• International Journal of Contents
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• v.15 no.1
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• pp.39-51
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• 2019

Spontaneous speech provides rich information defining the linguistic characteristics of individuals. As such, computational analysis of speech would enhance the efficiency involved in evaluating patients' speech. This study aims to provide a method to differentiate the persons with and without aphasia based on language usage. Ten aphasic patients and their counterpart normal controls participated, and they were all tasked to describe a set of given words. Their utterances were linguistically processed and compared to each other. Computational analyses from PCA (Principle Component Analysis) to machine learning were conducted to select the relevant linguistic features, and consequently to classify the two groups based on the features selected. It was found that functional words, not content words, were the main differentiator of the two groups. The most viable discriminators were demonstratives, function words, sentence final endings, and postpositions. The machine learning classification model was found to be quite accurate (90%), and to impressively be stable. This study is noteworthy as it is the first attempt that uses computational analysis to characterize the word usage patterns in Korean aphasic patients, thereby discriminating from the normal group.

• Journal of Korea Entertainment Industry Association
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• v.15 no.8
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• pp.247-254
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• 2021

The purpose of this study is to investigate the effects of action learning on the satisfaction of majors by cultivating task-solving ability through self-reflection in the form of team learning for a certain period of time in the form of team learning by using action learning for students taking convergence curriculum in universities. The subjects of the study were 40 students from the Department of Sports Rehabilitation, a convergence of the Department of Sports and Health Management and the Department of Physical Therapy located in Jeollanam-do. This was conducted to confirm the difference in the effect of satisfaction. Comparison of changes in groups of experimental groups with action learning teaching methods showed significant differences in self-directed learning skills, problem-solving skills, and major satisfaction(p<.001)(p<.05). A significant difference in self-directed learning ability, problem-solving ability, and major satisfaction was also shown in the comparison of changes in control groups that applied traditional teaching methods(p<.05). Comparison of changes between groups showed significant differences in self-directed learning skills, problem-solving skills and major satisfaction(p<.05). Applying the action learning teaching method to the level of students in the convergence course will improve self-directed learning skills, problem-solving skills, and major satisfaction, and further research will be needed to expand the target and add variables to combine qualitative research.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.10 no.1
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• pp.87-92
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• 2016

In this paper, we improved classification performance of benign and malignant lung nodules by including the parenchyma features. For small pulmonary nodules (4-10mm) nodules, there are a limited number of CT data voxels within the solid tumor, making them difficult to process through traditional CAD(computer aided diagnosis) tools. Increasing feature extraction to include the surrounding parenchyma will increase the CT voxel set for analysis in these very small pulmonary nodule cases and likely improve diagnostic performance while keeping the CAD tool flexible to scanner model and parameters. In AdaBoost learning using naive Bayes and SVM weak classifier, a number of significant features were selected from 304 features. The results from the COPDGene test yielded an accuracy, sensitivity and specificity of 100%. Therefore proposed method can be used for the computer aided diagnosis effectively.

• Physical Therapy Rehabilitation Science
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• v.13 no.1
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• pp.18-25
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• 2024

Objective: This study is a single-group pre-post experimental study to determine the effects of simulation-based practice education on nursing students' self-efficacy, performance confidence, and educational satisfaction. Design: Single-group pre-post experimental studies Methods: This study was conducted from September 1, 2023 to November 30, 2023 for nursing undergraduate students in a simulation based practical education program. The subjects were provided with learning materials about an acute myocardial infarction case with chest pain for preliminary learning. After that, they were divided into teams of 6 people and asked to do self-study for 2 hours per team, twice a week, before conducting simulation practice. For the simulation based practical education, the participants were divided into 9 teams of 6 people each, and each team had 10 minutes for orientation, 15 minutes for scenario operation, and 50 minutes for debriefing. Results: After the simulation based practical education, self-efficacy increased statistically significantly from a mean of 3.51 before training to a mean of 3.80 after training (t=-2.12, p=0.038). However, there was no significant difference in performance confidence. There was a significant positive correlation between self-efficacy and performance confidence (r=0.62, p<0.001) and training satisfaction (r=0.67, p<0.001) after the simulation based practical education. Self-confidence was also significantly correlated with educational satisfaction (r=0.76, p<0.001). Conclusions: The results of this study showed that utilizing simulation-based practical education can increase nursing students' self-efficacy, which positively affects their performance confidence and educational satisfaction. Therefore, simulation-based practical education is an effective nursing education method that can improve nursing students' practical skills.

• Journal of Korea Entertainment Industry Association
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• v.13 no.8
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• pp.619-626
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• 2019

This study was conducted to investigate the effects of a participatory rehabilitation program on sit-rise and rise-to-walk test performances, and perception and motor skills in adults with medically vulnerable individuals and, adults with developmental disabilities in particular. Seventeen adults with developmental disabilities participated in a participatory rehabilitation program using resistance bands and exercise balls, for 60 minutes once weekly over 13 weeks. Their performances were measured before and immediately after the intervention, and 12 weeks after. The findings were as follows. In the sit-rise test, the number of times rising from sitting posture increased after the intervention versus before, but the difference was not statistically significant. In the rise-to-walk test, the performance showed statistically significant difference over time, and the post-hoc test showed a significant effect after the intervention versus before. There was no significant difference in perception and motor skills. In sum, the participatory rehabilitation program positively influenced dynamic balancing related to functional activities but had no significant effect on perception and motor skills, which is related to motor control and motor learning. It is suggested that to increase the participation in community activities, reduce fall risk, and improve dynamic balancing abilities in adults with developmental disabilities, participatory rehabilitation programs should be utilized to promote the physical wellbeing.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.4
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• pp.371-376
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• 2017

In this paper, we propose an algorithm that can recognize the pattern regardless of the sensor position when performing EMG pattern recognition using circular EMG system equipment. Fourteen features were extracted by using the data obtained by measuring the eight channel EMG signals of six motions for 1 second. In addition, 112 features extracted from 8 channels were analyzed to perform principal component analysis, and only the data with high influence was cut out to 8 input signals. All experiments were performed using k-NN classifier and data was verified using 5-fold cross validation. When learning data in machine learning, the results vary greatly depending on what data is learned. EMG Accuracy of 99.3% was confirmed when using the learning data used in the previous studies. However, even if the position of the sensor was changed by only 22.5 degrees, it was clearly dropped to 67.28% accuracy. The accuracy of the proposed method is 98% and the accuracy of the proposed method is about 98% even if the sensor position is changed. Using these results, it is expected that the convenience of the users using the circular EMG system can be greatly increased.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.3
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• pp.261-270
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• 2017

Bad sitting postures are known to cause for a variety of diseases or physical deformation. However, it is not easy to fit right sitting posture for long periods of time. Therefore, methods of distinguishing and inducing good sitting posture have been constantly proposed. Proposed methods were image processing, using pressure sensor attached to the chair, and using the IMU (Internal Measurement Unit). The method of using IMU has advantages of simple hardware configuration and free of various constraints in measurement. In this paper, we researched on distinguishing sitting postures with a small amount of data using just one IMU. Feature extraction method was used to find data which contribution is the least for classification. Machine learning algorithms were used to find the best position to classify and we found best machine learning algorithm. Used feature extraction method was PCA(Principal Component Analysis). Used Machine learning models were five : SVM(Support Vector Machine), KNN(K Nearest Neighbor), K-means (K-means Algorithm) GMM (Gaussian Mixture Model), and HMM (Hidden Marcov Model). As a result of research, back neck is suitable position for classification because classification rate of it was highest in every model. It was confirmed that Yaw data which is one of the IMU data has the smallest contribution to classification rate using PCA and there was no changes in classification rate after removal it. SVM, KNN are suitable for classification because their classification rate are higher than the others.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.15-24
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• 2022

The article clarifies the conditions for information, digital and educational accessibility for higher education seekers with disabilities in terms of distance learning caused by quarantine restrictions. It is established that such conditions are regulated by international and Ukrainian legal documents (The Standard Rules on the Equalization of Opportunities for Persons with Disabilities, Convention on the Rights of Persons with Disabilities, Sustainable Development Goals, Law of Ukraine "On Education", Law of Ukraine "On Higher Education", Strategy for the Development of Higher Education in Ukraine 2021-2031, Development Strategy areas of innovation for the period up to 2030, Development strategy of the sphere of innovation activity for the period up to 2030). As a part of information barrierlessness, Higher Education Institutions (HEI) should provide access to information in various formats and using technologies, in particular Braille script, large-type printing, audio description (audio descriptive commenting), sign language interpretation, subtitling, a format suitable for reading by screen access programs, formats of simple speech, easy-to-read formats, means of alternative communication. The experience of Pavlo Tychyna Uman State Pedagogical University is described. In particular, special attention is paid to the study of sign language: in view of this, the initiative group implemented the project "Learning to hear and overcome social isolation together" with the financial support of the British Council in Ukraine. Within the framework of digital accessibility, the official website of the Faculty of Social and Psychological Education has been adapted for the visually impaired in accordance with WCAG 2.0 World Standards. In 2021, Pavlo Tychyna Uman State Pedagogical University implemented the project "Cultural, Recreational and Tourist Cherkasy Region: Inclusive Social 3D Map" funded by the Ukrainian Cultural Foundation; a site with available content for online travel in the region to provide barrier-free access to the historical and cultural heritage of Cherkasy region was created. Educational accessibility is achieved by increasing the number of people with special educational needs, receiving education in inclusive groups; activities of the Center for Social and Educational Integration and Inclusive Rehabilitation Social Tourism "Bez barieriv" ("Without barriers"); implementation of a research topic for financing the Ministry of Education and Science of Ukraine: "Social and psychological rehabilitation of children and youth with special educational needs by means of inclusive tourism"; implementation of the project "Social inclusion of distance educational process"; development of information campaigns to popularize the ideas of accessibility, the need for its implementation, ongoing training programs and competitions, etc.

• Journal of Dental Rehabilitation and Applied Science
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• v.33 no.2
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• pp.88-96
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• 2017

Purpose: The purpose of this study is to assess the relationship between the time spent designing custom abutments and repeated learning using dental implant computer aided design (CAD) software. Materials and Methods: The design of customized abutments was performed four stages using the 3DS CAD software and the EXO CAD software, and measured repeatedly three times by each stage. Learning effect by repetition was presented with the learning curve, and the significance of the reduction in the total time and the time at each stage spent on designing was evaluated using the Friedman test and the Wilcoxon signed rank test. The difference in the design time between groups was analyzed using the repeated measure two-way ANOVA. Statistical analysis was performed using the SPSS statistics software (P < 0.05). Results: Repeated learning of the customized abutment design displayed a significant difference according to the number of repetition and the stage (P < 0.001). The difference in the time spent designing was found to be significant (P < 0.001), and that between the CAD software programs was also significant (P = 0.006). Conclusion: Repeated learning of CAD software shortened the time spent designing. While less design time on average was spent with the 3DS CAD than with the EXO CAD, the EXO CAD showed better results in terms of learning rate according to learning effect.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.10 no.4
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• pp.259-265
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• 2016

In this paper, new method was proposed to classify lung tissues such as Broncho vascular, Emphysema, Ground Glass Reticular, Ground Glass, Honeycomb, Normal for early lung disease detection. 459 Statistical features was extraced from joint histogram matrix based on multi resolution analysis, volumetric LBP, and CT intensity, then dominant features was selected by using adaboost learning. Accuracy of proposed features and 3D AMFM was 90.1% and 85.3%, respectively. Proposed joint histogram based features shows better classification result than 3D AMFM in terms of accuracy, sensitivity, and specificity.