젖산 농도와 관류 비를 이용한 흰쥐에서의 출혈성 쇼크의 사망 예측 지표 개발

Purpose: We proposed a new index for predicting death resulting from hemorrhagic shock, which was calculated by dividing measured lactate concentration by perfusion. Methods: Using 24 Sprague-Dawley (S-D) rats, we induced uncontrolled hemorrhage and then measured blood lactate concentration and perfusion in addition to vital signs such as heart rate, blood pressure, respiration rate and temperature. Perfusion and lactate concentration were measured by laser Doppler flowmetry and a lactate concentration meter, respectively. We collected the data for 15 min, which consisted of 3 intervals after homeostasis, and thus obtained a new index. Results: The proposed index revealed an earlier death prediction than lactate concentration alone with the same timing as perfusion. The new index showed generally better sensitivity, specificity and accuracy than lactate concentration and perfusion. Using a receiver operating characteristic curve method, the mortality prediction with the proposed index resulted in a sensitivity of 98.0%, specificity of 90.0%, and accuracy of 93.7%. The mortality prediction with the proposed index resulted in a sensitivity of 98.0%, specificity of 90.0% and accuracy of 93.7%. Conclusion: This index could provide physicians, in emergency situations, with early and accurate mortality predictions for cases of human hemorrhagic shock.ope

A Survival Prediction Model for Rats with Hemorrhagic Shock Using an Artificial Neural Network

Purpose: To achieve early diagnosis of hemorrhagic shock using a survival prediction model in rats. Methods: We measured heart rate, mean arterial pressure, respiration rate and temperature in 45 Sprague-Dawley rats, and obtained an artificial neural network model for predicting survival rates. Results: Area under the receiver operating characteristic (ROC) curves was 0.992. Applying the determined optimal boundary value of 0.47, the sensitivity and specificity of survival prediction were 98.4 and 96.6%, respectively. Conclusion: Because this artificial neural network predicts quite accurate survival rates for rats subjected to fixed-volume hemorrhagic shock, and does so with simple measurements of systolic blood pressure (SBP), mean arterial pressure (MAP), heart rate (HR), respiration rate (RR), and temperature (TEMP), it could provide early diagnosis and effective treatment for hemorrhagic shock if this artificial neural network is applicable to humans.ope

A New Shock Index for Predicting Survival of Rats with Hemorrhagic Shock Using Perfusion and Lactate Concentration Ratio

Hemorrhagic shock is a clinically widespread syndrome characterized by inadequate oxygenation and supply. It is important to diagnose hemorrhagic shock in its early stage for improving treatment effects and survival rate. However, an accurate diagnosis and treatment could be delayed in the early stage of hemorrhagic shock by evaluating only vital signs such as heart rate and blood pressure. There have been many studies for the early diagnosis of hemorrhagic shock, reporting that lactate concentration and perfusion were useful variables for tissue hypoxia and metabolic acidosis. In this study, we measured both perfusion using a laser Doppler flowmeter and lactate concentration from the volume controlled hemorrhagic shock using rats. We also proposed a new shock index which was calculated by dividing lactate concentration by perfusion for early diagnosis. As a result of the survival prediction by the proposed index with the receiver operating characteristic curve method, the sensitivity, specificity, and accuracy of survival were 90.0, 96.7 and 94.0%, respectively. The proposed index showed the fastest significant difference among the other parameters such as blood pressure and heart rate. It could offer early diagnosis and effective treatment for human hemorrhagic shock if it is applicable to humans.ope

Comparison of Survival Prediction of Rats with Hemorrhagic Shocks Using Artificial Neural Network and Support Vector Machine

shock makes it possible for physician to treat successfully. The objective of this paper was to select an optimal classifier model using physiological signals from rats measured during hemorrhagic experiment. This data set was used to train and predict survival rate using artificial neural network (ANN) and support vector machine (SVM). To avoid over-fitting, we chose the best classifier according to performance measured by a 10-fold cross validation method. As a result, we selected ANN having three hidden nodes with one hidden layer and SVM with Gaussian kernel function as trained prediction model, and the ANN showed 88.9 % of sensitivity, 96.7 % of specificity, 92.0 % of accuracy and the SVM provided 97.8 % of sensitivity, 95.0 % of specificity, 96.7 % of accuracy. Therefore, SVM was better than ANN for survival prediction.ope

Cardio-pulmonary effects of RF fields emitted from WCDMA mobile phones

With rapid increasing usage of smart phones, social concerns have arisen about the possible effects of electromagnetic fields emitted from wideband code division multiple access(WCDMA) mobile phones on human health. The number of people with self-reported electromagnetic hypersensitivity(EHS) who complain of various subjective symptoms such as headache, insomnia etc. has also recently increased. However, it is unclear whether EHS results from physiological or other origins. In this double-blinded study, we investigated physiological changes such as heart rate, respiration rate, and heart rate variability with real and sham exposures for 15 EHS and 17 non-EHS persons using a module inside a dummy phone. Experiment was conducted using a WCDMA module with average power of 24 dBm at 1950 MHz with the specific absorption rate of 1.57 W/kg using a headphone for 32 min. As a conclusion, WCDMA RF exposure did not have any effects on the physiological variables in either group.ope

스마트안전 리빙랩에서 사용자경험 평가를 위한 방법론 개발

MasterSmart Safety Living Lab is a living lab facility, constructed and operated by KITECH in Korea, to support the evaluation, improvement and certification of smart safety products and services. In this Living Lab, user experience (UX) is evaluated to enhance the user acceptance and market competitiveness of products and services. This study developed a UX evaluation methodology that accommodates the characteristics of the Living Lab and smart safety products and services in order to carry out the UX evaluation systematically and efficiently in the Smart Safety Living Lab. This thesis aims to develop a User Experience Evaluation Methodology for Smart Safety Living Lab (SSLL-UXEM). SSLL-UXEM is a guideline and toolkit that enable UX evaluators to conduct UX evaluation of products and services systematically and efficiently. The methodology consists of a structured process for UX evaluation, and also provides a guideline for conducting each step of the process and a set of forms for recording the major items in each step. The usefulness of the proposed methodology is shown via an expert evaluation and case studies. SSLL-UXEM is expected to improve the efficiency and the consistency of the UX evaluation results. From a practical perspective, this research aims to contribute to evaluating a smart safety products and services and providing a basis for UX evaluation in various living labs in the future

Origins of electromagnetic hypersensitivity to 60 Hz magnetic fields: A provocation study

Abstract With increasing electrical device usage, social concerns about the possible effects of 60 Hz electromagnetic fields on human health have increased. The number of people with self-attributed electromagnetic hypersensitivity (EHS) who complain of various subjective symptoms such as headache and insomnia has also increased. However, it is unclear whether EHS results from physiological or other origins. In this double-blinded study, we simultaneously investigated physiological changes (heart rate, respiration rate, and heart rate variability), subjective symptoms, and perception of the magnetic field to assess origins of the subjective symptoms. Two volunteer groups of 15 self-reported EHS and 16 non-EHS individuals were tested with exposure to sham and real (60 Hz, 12.5 µT) magnetic fields for 30 min. Magnetic field exposure did not have any effects on physiological parameters or eight subjective symptoms in either group. There was also no evidence that the EHS group perceived the magnetic field better than the non-EHS group. In conclusion, the subjective symptoms did not result from the 60 Hz, 12.5 µT magnetic field exposures but from other non-physiological factorsope