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중증외상환자에서 동반된 척추 및 척수손상에 대한 임상적 분석
정주호,김대용,박창민 고신대학교 의과대학 2009 고신대학교 의과대학 학술지 Vol.24 No.2
Background: The traumatic spinal injury is an extremely serious condition that often results in death or disabilities. We investigated epidemiological data on spinal injuries specifically in severe trauma patient admitted to a preliminarily proposed Major Trauma Distinctive Care Center. Materials and Methods: We reviewed the medical records of 28 severe trauma patients (Injury Severity Score >15) with traumatic spinal (vertebral column or spinal cord) injuries admitted to the emergency medical center in the Kosin University Gospel Hospital (KUGH) from January to October 2009, retrospectively. Results: The ratio of male to female was 3 to 1. The mean age was 46.5 years. The leading causes of traumatic spinal injury are falls (39.4%). The most common level of injury was cervical (35%) and lumbar (35%) spine. Spinal fracture accounts for 47.8% of all traumatic spinal injury, spinal cord injury 37%, dislocation 8.7% and HNP (herniated nucleus pulposus) 6.5%. The most common type of spinal body fracture was compressive type (58.8%). In spinal cord injury, incomplete injury (64.7%) was more common than complete injury (35.3%) and quadriplegia accounts for 47.1% and paraplegia 52.9%. The most common associated injury was rib fracture & pneumohemothorax (31.2%). 5 patients underwent surgery earlier than 24 hours. The average Injury Severity Score (ISS) was 24.2 and the average Abbreviated Injury Scale Score (AISS) was 3.5. Conclusion: This clinical analysis is the first basic study for understanding the patterns of the spinal injuries in the severe trauma patients admitted to KUGH emergency medical center which was preliminarily proposed as Major Trauma Distinctive Care Center by Ministry for Health, Welfare and Family Affairs in November 2008. Although this study has only small number of cases during relatively short term period, it will be touchstone of succeeding analysis of spinal injuries in the severe trauma patients. Therefore continuous additional data collections and more precise clinical investigations are suggested
지능형 오디오 및 비전 패턴 기반 1인 가구 이상 징후 탐지 알고리즘
정주호,안준호 한국인터넷정보학회 2019 인터넷정보학회논문지 Vol.20 No.1
As the number of single-person households increases, it is not easy to ask for help alone if a single-person household is severely injured in the home. This paper detects abnormal event when members of a single household in the home are seriously injured. It proposes an vision detection algorithm that analyzes and recognizes patterns through videos that are collected based on home CCTV. And proposes audio detection algorithms that analyze and recognize patterns of sound that occur in households based on Smartphones. If only each algorithm is used, shortcomings exist and it is difficult to detect situations such as serious injuries in a wide area. So I propose a fusion method that effectively combines the two algorithms. The performance of the detection algorithm and the precise detection performance of the proposed fusion method were evaluated, respectively. 1인 가구의 수가 증가함에 따라 1인 가구의 구성원이 집안에서 심각한 부상을 당할 경우 혼자 도움을 청하기 쉽지 않다. 본 연구는 집안에서 1인 가구의 구성원이 심각한 부상을 당했을 때 비일상적인 상태를 탐지한다. 홈 CCTV를 기반으로 수집된 영상을 통해 패턴을 분석 및 인식하는 영상 탐지 알고리즘을 제안한다. 또한, 스마트폰을 기반으로 집안에서 발생하는 소리의 패턴을 분석 및 인식하는 음성 탐지 알고리즘도 제안한다. 각각의 알고리즘만 사용할 경우, 단점이 존재하여 넓은 영역에서 심각한 부상과 같은 상황을 탐지하기 어렵다. 그래서 두 알고리즘을 효율적으로 결합한 융합 방식을 제안한다. 각각 탐지 알고리즘의 성능과 제안된 융합 방식의 정확한 탐지 성능을 평가했다.