• The Korean Society of Law and Medicine
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• v.17 no.2
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• pp.125-144
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• 2016

All forms of Clinical trial should be fully equipped with protection systems for experimental subjects considering their uncertainty and various risks. Existing laws have some regulations in pharmaceutical affairs act and medical device act. Nonetheless, there is a limit to protect the subjects considering law objective to perform administration of medicine. Furthermore, the clinical trial on minor has no direct regulations in pharmaceutical affairs act, but prescribes certain portion in clinical trial assessment guideline on infants or medicine clinical trial management standard, however there is a limit because that is just recommendation not having legal effectiveness. The legislative solution would be possible for legal problems of clinical trial on minor by examining treatment system on minor in organ transplant act and clinical trial on minor in other foreign laws stronger than usual medical practice in terms of degree of human body invasion. I suppose that the control system of clinical trial being done focusing on the pharmaceutical affairs act, medical device act and other guidelines in existing laws system should be resolved by legislating 'trial subject protection law', in addition, this would be well balanced in organ transplant act on protection system of minor organ donors. Furthermore, the judgement on the consent ability and spontaneity in clinical trial on minor should be judged considering maturity and mentality of minor by clinical trial institutional review board based on legislative solution mentioned above.

• Journal of Trauma and Injury
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• v.23 no.2
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• pp.163-169
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• 2010

Purpose: Spinal epidural hematoma (EDH) is a rare condition requiring an urgent diagnosis and management. We describe here the clinical features, magnetic resonance image (MRI) findings, and outcomes of surgery in six patients with spinal EDH. Methods: We retrospectively analyzed six patients who underwent surgery for spinal EDH between April 2004 and May 2010. Preoperative MRI findings within 48 hours of symptom occurrence were analyzed for cord compression, extent of EDH, and presence of vascular abnormalities. Pre- and postoperative neurological status was also assessed comparatively. Results: Our six patients consisted of three men and three women, with a mean age of 70 years (range: 54-88 years), who presented with the back pain or motor weakness. The mean follow-up period was 34 months (range: 2-72 months). Two patients had cardiovascular disease and were taking warfarin, but the others had no history of medical comorbidity. Those two patients taking warfarin had a history of trauma, another one experienced symptoms during a strenuous effort, and the others developed spontaneously. Before surgery, motor power was grade III in three patients, grade 0 in two patients, and normal in one patient. Preoperative MRI showed no vascular abnormalities except for the EDH in any patient. At the last follow-up, all those five patients with motor weakness showed neurological improvement compared to their preoperative status. There were no complications related to surgery. All six patients were able to ambulate with or without an assistive device. Conclusion: Spinal EDH can occur in patients without trauma, bleeding diathesis, or combined vascular pathology. The surgical outcomes of spinal EDH seem to be satisfactory, even in quadriplegic patients.

• 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.

• International Journal of Computer Science & Network Security
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• v.24 no.8
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• pp.32-42
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• 2024

The Internet of Things (IoT) is set to transform patient care by enhancing data collection, analysis, and management through medical sensors and wearable devices. However, the convergence of IoT device vulnerabilities and the sensitivity of healthcare data raises significant data integrity and privacy concerns. In response, this research introduces the Smart-Coord system, a practical and affordable solution for securing healthcare IoT. Smart-Coord leverages blockchain technology and coordinate-based access management to fortify healthcare IoT. It employs IPFS for immutable data storage and intelligent Solidity Ethereum contracts for data integrity and confidentiality, creating a hierarchical, AES-CBC-secured data transmission protocol from IoT devices to blockchain repositories. Our technique uses a unique coordinate system to embed confidentiality and integrity regulations into a single access control model, dictating data access and transfer based on subject-object pairings in a coordinate plane. This dual enforcement technique governs and secures the flow of healthcare IoT information. With its implementation on the Matic network, the Smart-Coord system's computational efficiency and cost-effectiveness are unparalleled. Smart-Coord boasts significantly lower transaction costs and data operation processing times than other blockchain networks, making it a practical and affordable solution. Smart-Coord holds the promise of enhancing IoT-based healthcare system security by managing sensitive health data in a scalable, efficient, and secure manner. The Smart-Coord framework heralds a new era in healthcare IoT adoption, expertly managing data integrity, confidentiality, and accessibility to ensure a secure, reliable digital environment for patient data management.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.691-697
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• 2013

Recently, u-healthcare device is developed and commercialized for healthcare management and emergency medical. The kinds of the measurable biomedical signals on the device are electrocardiogram, skin temperature, pulse oxygen, heart rate, respiration, etc. Specially, the photoplethysmograph(PPG) signal of these signals is the important signal in measuring oxygen, heart rate and peripheral vascular compliance. The accuracy of PPG signal reduce from influence of the motion artifacts that generated from the movements of user or patient. Therefore, this study suggests a new method to remove the motion artifact that is using optical power modulation and ICA(Independent Component Analysis). For analyzing the proposed method, we used variety of noises made by artificially. In the results of experiments, the proposed method showed good performances than an adaptive filter.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.765-773
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• 2011

Today, as the number of applicants for admission decreases, competition among universities is deepening in Korea. Especially, the existence of local universities has led to intense competition to increase the enrollment rate of new students and reduce dropout rate. To survive in this competition, local universities are making various efforts; however, the primary problem is improving their educational service quality. In this study, we have developed a device to measure educational service quality which can be applied to the field of higher education, and factors that determine educational service quality are dragged through this device. In addition, this research identifies which statistically significant factors play a part in overall satisfaction and word of mouth effect, and interprets 29 quality attributes using importance-satisfaction transformed index.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.209-215
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• 2019

The most important personal health care in digital health care is a very important issue mainly for chronic diseases. Therefore, it is important to develop a simple wearable device for real-time health management. Existing blood pressure estimation wearable devices use PPG characteristics to analyze PTT and propose blood pressure estimation algorithms. However, the influencing factors of the algorithm such as the reproducibility of PPG, whether to apply various PTTs, and variables generated from the physical differences of the measurers are actually very complex. Therefore, in this study, the correlation between PTT, SBP, and DBP was analyzed, and it was designed to use PPG sensors for device miniaturization. The blood pressure estimation algorithm took into account differences in PPG, heart rate, and personal variables.

• Journal of Information Technology Applications and Management
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• v.26 no.1
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• pp.21-38
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• 2019

This study starts from the question, "Are people of the age 60 and over equally 'old?' "As the aging population has rapidly become a global issue, it is a timely question to think about whether it is appropriate to classify people aged 60 and over as senior citizens monolithically based on their chronological age. Thanks to the advancement of medical technology and ever-increasing life expectancy, there may be more differences than we thought in terms of cognitive and behavioral patterns among the elderly population. In order to further investigate this question, this study focuses on technology acceptance behavior of 132 participants over the age of 60 towards a wearable healthcare device. The results show that there were interesting behavioral differences among participants depending on their cognitive capabilities. More specifically, participants with high cognitive capability (Superagers) consider the usefulness and the social aspects (social norm and image) of using wearable healthcare technology. Whereas for those with relatively low cognitive capability (non-Superagers), usefulness of using the technology was not a significant factor, and they mainly considered social norm and image. Our findings imply that the current monolithic application of chronological age to classify the elderly population should be carefully reconsidered because people aged over 60 years old may not always share homogeneous cognitive and behavioral patterns.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.1-9
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• 2022

In this paper, we propose the Deep Learning-Based Companion Animal Abnormal Behavior Detection Service, which using video and sensor data. Due to the recent increase in households with companion animals, the pet tech industry with artificial intelligence is growing in the existing food and medical-oriented companion animal market. In this study, companion animal behavior was classified and abnormal behavior was detected based on a deep learning model using various data for health management of companion animals through artificial intelligence. Video data and sensor data of companion animals are collected using CCTV and the manufactured pet wearable device, and used as input data for the model. Image data was processed by combining the YOLO(You Only Look Once) model and DeepLabCut for extracting joint coordinates to detect companion animal objects for behavior classification. Also, in order to process sensor data, GAT(Graph Attention Network), which can identify the correlation and characteristics of each sensor, was used.

• Information Systems Review
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• v.26 no.2
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• pp.137-153
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• 2024

This study aimed to propose early diagnosis and management of dementia, which is increasing in aging societies, and suggest commercial utilization strategies by leveraging digital healthcare technologies, particularly lifelog data collected from wearable devices. By introducing new approaches to dementia prevention and management, this study sought to contribute to the field of dementia prediction and prevention. The research utilized 12,184 pieces of lifelog information (sleep and activity data) and dementia diagnosis data collected from 174 individuals aged between 60 and 80, based on medical pathological diagnoses. During the research process, a multidimensional dataset including sleep and activity data was standardized, and various machine learning algorithms were analyzed, with the random forest model showing the highest ROC-AUC score, indicating superior performance. Furthermore, an ablation test was conducted to evaluate the impact of excluding variables related to sleep and activity on the model's predictive power, confirming that regular sleep and activity have a significant influence on dementia prevention. Lastly, by exploring the potential for commercial utilization strategies of the developed model, the study proposed new directions for the commercial spread of dementia prevention systems.