• Journal of Biomedical Engineering Research
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• v.31 no.3
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• pp.217-226
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• 2010

The lower limb orthosis with a pneumatic rubber actuator, which is intended for the assistance and the enhancement of muscular activities of lower limbs was developed in this study. Compared to other knee extension assistive devices being developed by other researchers, our device is designed especially for the elderly people and intended only for slight assistance so that the subjects can keep their muscular strength. For the effectiveness of system, muscular activities of major muscles in lower limbs during sit-to-stand (STS) and squat motion were measured and analyzed. Subjects were performed the STS and squat motion with and without lower limb orthosis. We made comparison muscular activities between with and without lower limb orthosis. Lower limb orthosis was controlled using muscular stiffness force feedback that is controlled by muscular activities of the measured muscle from force sensor. For analysis of muscular activities, electromyography of the subjects was measured during STS and squat motion, and these were measured using MP 150(BIOPAC Systems, Inc.). Muscles of interest were rectus femoris(RF), vastus lateralis(VL), vastus medialis(VM) and vastus intermedius(VI) muscles in lower limbs of the right side. A biodex dynamometer was used to measure the maximal concentric isokinetic strength of the knee extensors of wearing and not wearing orthosis on right side. The test were performed using the concentric isokinetic mode of test with the velocity set at 60°/s for muscles around the knee joints. The experimental result showed that muscular activities in lower limbs wearing orthosis using muscular stiffness force of a vastus medialis muscle was reduced and knee extension torque of an knee joint wearing lower limb orthosis was increased. With this, we confirmed the effectiveness of the developed lower limb orthosis.

• Journal of Chest Surgery
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• v.26 no.3
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• pp.163-169
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• 1993

This is the result of the annual statistic analysis of thoracic and cardiovascular surgical cases in 1992 Korea. Overall 17, 520 cases of surgery [11, 732 cases of thoracic surgery by 54 institutes / 5, 788 cases of cardiovascular surgery by 48 institutes] were done. 1. Tumor [N=2, 532] : Lung was the most frequently involved organ by tumor [54.9%],and the remainders were mediastinum [16.2%] / esophagus [14.8%] / chest wall [11.7%] / tracheobronchus [1.3%] / pleura [1.1%] in order. Of 1, 082 cases of primary lung cancer surgery,the frequency of cell type was squamous [62.6%] / adeno [21.6%] / small cell [7.1%] / large cell [2.7%]. Of 411 cases of mediastinal tumor surgery,the frequency of cell type was neurogenic [28.8%] / thymoma [27.6%] / teratoma [17.7%] / congenital cystic [17.2%]. Of 376 cases of esophageal tumor surgery,primary cancer were the most [85.4%]. 2. Infection [N=3, 157] : Pleura was the most frequently involved organ [59.0%],and the remainders were lung [31.3%] / chest wall [8.6%] / mediastinum [1.1%] in order. 3. Miscellaneous [N=6, 043] : Lung and pleural disease esp. pneumothorax [85.1%] was the most frequent surgical indication. The remainders were chest wall anomaly [3.4%] / benign esophageal disease [3.4%] / diaphragmatic pathology [2.4%] / myasthenia [1.4%] in order. Of 85 cases of thymectomy for myasthenia gravis,thymoma was noted in 58.8%. 1. Congenital heart disease [N=3, 363] : The ratio of noncyanotic to cyanotic heart disease was 3:1. Of 2, 516 cases of noncyanotic heart disease,the frequency of disease entity was VSD [44.1%] / ASD [26.0%] / PDA [19.4%] / PS [3.3%],and that of 847 cases of cyanotic heart disease was TOF [29.4%] / ECD [15.6%] / TGA [9.7%] / DORV [7.6%]. Overall mortalities were 2.1% in noncyanotic and 12.2% in cyanotic heart surgery. 2. Acquired heart disease [N=1, 929] : Of 1, 422 cases of valvular surgery,single mitral pathology was the most frequent candidate [48.0%],and total 1, 574 prosthetic valves which were mainly mechanical [95.6%] were used. Of 376 cases of coronary surgery,triple vessel was the most [35.9%],and the frequency of bypassing grafts was great saphenous vein [52.9%] / internal mammary artery [44.7%] / artificial vessel [2.4%]. Overall mortalities were 3.4% in valvular and 4.5% in coronary surgery. 3. Pericardium,Cardiac tumor,Arrhythmia,Aortic aneurysm,Assist device,and Pacemaker : There were no specific changes compared to previous survey1]. This nation-wide inquiry will be continued and reported annually by KTCS Society.

• Progress in Medical Physics
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• v.26 no.1
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• pp.52-58
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• 2015

The automated dental cavity detection program for a new concept intra-oral dental x-ray imaging device, an auxiliary diagnosis system, which is able to assist a dentist to identify dental caries in an early stage and to make an accurate diagnosis, was to be developed. The primary theory of the automatic dental cavity detection program is divided into two algorithms; one is an image segmentation skill to discriminate between a dental cavity and a normal tooth and the other is a computational method to analyze feature of an tooth image and take an advantage of it for detection of dental cavities. In the present study, it is, first, evaluated how accurately the DRLSE (Direct Regularized Level Set Evolution) method extracts demarcation surrounding the dental cavity. In order to evaluate the ability of the developed algorithm to automatically detect dental cavities, 7 tooth phantoms from incisor to molar were fabricated which contained a various form of cavities. Then, dental cavities in the tooth phantom images were analyzed with the developed algorithm. Except for two cavities whose contours were identified partially, the contours of 12 cavities were correctly discriminated by the automated dental caries detection program, which, consequently, proved the practical feasibility of the automatic dental lesion detection algorithm. However, an efficient and enhanced algorithm is required for its application to the actual dental diagnosis since shapes or conditions of the dental caries are different between individuals and complicated. In the future, the automatic dental cavity detection system will be improved adding pattern recognition or machine learning based algorithm which can deal with information of tooth status.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.429-438
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• 1997

Mechanical valve is one of the most widely used implantable artificial organs of which the reliability is so important that its failure means the death of patient. Therefore early noninvasive detection is essentially required, though mechanical valve failure with thrombosis is the most common. The objective of this paper is to detect the thrombosis formation by spectral analysis and neural network. Using microphone and amplifier, we measured the sound from the mechanical valve which is attached to the pneumatic ventricular assist device. The sound was sampled by A/D converter(DaqBook 100) and the periodogram is the main algorithm for obtaining spectrum. We made the thrombosis models using pellethane and silicon and they are thrombosis model on the valvular disk, around the sewing ring and fibrous tissue growth across the orifice of valve. The performance of the measurment system was tested firstly using 1 KHz sinusoidal wave. The measurement system detected well 1KHz spectrum as expected. The spectrum of normal and 5 kinds of thrombotic valve were obtained and primary and secondary peak appeared in each spectrum waveform. We find that the secondary peak changes according to the thrombosis model. So to distinguish the secondary peak of normal and thrombotic valve quantatively, 3 layer back propagation neural network, which contains 7, 000 input node, 20 hidden layer and 1 output was employed The trained neural network can distinguish normal and valve with more than 90% probability. As a conclusion, the noninvasive monitoring of implanted mechanical valve is possible by analysing the acoustical spectrum using neural network algorithm and this method will be applied to the performance evaluation of other implantable artificial organs.

• Journal of the Ergonomics Society of Korea
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• v.33 no.6
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• pp.487-497
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• 2014

Objective: This study aims to develop and evaluate a multi-purpose rollator, which may be used as a seat, as a traditional walker, or as a storage basket for elderly farmers. Background: The rollators on the market are not user-friendly designed and seen inconvenient for elderly farmers to use, although they are sold at considerably high price. Since they lack enough space to load stuffs and are not durable or stable enough, they do not seem to be suitable for elderly farmers to use in rural areas. Method: Two types of methods were used in this study. First, the survey consisted of 19 questions was conducted among elderly farmers in rural areas, after using the developed rollator, to evaluate the usability of the rollator developed in this study. Second, EMG experiment was conducted to compare the existing rollator and developed rollator quantitatively. Through this experiment, we tried to verify the differences of muscle responses, when using the traditional and the developed ones, which have their own brake system, in the ramp. Results: The developed rollator was highly evaluated in most of the questions in the usability survey, except for the 'Weight' category in which the opinions were divided into three different types (Worse: 31%, Similar: 30%, Better: 36%). The result of EMG experiment showed that the existing rollator (7.4%MVC) demands more muscle strength than the developed rollator (5.5%MVC) does. By statistically analyzing the results of upper limb and lower limb respectively, we found out that all the muscles except deltoid in upper limb showed statistically significant differences in muscle activity when using the existing and the developed rollator. However, there was no statistical difference in lower limb muscles. Conclusion: The developed rollator in this study has maximized the functionality of the brake system, the storage and the chair, which were pointed out as the weaknesses of existing rollators. Furthermore, the developed rollator is designed to be more user-friendly, safe, durable, and effective for elderly farmers to use in rural areas, where roads are rough and bumpy. Application: We expect that the emergency brake system developed in this study would be utilized for other convenience equipment, such as strollers and carts, and that it would be able to develop and produce more secure and reliable equipment in the future.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.6
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• pp.251-256
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• 2019

A capsule endoscopy is a medical device that can capture an entire digestive organ from the esophagus to the anus at one time. It produces a vast amount of images consisted of about 8~12 hours in length and more than 50,000 frames on a single examination. However, since the analysis of endoscopic images is performed manually by a medical imaging specialist, the automation requirements of the analysis are increasing to assist diagnosis of the disease in the image. Among them, this study focused on automatic detection of polyp images. A polyp is a protruding lesion that can be found in the gastrointestinal tract. In this paper, we propose a weighted-image generation method to enhance the polyp image learning by multi-scale analysis. It is a way to extract the suspicious region of the polyp through the multi-scale analysis and combine it with the original image to generate a weighted image, that can enhance the polyp image learning. We experimented with SVM and RF which is one of the machine learning methods for 452 pieces of collected data. The F1-score of detecting the polyp with only original images was 89.3%, but when combined with the weighted images generated by the proposed method, the F1-score was improved to about 93.1%.

• Journal of Chest Surgery
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• v.54 no.2
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• pp.99-105
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• 2021

Background: The number of heart transplantations (HTx) is increasing annually. Due to advances in medical and surgical support, the outcomes of HTx are also improving. Extracorporeal circulatory life support (ECLS) provides patients with decompensated heart failure a chance to undergo HTx. A medical approach involving collaboration among experienced experts in different fields should improve the outcomes and prognosis of ECLS-bridged HTx. Methods: From December 2003 to December 2018, 1,465 patients received ECLS at Samsung Medical Center. We excluded patients who had not undergone HTx or underwent repeated transplantations. Patients younger than 18 years were excluded. We also excluded patients who received an implantable durable left ventricular assist device before HTx. In total, 91 patients were included in this study. A multidisciplinary team approach began in March 2013 at our hospital. We divided the patients into 2 groups depending on whether they were treated before or after implementation of the team approach. Results: The 30-day mortality rate was significantly higher in the pre-ECLS team group than in the post-ECLS team group (n=5, 18.5% vs. n=2, 3.1%; p=0.023). The 1-year survival rate was better in the post-ECLS team group than in the pre-ECLS team group (n=57, 89.1% vs. n=19, 70.4%; p=0.023). Conclusion: We found that implementing a multidisciplinary team approach improved the outcomes of ECLS-bridged HTx. Team-based care should be adapted at HTx centers that perform high-risk HTx.

• Journal of Gastric Cancer
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• v.24 no.3
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• pp.327-340
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• 2024

Purpose: Results of initial endoscopic biopsy of gastric lesions often differ from those of the final pathological diagnosis. We evaluated whether an artificial intelligence-based gastric lesion detection and diagnostic system, ENdoscopy as AI-powered Device Computer Aided Diagnosis for Gastroscopy (ENAD CAD-G), could reduce this discrepancy. Materials and Methods: We retrospectively collected 24,948 endoscopic images of early gastric cancers (EGCs), dysplasia, and benign lesions from 9,892 patients who underwent esophagogastroduodenoscopy between 2011 and 2021. The diagnostic performance of ENAD CAD-G was evaluated using the following real-world datasets: patients referred from community clinics with initial biopsy results of atypia (n=154), participants who underwent endoscopic resection for neoplasms (Internal video set, n=140), and participants who underwent endoscopy for screening or suspicion of gastric neoplasm referred from community clinics (External video set, n=296). Results: ENAD CAD-G classified the referred gastric lesions of atypia into EGC (accuracy, 82.47%; 95% confidence interval [CI], 76.46%-88.47%), dysplasia (88.31%; 83.24%-93.39%), and benign lesions (83.12%; 77.20%-89.03%). In the Internal video set, ENAD CAD-G identified dysplasia and EGC with diagnostic accuracies of 88.57% (95% CI, 83.30%-93.84%) and 91.43% (86.79%-96.07%), respectively, compared with an accuracy of 60.71% (52.62%-68.80%) for the initial biopsy results (P<0.001). In the External video set, ENAD CAD-G classified EGC, dysplasia, and benign lesions with diagnostic accuracies of 87.50% (83.73%-91.27%), 90.54% (87.21%-93.87%), and 88.85% (85.27%-92.44%), respectively. Conclusions: ENAD CAD-G is superior to initial biopsy for the detection and diagnosis of gastric lesions that require endoscopic resection. ENAD CAD-G can assist community endoscopists in identifying gastric lesions that require endoscopic resection.

• Korean Journal of Radiology
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• v.25 no.7
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• pp.613-622
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• 2024

Objective: In Korea, radiology has been positioned towards the early adoption of artificial intelligence-based software as medical devices (AI-SaMDs); however, little is known about the current usage, implementation, and future needs of AI-SaMDs. We surveyed the current trends and expectations for AI-SaMDs among members of the Korean Society of Radiology (KSR). Materials and Methods: An anonymous and voluntary online survey was open to all KSR members between April 17 and May 15, 2023. The survey was focused on the experiences of using AI-SaMDs, patterns of usage, levels of satisfaction, and expectations regarding the use of AI-SaMDs, including the roles of the industry, government, and KSR regarding the clinical use of AI-SaMDs. Results: Among the 370 respondents (response rate: 7.7% [370/4792]; 340 board-certified radiologists; 210 from academic institutions), 60.3% (223/370) had experience using AI-SaMDs. The two most common use-case of AI-SaMDs among the respondents were lesion detection (82.1%, 183/223), lesion diagnosis/classification (55.2%, 123/223), with the target imaging modalities being plain radiography (62.3%, 139/223), CT (42.6%, 95/223), mammography (29.1%, 65/223), and MRI (28.7%, 64/223). Most users were satisfied with AI-SaMDs (67.6% [115/170, for improvement of patient management] to 85.1% [189/222, for performance]). Regarding the expansion of clinical applications, most respondents expressed a preference for AI-SaMDs to assist in detection/diagnosis (77.0%, 285/370) and to perform automated measurement/quantification (63.5%, 235/370). Most respondents indicated that future development of AI-SaMDs should focus on improving practice efficiency (81.9%, 303/370) and quality (71.4%, 264/370). Overall, 91.9% of the respondents (340/370) agreed that there is a need for education or guidelines driven by the KSR regarding the use of AI-SaMDs. Conclusion: The penetration rate of AI-SaMDs in clinical practice and the corresponding satisfaction levels were high among members of the KSR. Most AI-SaMDs have been used for lesion detection, diagnosis, and classification. Most respondents requested KSR-driven education or guidelines on the use of AI-SaMDs.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.317-322
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• 2022

The rapid development of information technology is also bringing about many changes in the medical environment. In particular, it is leading the rapid change of medical image information systems using big data and artificial intelligence (AI). The prescription delivery system (OCS), which consists of an electronic medical record (EMR) and a medical image storage and transmission system (PACS), has rapidly changed the medical environment from analog to digital. When combined with multiple solutions, PACS represents a new direction for advancement in security, interoperability, efficiency and automation. Among them, the combination with artificial intelligence (AI) using big data that can improve the quality of images is actively progressing. In particular, AI PACS, a system that can assist in reading medical images using deep learning technology, was developed in cooperation with universities and industries and is being used in hospitals. As such, in line with the rapid changes in the medical image information system in the medical environment, structural changes in the medical market and changes in medical policies to cope with them are also necessary. On the other hand, medical image information is based on a digital medical image transmission device (DICOM) format method, and is divided into a tomographic volume image, a volume image, and a cross-sectional image, a two-dimensional image, according to a generation method. In addition, recently, many medical institutions are rushing to introduce the next-generation integrated medical information system by promoting smart hospital services. The next-generation integrated medical information system is built as a solution that integrates EMR, electronic consent, big data, AI, precision medicine, and interworking with external institutions. It aims to realize research. Korea's medical image information system is at a world-class level thanks to advanced IT technology and government policies. In particular, the PACS solution is the only field exporting medical information technology to the world. In this study, along with the analysis of the medical image information system using big data, the current trend was grasped based on the historical background of the introduction of the medical image information system in Korea, and the future development direction was predicted. In the future, based on DICOM big data accumulated over 20 years, we plan to conduct research that can increase the image read rate by using AI and deep learning algorithms.