Hyunmok Son - Academia.edu (original) (raw)

Papers by Hyunmok Son

ACS Biomaterials Science & Engineering, Jan 26, 2023

Polymers, Dec 25, 2020

Post-surgery failure of dental implants due to alveolar bone loss is currently critical, disturbi... more Post-surgery failure of dental implants due to alveolar bone loss is currently critical, disturbing the quality of life of senior dental patients. To overcome this problem, bioceramic or bone graft material is loaded into the defect. However, connective tissue invasion instead of osteogenic tissue limits bone tissue regeneration. The guided bone regeneration concept was adapted to solve this problem and still has room for improvements, such as biochemical similarity or oriented structure. In this article, an aligned electrospun-guided bone regeneration barrier with xenograft equine bonederived nano hydroxyapatite (EBNH-RB) was fabricated by electrospinning EBNH/PCL solution on high-speed rotating drum collector and fiber characterization, viability and differentiation enhancing properties of mesenchymal dental pulp stem cell on the barrier was determined. EBNH-RB showed biochemical and structural similarity to natural bone tissue electron microscopy image analysis and x-ray diffractometer analysis, and had a significantly better effect in promoting osteogenesis based on the increased bioceramic content by promoting cell viability, calcium deposition and osteogenic marker expression, suggesting that they can be successfully applied to regenerate alveolar bone as a guided bone regeneration barrier.

IEEE Access, 2022

Population aging is a global trend, and the highest proportion of elderly people in the workforce... more Population aging is a global trend, and the highest proportion of elderly people in the workforce per unit of population is found in agricultural areas. However, few systematic studies have been conducted on farmer falls in the field of agricultural machinery. This study focuses on the application of classification methods for monitoring devices to detect fall/nonfall movements of farmworkers, where agricultural biomechanical factors are considered in detecting activities of daily living. In this study, we recorded and analyzed original acquisition datasets of signals obtained from two accelerometers and one gyroscope for 40 healthy individuals who performed various falls and activities of daily living (ADLs). Spatial characteristics were used to train the machine-learning classifiers to distinguish between fall and non-fall events. Supervised machine learning experiments evaluated the effectiveness of the proposed approach: the k-nearest neighbors (kNN) and support vector machine (SVM) algorithms achieved roc auc-scores of 0.999 in differentiating between falls and ADLs (binary-class classification). Moreover, an artificial neural network (ANN) classifier showed the highest performance in terms of classification roc auc-scores of 1.0. The evaluation metric demonstrated the highest performance in the analysis and evaluation of the signal obtained from the S2 acceleration sensor with a measurement range of ±16 g. The proposed SVM classifier evaluations showed a 0.988 roc auc-score for sensor tests in multi-class classification, along with the highest performance in terms of the F1-score and Matthews Correlation Coefficient (MCC) over 84% in the multi-class classification model for distinguishing each of ADLs and Fall using ±16 g acceleration sensor.

Applied sciences, Apr 2, 2021

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Polymers, Jan 14, 2021

Purpose: The purpose of this study is to provide analysis of physiological, biomechanical respons... more Purpose: The purpose of this study is to provide analysis of physiological, biomechanical responses occurring from the operation to lifting or twist lifting task appears frequently in agricultural work. Methods: This study investigated the changes of physiological factors such as heart rate, heart rate variability (HRV) and biomechanical factors such as physical activity and kinetic analysis in the task of twisting at the waist while lifting. Results: Heart rates changed significantly with the workload. The result indicated that the workload of 2 kg was light intensity work, and the workload of 12 kg was hard intensity work. Physical activity increased as the workload increased both on wrist and waist. Besides, stress index of the worker increased with the workload. Dynamic load to herniated discs was analyzed using inertial sensor, and the angular acceleration and torque increased with the workload. The proposed measurement system can measure the recipient`s physiological and physi...

ACS Biomaterials Science & Engineering, Jan 26, 2023

IEEE Access

Population aging is a global trend, and the highest proportion of elderly people in the workforce... more Population aging is a global trend, and the highest proportion of elderly people in the workforce per unit of population is found in agricultural areas. However, few systematic studies have been conducted on farmer falls in the field of agricultural machinery. This study focuses on the application of classification methods for monitoring devices to detect fall/nonfall movements of farmworkers, where agricultural biomechanical factors are considered in detecting activities of daily living. In this study, we recorded and analyzed original acquisition datasets of signals obtained from two accelerometers and one gyroscope for 40 healthy individuals who performed various falls and activities of daily living (ADLs). Spatial characteristics were used to train the machine-learning classifiers to distinguish between fall and non-fall events. Supervised machine learning experiments evaluated the effectiveness of the proposed approach: the k-nearest neighbors (kNN) and support vector machine (SVM) algorithms achieved roc auc-scores of 0.999 in distinguishing falls and ADLs (binary-class classification). Moreover, an artificial neural network (ANN) classifier showed the highest performance in terms of classification roc auc-scores of 1.0. The evaluation metric demonstrated the highest performance in the analysis and evaluation of the signal obtained from the S2 acceleration sensor with a measurement range of ±16 g. The proposed SVM classifier evaluations showed a 0.988 roc auc-score for sensor tests in multi-class classification, along with the highest performance in terms of the F1-score and Matthews Correlation Coefficient (MCC) over 84% in the multi-class classification model for distinguishing each of ADLs and Fall using ±16 g acceleration sensor. INDEX TERMS Agricultural worker, fall-detection, human behavior recognition, machine learning, wearable sensor.

Applied Sciences, 2021

Cisplatin, a representative anticancer drug used to treat cancer, has many adverse effects. In pa... more Cisplatin, a representative anticancer drug used to treat cancer, has many adverse effects. In particular, it causes significant damage to the kidneys. Thus, many researchers have studied the delivery of drugs, such as cisplatin, to cancer areas using targeted drug-delivery systems. Here, we propose a new way to treat cancer by delivering anticancer drugs directly to the tumor site using the electrospray (ES) technique. We determined the optimal conditions for ES to promote the introduction of cisplatin into cancer cells. In our results, the group with cisplatin delivery-based electrospray (CDES) at 6 kV had an apoptosis of cancer cells approximately two times more than the group treated with cisplatin alone. We also confirmed that ES alone did not affect the survival of cells up to a voltage of 6 kV, but increased the permeability of the cell plasma membrane instantaneously, facilitating the influx of the drug.

Polymers, 2021

The 3D-printed bioactive ceramic incorporated Poly(ε-caprolactone) (PCL) scaffolds show great pro... more The 3D-printed bioactive ceramic incorporated Poly(ε-caprolactone) (PCL) scaffolds show great promise as synthetic bone graft substitutes. However, 3D-printed scaffolds still lack adequate surface properties for cells to be attached to them. In this study, we modified the surface characteristics of 3D-printed poly(ε-caprolactone)/hydroxyapatite scaffolds using O2 plasma and sodium hydroxide. The surface property of the alkaline hydrolyzed and O2 plasma-treated PCL/HA scaffolds were evaluated using field-emission scanning microscopy (FE-SEM), Alizarin Red S (ARS) staining, and water contact angle analysis, respectively. The in vitro behavior of the scaffolds was investigated using human dental pulp-derived stem cells (hDPSCs). Cell proliferation of hDPSCs on the scaffolds was evaluated via immunocytochemistry (ICC) and water-soluble tetrazolium salt (WST-1) assay. Osteogenic differentiation of hDPSCs on the scaffolds was further investigated using ARS staining and Western blot analys...

Polymers, 2020

Post-surgery failure of dental implants due to alveolar bone loss is currently critical, disturbi... more Post-surgery failure of dental implants due to alveolar bone loss is currently critical, disturbing the quality of life of senior dental patients. To overcome this problem, bioceramic or bone graft material is loaded into the defect. However, connective tissue invasion instead of osteogenic tissue limits bone tissue regeneration. The guided bone regeneration concept was adapted to solve this problem and still has room for improvements, such as biochemical similarity or oriented structure. In this article, an aligned electrospun-guided bone regeneration barrier with xenograft equine bone-derived nano hydroxyapatite (EBNH-RB) was fabricated by electrospinning EBNH/PCL solution on high-speed rotating drum collector and fiber characterization, viability and differentiation enhancing properties of mesenchymal dental pulp stem cell on the barrier was determined. EBNH-RB showed biochemical and structural similarity to natural bone tissue electron microscopy image analysis and x-ray diffrac...

ACS Biomaterials Science & Engineering, Jan 26, 2023

Polymers, Dec 25, 2020

IEEE Access, 2022

Applied sciences, Apr 2, 2021

Polymers, Jan 14, 2021

ACS Biomaterials Science & Engineering, Jan 26, 2023

IEEE Access

Population aging is a global trend, and the highest proportion of elderly people in the workforce... more Population aging is a global trend, and the highest proportion of elderly people in the workforce per unit of population is found in agricultural areas. However, few systematic studies have been conducted on farmer falls in the field of agricultural machinery. This study focuses on the application of classification methods for monitoring devices to detect fall/nonfall movements of farmworkers, where agricultural biomechanical factors are considered in detecting activities of daily living. In this study, we recorded and analyzed original acquisition datasets of signals obtained from two accelerometers and one gyroscope for 40 healthy individuals who performed various falls and activities of daily living (ADLs). Spatial characteristics were used to train the machine-learning classifiers to distinguish between fall and non-fall events. Supervised machine learning experiments evaluated the effectiveness of the proposed approach: the k-nearest neighbors (kNN) and support vector machine (SVM) algorithms achieved roc auc-scores of 0.999 in distinguishing falls and ADLs (binary-class classification). Moreover, an artificial neural network (ANN) classifier showed the highest performance in terms of classification roc auc-scores of 1.0. The evaluation metric demonstrated the highest performance in the analysis and evaluation of the signal obtained from the S2 acceleration sensor with a measurement range of ±16 g. The proposed SVM classifier evaluations showed a 0.988 roc auc-score for sensor tests in multi-class classification, along with the highest performance in terms of the F1-score and Matthews Correlation Coefficient (MCC) over 84% in the multi-class classification model for distinguishing each of ADLs and Fall using ±16 g acceleration sensor. INDEX TERMS Agricultural worker, fall-detection, human behavior recognition, machine learning, wearable sensor.

Applied Sciences, 2021

Polymers, 2021

Polymers, 2020

Post-surgery failure of dental implants due to alveolar bone loss is currently critical, disturbi... more Post-surgery failure of dental implants due to alveolar bone loss is currently critical, disturbing the quality of life of senior dental patients. To overcome this problem, bioceramic or bone graft material is loaded into the defect. However, connective tissue invasion instead of osteogenic tissue limits bone tissue regeneration. The guided bone regeneration concept was adapted to solve this problem and still has room for improvements, such as biochemical similarity or oriented structure. In this article, an aligned electrospun-guided bone regeneration barrier with xenograft equine bone-derived nano hydroxyapatite (EBNH-RB) was fabricated by electrospinning EBNH/PCL solution on high-speed rotating drum collector and fiber characterization, viability and differentiation enhancing properties of mesenchymal dental pulp stem cell on the barrier was determined. EBNH-RB showed biochemical and structural similarity to natural bone tissue electron microscopy image analysis and x-ray diffrac...