areas and lung function in participants.

• Journal of the Korean Society of Physical Medicine
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• v.14 no.1
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• pp.151-161
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• 2019

PURPOSE: To investigate the validity of a smartphone application for post-stroke daily living activity management based on an evaluation by users and experts. METHODS: The study design adhered to the analysis, design, development, implementation, and evaluation ADDIE (Analysis-Design-Development-Implement-Evaluation) model. We downloaded the application onto the smartphones of 33 users and 30 experts, taught them how to use it, and asked them to use the application for four weeks. The users' daily lives before and after using the application were compared based on the K-MBI (Korean Version of Modified Barthel Index) to evaluate the usability of the application. For the expert group, we investigated the content validity and reliability of the application and evaluated the usability of the application. Data were analyzed using the SPSS 21.0 software. Users' general characteristics and experts' evaluation scores were analyzed using descriptive statistics. Content validity was tested using the content validity index (CVI), and reliability was tested with Cronbach's alpha. Users' K-MBI scores before and after using the application were compared with the paired sample t-test. RESULTS: Users gave an average rating of 2.93 out of 4 for the application for managing the daily lives of stroke patients, while experts gave an average score of 3.14. With regard to the K-MBI scores, only the dressing score improved significantly (p<.005) after using the application, and scores for other categories slightly improved but not to significant levels. CONCLUSION: The results of this study suggest that the STROKECARE application is usable and could help stroke patients manage their daily lives.

• PNF and Movement
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• v.20 no.3
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• pp.359-370
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• 2022

Purpose: Physical therapists are required to properly choose the most appropriate treatment for each patient within the framework of the International Classification of Functioning, Disability, and Health (ICF model). The aims of this study were to determine whether neurological physical therapists in clinical settings in South Korea know about the ICF model and to investigate the current trends of outcome measures (OMs) used by them. Methods: Two hundred and one physical therapists who worked with patients with neurological disorders participated in this study. The survey was conducted via e-mail and asked about commonly used OMs and the considerations for selecting OMs. Results: All physical therapists involved in this study responded completely, and 45.8% of participants learned about the ICF model, while 37.3% understood the detailed information related to the ICF model. The rest of the participants did not know or just heard about the ICF model. The most frequently used tools at the body function/structure level were the Range of Motion (98%), Manual Muscle Test (97%), Berg Balance Scale (83.1%), and Modified Ashworth Scale (70.6%) when allowing repetition. At the activity level, the 10-meter walk test (71.1%), 6-minute walk test (54.2%), and Functional Ambulatory Category (43.3%) were used, while the Activity-Specific Balance Confidence Scale (23.9%) was used at the participation level. There was a positive relationship between the number of tools used and years of work, as well as the level of understanding of the ICF model. Conclusion: The results of this study suggest that it is necessary to learn the ICF model in a clinical setting. In addition, the medical system needs to be modified to encourage physical therapists in South Korea to use proper OMs within the ICF model.

• Journal of Korean Academy of Nursing
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• v.48 no.6
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• pp.692-707
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• 2018

Purpose: We aimed to examine the effects of an integrated physical activity (PA) program developed for physically inactive workers on the theoretical basis of the PRECEDE-PROCEED model. Methods: Participants were 268 workers in three departments of L manufacturing unit in South Korea. The three departments were randomly allocated into integration (n=86) (INT), education (n=94) (ED), and control (n=88) (CT) groups. The INT group received self-regulation, support, and policy-environmental strategies of a 12-week integrated PA program, the ED group received self-regulation strategies only, and the CT group did not receive any strategies. After 12 weeks, process evaluation was conducted by using the measures of self-regulation (autonomous vs. controlled regulation), autonomy support, and resource availability; impact evaluation by using PA measures of sitting time, PA expenditure, and compliance; and outcome evaluation by using the measures of cardiometabolic/musculoskeletal health and presenteeism. Results: Among process measures, autonomous regulation did not differ by group, but significantly decreased in the CT group (p=.006). Among impact measures, PA compliance significantly increased in the INT group compared to the CT group (p=.003). Among outcome measures, the changes in cardiometabolic/musculoskeletal health and presenteeism did not differ by group; however, systolic blood pressure (p=.012) and a presenteeism variable (p=.041) significantly decreased only in the INT group. Conclusion: The integrated PA program may have a significant effect on increases in PA compliance and significant tendencies toward improvements in a part of cardiometabolic health and presenteeism for physically inactive workers. Therefore, occupational health nurses may modify and use it as a workplace PA program.

• Physical Therapy Korea
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• v.13 no.4
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• pp.1-9
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• 2006

The purpose of this research was to analyze the effects of the increase of the femoral anteversion angle on the unbalanced quadriceps femoris muscle causing the increase of the valgus force on the knee joints and patellofemoral pain syndrome by comparing with the group that shows the smaller femoral anteversion angle. The method for the research was to compare the femoral muscle's activity while the subjects were maintaining the knee joint flexed isometrically for 10 seconds. The evaluation tool for femoral muscle's activity was QEMG-4 (model LXM 3204). The results were as followings. Firstly, in case of the experimental group, the muscle strength of the vastus lateralis muscle was strong while the rectus femoris and vastus medialis were weak. In these facts, we can see the statistically meaningful difference in vastus medialis muscle activity. Secondly, in the muscle activity analysis for vastus lateralis and medialis of the two groups, we could see the vastus lateralis muscle was strong in anteversion wider for experimental group while the vastus medialis muscle contracted far more stronger in anteversion smaller for control group. From these results, we can see the significant differences in muscle recruitment between the two groups. Above results show that if the anteversion becomes wider, vastus medialis muscle will become seriously weaker, on the other hand, vastus lateralis act stronger.

• Journal of Environmental Science International
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• v.16 no.11
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• pp.1231-1238
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• 2007

The promotion of walking and bicycling is recently a hot topic in the urban planning and design field. Many planners have already examined the many components of the land use-transportation connection and built environment-physical activity link. A rapidly growing area of urban form research is to measure the level of walk-ability in urban environments. With this background, this research conducted a preliminary study to develop the evaluation indicators of pedestrian environments. Based on the literature reviews on walking or pedestrian environments, we proposed the seventeen indicators related with pedestrian facilities, road attributes and walking environment. We also performed a questionary survey to evaluate the satisfaction of their neighborhood pedestrian environments for 302 randomly selected adults living in the City of Changwon, Gyeongsangnam-do. Finally, this research provided the valid model to evaluate the effects of physical environmental factors on the walking satisfaction using factor analysis and multiple regression analysis.

• Journal of Engineering Education Research
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• v.23 no.6
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• pp.68-76
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• 2020

This study presents a teaching model to increase the participation and interest, and to improve their understanding of physical concepts of first-year engineering students taking physics(2) course at a three-year college. In the class, a team task solution based on teamwork and a peer learning method through questions and answers between participants in each team were applied so that learners could actively participate in the class to discuss and present. We examined how the activities of each team affected students' interest in subjects, motivation to learn, and the degree of understanding of physical concepts. In the team activity, students were able to actively participate through emotional sharing between learners and free questions and explanations, and it was confirmed that academic achievement was improved by comparing the final exam evaluation results with the evaluation results of the previous three years.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.