• Physical Therapy Korea
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• v.26 no.3
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• pp.23-31
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• 2019

Background: Measurement of passive ankle dorsiflexion range of motion (ADROM) is often part of a physical therapy assessment. Objects: The objective of this study was to identify the effects of subtalar joint neutral position (SJNP) on passive ADROM according to knee position in young adults. Methods: We recruited 14 young adult participants for this study. Two examiners used a universal goniometer to measure passive ADROM with and without SJNP. Dorsiflexion force was applied to the forefoot until maximum resistance was reached in two knee positions (extension and $90^{\circ}$ flexion) in the prone position. Subtalar joint position was also recorded at maximum ADROM. Passive ADROM was measured three times at different knee and subtalar joint positions, in random order. Two-way repeated-measures analysis of variance was used to compare the effects of subtalar joint and knee position on passive ADROM. Results: Passive ADROM was significantly lower with than without SJNP during both knee extension (mean difference: $7.4^{\circ}$) and $90^{\circ}$ flexion (mean difference: $16.9^{\circ}$) (p<.01). Passive ADROM was significantly higher during $90^{\circ}$ knee flexion than during knee extension both with (mean difference: $5.8^{\circ}$) and without SJNP (mean difference: $15.2^{\circ}$) (p<.01). The valgus position of the subtalar joint was significantly lower with than without SJNP during both knee extension (mean difference: $3.3^{\circ}$) and $90^{\circ}$ flexion (mean difference: $4.3^{\circ}$) (p<.01). Conclusion: Our results indicate that the gastrocnemius may limit ankle dorsiflexion more than the soleus does. Greater dorsiflexion at the subtalar and midtarsal joints was observed during passive ADROM measurement without than that with SJNP; therefore, SJNP should be maintained for accurate measurement of ADROM.

• Physical Therapy Rehabilitation Science
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• v.8 no.3
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• pp.162-169
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• 2019

Objective: The purpose of this study was to investigate the conditions for the application of various plank exercises to people who require trunk stabilization by comparing trunk muscle activity according to the degree of hip abduction in the plank exercise. Design: Cross-sectional study. Methods: Twenty healthy participants voluntarily participated in this study and the plank exercise was performed under 5 conditions (two-legged support plank [TSP] with hip abduction, TSP with hip abduction of 15 degrees, TSP with hip abduction of 30, one-legged support plank [OSP] with hip abduction of 15 degrees, OSP with hip abduction of 30 degrees). In order to measure the trunk muscle activity according to the 5 conditions, surface electromyography was used. The electrical activities of the rectus abdominis (RA), external oblique (EO), and internal oblique (IO) muscles were measured during the 5 plank exercises. Subjects practiced each of the 5 conditions three times in random order and the average values were obtained. Results: In the OSP condition with 15/30 degrees of hip abduction, activities of the RA, EO, and IO were significantly greater than during the TSP (p<0.05). In the OSP with 30 degrees of hip abduction condition, activities of the left EO, IO were significantly greater than other plank exercise conditions (p<0.05). Conclusions: The plank exercise with hip abduction of 30 degrees and the OSP exercise can be suggested as an effective method to enhance the activity of the trunk oblique muscles.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.25-31
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• 2021

Moving toward an aged society, traffic accidents involving elderly drivers have also attracted broader public attention. A rapid increase of senior involvement in crashes calls for developing appropriate crash-severity prediction models specific to senior drivers. In that regard, this study leverages machine learning (ML) algorithms so as to predict the severity of vehicle-pedestrian collisions induced by elderly drivers. Specifically, four ML algorithms (i.e., Logistic model, K-nearest Neighbor (KNN), Random Forest (RF), and Support Vector Machine (SVM)) have been developed and compared. Our results show that Logistic model and SVM have outperformed their rivals in terms of the overall prediction accuracy, while precision measure exhibits in favor of RF. We also clarify that driver education and technology development would be effective countermeasures against severity risks of senior driver-induced collisions. These allow us to support informed decision making for policymakers to enhance public safety.

• Nutrition Research and Practice
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• v.15 no.1
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• pp.95-105
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• 2021

BACKGROUND/OBJECTIVES: The measurement of body composition, including muscle and fat mass, remains challenging in large epidemiological studies due to time constraint and cost when using accurate modalities. Therefore, this study aimed to develop and validate prediction equations according to sex to measure lean body mass (LBM), appendicular skeletal muscle mass (ASM), and body fat mass (BFM) using anthropometric measurement, serum creatinine level, and lifestyle factors as independent variables and dual-energy X-ray absorptiometry as the reference method. SUBJECTS/METHODS: A sample of the Korean general adult population (men: 7,599; women: 10,009) from the Korean National Health and Nutrition Examination Survey 2008-2011 was included in this study. The participants were divided into the derivation and validation groups via a random number generator (with a ratio of 70:30). The prediction equations were developed using a series of multivariable linear regressions and validated using the Bland-Altman plot and intraclass correlation coefficient (ICC). RESULTS: The initial and practical equations that included age, height, weight, and waist circumference had a different predictive ability for LBM (men: R2 = 0.85, standard error of estimate [SEE] = 2.7 kg; women: R2 = 0.78, SEE = 2.2 kg), ASM (men: R2 = 0.81, SEE = 1.6 kg; women: R2 = 0.71, SEE = 1.2 kg), and BFM (men: R2 = 0.74, SEE = 2.7 kg; women: R2 = 0.83, SEE = 2.2 kg) according to sex. Compared with the first prediction equation, the addition of other factors, including serum creatinine level, physical activity, smoking status, and alcohol use, resulted in an R2 that is higher by 0.01 and SEE that is lower by 0.1. CONCLUSIONS: All equations had low bias, moderate agreement based on the Bland-Altman plot, and high ICC, and this result showed that these equations can be further applied to other epidemiologic studies.

• Physical Therapy Korea
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• v.28 no.3
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• pp.194-199
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• 2021

Background: The scapulo-thoracic musculatures including serratus anterior (SA), upper trapezius and lower trapezius can provide shoulder stability and functional shoulder movement. Objects: The muscle activities of upper and lower SA were compared during three different scapular protraction exercises in healthy individuals in sitting position. Methods: Twenty-five healthy subjects were participated. Electromyography device was used to measure muscle activity of upper and lower SA and trapezius muscles. Each subject was asked to perform three different scapular protraction exercises (scapular protraction [SP], SP with self-resistance [SPSR], SPSR with hand-exerciser [SPSRH]) in random order. One-way repeated measures analysis of the variance and a Bonferroni post hoc test were used. Results: The muscle activity of lower SA muscle was significantly different among three conditions (SP vs. SPSR vs. SPSRH) (p < 0.01). The lower SA muscle activity was significantly greater during SPSRH compared to SP and SPSR, which required joint stability more than SP and SPSR (p < 0.01). Conclusion: SPSRH exercise can be recommended to facilitate the muscle activity of lower SA. In addition, the intramuscular variation in the upper and lower SA during scapular protraction exercise is required to consider the effective rehabilitation.

• Journal of Dental Anesthesia and Pain Medicine
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• v.22 no.1
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• pp.1-10
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• 2022

Background: Inferior alveolar nerve block (IANB) is known to have a lower success rate for anesthesia in patients with irreversible pulpitis. This calls for supplementary techniques to effectively anesthetize such patients. This systematic review aimed to evaluate the published literature for determining the success rate of anesthesia induction using post-IANB intraligamentary (IL) injection in the mandibular teeth of patients with symptomatic irreversible pulpitis. The review question was, "What is the success rate of IL injection in the mandibular teeth of patients with irreversible pulpitis as a supplementary technique for endodontic treatment?" Methods: A thorough search of electronic databases and manual searches were performed. The protocol of the review was framed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist and was registered in the International Prospective Register of Ongoing Systematic Reviews (PROSPERO) with a proper criterion for inclusion and exclusion of studies. The included studies were analyzed using the Cochrane Collaboration "Risk of Bias" tool. A meta-analysis that included a comparison of primary nerve block and supplemental IL injection was performed. The success rate was evaluated using the combined risk ratio (RR) with a random risk model. A funnel plot was created to measure publication bias. Results: After all analyses, four studies were included. In the forest plot representation, RRs were 3.56 (95% CI: 2.86, 4.44), which were in favor of the supplemental IL injections. Statistical heterogeneity was found to be 0%. These values suggest that supplemental IL injections provide better success rates for anesthesia. Conclusion: According to the pooled qualitative and quantitative analyses, supplemental IL injections increased anesthetic efficacy.

• Physical Therapy Korea
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• v.29 no.1
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• pp.11-18
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• 2022

Background: Muscle activities of gluteus maximus (GM) and hamstring (HAM) have important roles in the stability and mobility of the hip joint during various functional activities including bridge and prone hip extension exercises. Objects: The purpose of this study is to investigate muscle activities of GM, multifidus (MF) and HAM during three different bridge exercises in healthy individuals. Methods: Twenty healthy subjects were participated. Electromyography device was used to measure muscle activities of GM, MF and HAM. Each subject was asked to perform three different bridge exercises with hip abduction (0°, 15°, 30°) in random order. One-way repeated measures analysis of the variance and a Bonferroni post hoc test were used. Statistical significance was set at α = 0.01. Results: The muscle activity of GM was significantly different among three conditions (hip abduction 0°, 15°, 30°) (adjusted p-value [Padj] < 0.01). The muscle activity of GM was significantly greater during bridge exercise with hip abduction 30° compared to 0° and 15° (Padj < 0.01). There was no significant difference in the muscle activity of MF and HAM muscle (Padj > 0.01). The ratio of muscle activity (ratio = GM/HAM) during bridge exercise with hip abduction 30° was significant greater compared to the hip abduction angles 0° and 15° (Padj < 0.01). Conclusion: Bridge exercise with hip abduction 30° can be recommended to selectively facilitate the muscle activity of GM and improve the ratio of muscle activity between GM and HAM.

• Asia-Pacific Journal of Business
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• v.13 no.3
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• pp.293-309
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• 2022

Purpose - The purpose of this study is to explore the possibility of predicting the degree of smartphone overdependence based on mobile phone usage patterns. Design/methodology/approach - In this study, a survey conducted by Korea Internet and Security Agency(KISA) called "problematic smartphone use survey" was analyzed. The survey consists of 180 questions, and data were collected from 29,712 participants. Based on the data on the smartphone usage pattern obtained through the questionnaire, the smartphone addiction level was predicted using machine learning techniques. k-NN, gradient boosting, XGBoost, CatBoost, AdaBoost and random forest algorithms were employed. Findings - First, while various factors together influence the smartphone overdependence level, the results show that all machine learning techniques perform well to predict the smartphone overdependence level. Especially, we focus on the features which can be obtained from the smartphone log data (without psychological factors). It means that our results can be a basis for diagnostic programs to detect problematic smartphone use. Second, the results show that information on users' age, marriage and smartphone usage patterns can be used as predictors to determine whether users are addicted to smartphones. Other demographic characteristics such as sex or region did not appear to significantly affect smartphone overdependence levels. Research implications or Originality - While there are some studies that predict smartphone overdependence level using machine learning techniques, but the studies only present algorithm performance based on survey data. In this study, based on the information gain measure, questions that have more influence on the smartphone overdependence level are presented, and the performance of algorithms according to the questions is compared. Through the results of this study, it is shown that smartphone overdependence level can be predicted with less information if questions about smartphone use are given appropriately.

• Safety and Health at Work
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• v.11 no.4
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• pp.526-532
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• 2020

Background: The high incidence of work-related diseases and injuries among day-laborers and workers with no legal contracts (informal workers) has received the attention of the Thai authorities. Workers' low occupational health literacy (OHL) has been reasoned as one contributing factor. Absence of a valid tool has prevented assessment of informal workers' OHL. The aim of this study was to create a valid and reliable Occupational Health Literacy Scale within the context of Thai working culture (TOHLS-IF). Methods: This study used the mixed method approach to develop TOHLS-IF. Questions were generated using in-depth interviews and an extensive review of the literature. Experts' assessment confirmed the content validity of TOHLS-IF. The scales of its psychometric properties were assessed in a sample of 400 informal workers using cluster random sampling. Results: The final version of the TOHLS-IF comprises 38 items within 4 dimensions: Ability to Gain Access, Understanding, Evaluation, and Use of occupational health and safety information. Factor analysis identified items explaining 50.22% of the total variance. The final confirmatory analysis confirmed the model estimates were satisfactory for the construct. TOHLS-IF demonstrated a high internal consistency and satisfactory reliability (Cronbach's alpha = .98). Conclusion: The TOHLS-IF is a valid and reliable instrument to assess informal workers' OHL. The structural dimensions of this instrument are based on the concept of health literacy and Thai culture. Thai health professionals are encouraged to benefit from this instrument to assess their workers' OHL and apply findings as guidelines for effective occupational health and safety interventions.

• Smart Structures and Systems
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• v.30 no.6
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• pp.687-701
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• 2022

Inevitable response loss under complex operational conditions significantly affects the integrity and quality of measured data, leading the structural health monitoring (SHM) ineffective. To remedy the impact of data loss, a common way is to transfer the recorded response of available measure point to where the data loss occurred by establishing the response mapping from measured data. However, the current research has yet addressed the structural condition changes afterward and response mapping learning from a small sample. So, this paper proposes a novel data driven structural response reconstruction method based on a sophisticated designed generating adversarial network (UAGAN). Advanced deep learning techniques including U-shaped dense blocks, self-attention and a customized loss function are specialized and embedded in UAGAN to improve the universal and representative features extraction and generalized responses mapping establishment. In numerical validation, UAGAN efficiently and accurately captures the distinguished features of structural response from only 40 training samples of the intact structure. Besides, the established response mapping is universal, which effectively reconstructs responses of the structure suffered up to 10% random stiffness reduction or structural damage. In the experimental validation, UAGAN is trained with ambient response and applied to reconstruct response measured under earthquake. The reconstruction losses of response in the time and frequency domains reached 16% and 17%, that is better than the previous research, demonstrating the leading performance of the sophisticated designed network. In addition, the identified modal parameters from reconstructed and the corresponding true responses are highly consistent indicates that the proposed UAGAN is very potential to be applied to practical civil engineering.