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김동권,김용락,김행식 대한마취과학회 1978 Korean Journal of Anesthesiology Vol.11 No.1
Among the transfusion reaction, the hemolytic reactien due to mismatched blood transfusion is a fatal complication. After immediate fatel disaster, the renal complication is still life threatening snd so its prevention and management are very important. We experienced five cases of acute renal failure and, two of five patients were developed at the SNU hospital and the remainders were transfered to the SNU hospital from local hospital. Two of five patients were showed oliguric renal failures and the remamders were showed non-o-liguric renal failures. All five patients were discharged without compliication. We summeriie the labaratory data of the five patients during hospitalization and together reviewed with the literatures.
임계값 기반 충격 전 낙상검출 및 실제 노인 데이터셋을 사용한 검증
김동권,이승희,구범모,양수민,김영호 대한의용생체공학회 2023 의공학회지 Vol.44 No.6
Among the elderly, fatal injuries and deaths are significantly attributed to falls. Therefore, a pre-impact fall detection system is necessary for injury prevention. In this study, a robust threshold-based algorithm was pro- posed for pre-impact fall detection, reducing false positives in highly dynamic daily-living movements. The algorithm was validated using public datasets (KFall and FARSEEING) that include the real-world elderly fall. A 6-axis IMU sensor (Movella Dot, Movella, Netherlands) was attached to S2 of 20 healthy adults (aged 22.0±1.9years, height 164.9±5.9cm, weight 61.4±17.1kg) to measure 14 activities of daily living and 11 fall movements at a sampling fre- quency of 60Hz. A 5Hz low-pass filter was applied to the IMU data to remove high-frequency noise. Sum vector mag- nitude of acceleration and angular velocity, roll, pitch, and vertical velocity were extracted as feature vector. The proposed algorithm showed an accuracy 98.3%, a sensitivity 100%, a specificity 97.0%, and an average lead-time 311±99ms with our experimental data. When evaluated using the KFall public dataset, an accuracy in adult data improved to 99.5% compared to recent studies, and for the elderly data, a specificity of 100% was achieved. When evaluated using FARSEEING real-world elderly fall data without separate segmentation, it showed a sensitivity of 71.4% (5/7).