• 전자공학회논문지SC
• /
• 제49권2호
• /
• pp.38-45
• /
• 2012

선천성 난청으로 태어난 아이를 조기에 진단하여 가능한 빨리 적절한 치료를 해줌으로써 치료 효과를 극대화하고, 이후에 발생되는 사회적 비용을 최소화할 수 있기 때문에 신생아로부터 난청 이상 유무를 객관적으로 판별하는 검사 장비가 필요하다. 대표적인 것으로 청성뇌간반응(auditory brainstem response, ABR) 검사가 있으나 클릭음(click sound)에 대한 반응으로 주파수 특이성이 없고 고주파수 대역에 대한 청력을 주로 반영하는 단점이 있다. 청성지속반응(auditory steady-state response, ASSR) 검사는 주파수 특이도는 좋으나 오진의 가능성이 조금 높다. 이러한 단점을 보완하여 청성뇌간반응 검사와 청성지속반응 검사를 하나의 시스템에서 측정하고, Fsp와 F-test 분석을 통하여 객관적 지표를 보여주는 시스템을 제안하였다. 하드웨어 구성요소를 최소화하고 소프트웨어 역할을 강화하여 추후 하드웨어 수정 없이 소프트웨어의 수정만으로 다양한 검사가 가능하도록 설계하였다. 제안한 시스템의 객관적 평가 기능은 정상인 10명을 대상으로 한 실험을 통하여 검증하였다.

• 대한임상검사과학회지
• /
• 제45권4호
• /
• pp.149-153
• /
• 2013

Candidiasis is a fungal infection of the most common causes; generally, opportunistic infections occur often in patients with weakened immune systems. Because of high rates in fungal infection patients and increasing frequency of being isolated from clinical materials, quickly identifying of Candida albicans is critical. By identifying 404 yeast cell strains of referred samples via API 20C kits, NGL and PRO tests and Germ tube (GT) test were conducted and compared. In the 3.0 McFarland yeast cells, 0.1% ${\rho}-nitrophenyl-N-acetyl-{\beta}-D-galactosaminide$ (NGL) and 0.04% ${\small{L}}$-proline ${\beta}$-naphtylamide (PRO) were each put in test tubes and incubated at $35^{\circ}C$ for 15, 30, 60 and 90 minutes. Afterwards, 1 drop of 2% NaOH was applied, and if the color turned yellow; it was positive for NGL test. Afterwards, 1% ${\rho}$-dimethylaminocinnamaldehyde was applied, and if the upper layer turned pink or red, it was positive for PRO test. NGL and PRO tests were conducted for all C. albicans and identified accurately within 30 minutes. In NGL, PRO test, false-positive, negative were not seen, whereas, GT test showed false-positive in 1 strain and false-negative in 3 strains. Therefore, sensitivity and specificity of NGL, PRO tests were 100% and 99.5%, respectively, and positive and negative predictive rate were 99.5% and 100%, respectively. However, GT test sensitivity and specificity were 98.5% and 99.5%, respectively, and positive and negative predictive rates were 99.5% and 98.5%, respectively. In conclusion, NGL, PRO tests are better than GT tests for sensitivity and specificity, therefore, these reliable tests will be useful in clinical laboratories.

• Clinical and Experimental Pediatrics
• /
• 제60권7호
• /
• pp.208-215
• /
• 2017

Purpose: Activation of Toll-like receptor 2 (TLR2) present on circulating monocytes in patients with Kawasaki disease (KD) can lead to the production of proinflammatory cytokines and interleukin-10 (IL-10). We aimed to determine the association of the frequency of circulating TLR2+/ CD14+ monocytes (FTLR2%) with the outcomes of KD, as well as to compare FTLR2% to the usefulness of sIL-10. Methods: The FTLR2% in patients with KD was measured by flow cytometry. Serum levels of IL-10 (sIL-10) were determined in 31 patients with KD before the initial treatment with intravenous immunoglobulin (IVIG) and in 21 febrile controls by using enzyme-linked immunosorbent assay. Patients were classified as having coronary artery lesions (CALs) based on the maximal internal diameters of the proximal right coronary artery and proximal left anterior descending coronary artery one month after the initial diagnosis. Results: We found that FTLR2% greater than 92.62% predicted CALs with 80% sensitivity and 68.4% specificity, whereas FTLR2% more than 94.61% predicted IVIG resistance with 66.7% sensitivity and 71.4% specificity. Moreover, sIL-10 more than 15.52 pg/mL predicted CALs and IVIG resistance with 40% and 66.7% sensitivity, respectively, and 73.7% and 76.2% specificity, respectively. Conclusion: We showed that measuring FTLR2% before the initial treatment could be useful in predicting CAL development with better sensitivity than sIL-10 and with results comparable to sIL-10 results for the prediction of IVIG resistance in patients with KD. However, further studies are necessary to validate FTLR2% as a marker of prognosis and severity of KD.

• The Korean Journal of Pain
• /
• 제32권2호
• /
• pp.120-128
• /
• 2019

Background: We aimed to explore the American College of Rheumatology (ACR) 1990 and 2011 fibromyalgia (FM) classification criteria's items and the components of Fibromyalgia Impact Questionnaire (FIQ) to identify features best discriminating FM features. Finally, we developed a combined FM diagnostic (C-FM) model using the FM's key features. Methods: The means and frequency on tender points (TPs), ACR 2011 components and FIQ items were calculated in the FM and non-FM (osteoarthritis [OA] and non-OA) patients. Then, two-step multiple logistic regression analysis was performed to order these variables according to their maximal statistical contribution in predicting group membership. Partial correlations assessed their unique contribution, and two-group discriminant analysis provided a classification table. Using receiver operator characteristic analyses, we determined the sensitivity and specificity of the final model. Results: A total of 172 patients with FM, 75 with OA and 21 with periarthritis or regional pain syndromes were enrolled. Two steps multiple logistic regression analysis identified 8 key features of FM which accounted for 64.8% of variance associated with FM group membership: lateral epicondyle TP with variance percentages (36.9%), neck pain (14.5%), fatigue (4.7%), insomnia (3%), upper back pain (2.2%), shoulder pain (1.5%), gluteal TP (1.2%), and FIQ fatigue (0.9%). The C-FM model demonstrated a 91.4% correct classification rate, 91.9% for sensitivity and 91.7% for specificity. Conclusions: The C-FM model can accurately detect FM patients among other pain disorders. Re-inclusion of TPs along with saving of FM main symptoms in the C-FM model is a unique feature of this model.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제55권5호
• /
• pp.240-247
• /
• 2006

Frequent arousals during sleep degrade the quality of sleep and result in sleep fragmentation. Visual inspection of physiological signals to detect the arousal events is cumbersome and time-consuming work. The purpose of this study is to develop an automatic algorithm to detect the arousal events. The proposed method is based on time-frequency analysis and the support vector machine classifier using single channel electroencephalogram (EEG). To extract features, first we computed 6 indices to find out the informations of a subject's sleep states. Next powers of each of 4 frequency bands were computed using spectrogram of arousal region. And finally we computed variations of power of EEG frequency to detect arousals. The performance has been assessed using polysomnographic (PSG) recordings of twenty patients with sleep apnea, snoring and excessive daytime sleepiness (EDS). We could obtain sensitivity of 79.65%, specificity of 89.52% for the data sets. We have shown that proposed method was effective for detecting the arousal events.

• 대한한의진단학회지
• /
• 제16권2호
• /
• pp.33-46
• /
• 2012

Purpose : Nowadays excrement-related disease that repeats constipation and diarrhea is on the increase due to the change of dietary and lack of exercise, etc. We analyzed Bangyakhappyeon in order to find out the materia medica which is used for the excrement patterns. Methods : The database used in present thesisis consist of disease pattern, nature of medicinals and materia medica from Bangyakhappyeon was constructed. We analyzed the nature of medicinals of excrement patterns(or symptom) by frequency analysis and network analysis, and also searched main materia medica of excrement patterns(or symptom) by frequency analysis and rule mining. Results : We analyzed the nature of medicinals of excrement patterns(or symptom) in Bangyakhappyeon. And we researched the high frequency materia medica, high specificity materia medica and high frequent paired-drugs as main materia medica of excrement patterns(or symptom). Conclusion : This study found the information about frequency relationship between excrement patterns(or symptoms) and materia medica.

• 한국정보통신학회논문지
• /
• 제15권12호
• /
• pp.2655-2663
• /
• 2011

지금까지 심방세동을 검출하는 방법은 P파의 형태, 시간 주파수 영역 분석법이 주를 이루었다. 하지만 P파는 잡음의 영향을 많이 받는 환경에서는 검출의 정확도가 떨어지며, 시간 주파수 영역 분석법은 RR 간격에 따라 변화하는 불규칙적 리듬에 관한 정보를 정확하게 얻지 못하는 단점이 있다. 본 연구에서는, P파의 형태는 고려하지 않고, 불규칙 RR 간격 리듬의 비선형적 특성 분석을 통한 심방세동 검출 알고리즘을 제안한다. 이를 위해 불규칙 RR 간격 리듬을 다양성, 무작위성, 복잡성으로 각각 정의하고 제곱평균제곱근(RMSSD), 전환점비(TPR), 표본 엔트로비(SpEn)의 3가지 비선형적 특성 분석을 통하여 심방세동을 분류하였다. 제안된 알고리즘의 검출 성능을 평가하기 위해 3가지 통계치의 최적값을 설정하고 MIT-BIH 심방세동 데이터베이스와 부정맥 데이터베이스를 이용하여 실험하였다. 성능 평가 결과, MIT-BIH 심방세동 데이터베이스에 대해서는 민감도(sensitivity:94.5%), 특이도(specificity:96.2%)를 각각 나타내었으며, 부정맥 데이터베이스에 대해서는 민감도(89.8%), 특이도(89.62%)를 각각 나타내었다.

• 대한의용생체공학회:의공학회지
• /
• 제36권5호
• /
• pp.169-176
• /
• 2015

Implantable closed-loop epilepsy controllers require ideally both accurate epileptic seizure detection and low power consumption. On-chip oscillators can be used in implantable devices because they consume less power than other oscillators such as crystal oscillators. In this study, we investigated the tolerable error range of a lower power on-chip oscillator without losing the accuracy of seizure detection. We used 24 ictal and 14 interictal intracranial electroencephalographic segments recorded from epilepsy surgery patients. The performance variations with respect to oscillator frequency errors were estimated in terms of specificity, modified sensitivity, and detection timing difference of seizure onset using Generic Osorio Frei Algorithm. The frequency errors of on-chip oscillators were set at ${\pm}10%$ as the worst case. Our results showed that an oscillator error of ${\pm}10%$ affected both specificity and modified sensitivity by less than 3%. In addition, seizure onsets were detected with errors earlier or later than without errors and the average detection timing difference varied within less than 0.5 s range. The results suggest that on-chip oscillators could be useful for low-power implantable devices without error compensation circuitry requiring significant additional power. These findings could help the design of closed-loop systems with a seizure detector and automated stimulators for intractable epilepsy patients.

• The Plant Pathology Journal
• /
• 제16권1호
• /
• pp.1-8
• /
• 2000

Worldwide, rice blast, caused by Magnaporthe grisea (Hebert) Barr. (anamorph, Pyricularia grisea Sacc.), is one of the most economically devastating crop diseases. Management of rice blast through the breeding of blast-resistant varieties has had only limited xuccess due to the frequent breakdown of resistance under field conditions (Bonman etal., 1992; Correa-Victoria and Zeigler, 1991; Kiyosawa, 1982). The frequent variation of race in pathogen populations has been proposed as the principal mechanism involved in the loss of resistance (Ou, 1980). Although it is generally accepted that race change in M. grisea occurs in nature, the degree of its variability has been a controversial subject. A number of studies have reported the appearance of new races at extremely high rates (Giatgong and Frederiksen, 1968; Ou and Ayad, 1968; Ou et al., 1970; Ou et al., 1971). Various potential mechanisms, including heterokaryosis (Suzuki, 1965), parasexual recombination (Genovesi and Magill, 1976), and aneuploidy (Kameswar Row et al., 1985; Ou, 1980), have been proposed to explain frequent race changes. In contrast, other studies have shown that although race change could occur, its frequency was much lower than that predicted by earlier studies (Bonman et al., 1987; Latterell and Rossi, 1986; Marchetti et al., 1976). Although questions about the frequency of race changes in M. grisea remain unanswered, the application of molecular genetic tools to study the fungus, ranging from its genes controlling host specificity to its population sturctures and dynamics, have begun to provide new insights into the potential mechanisms underlying race variation. In this review we aim to provide an overview on (a) the molecular basis of host specificity of M. grisea, (b) the population structure and dynamics of rice pathogens, and (c) the nature and mechanisms of genetic changes underpinning virulence variation in M. grisea.

• 대한의용생체공학회:의공학회지
• /
• 제44권6호
• /
• pp.384-391
• /
• 2023

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 proposed 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 frequency of 60Hz. A 5Hz low-pass filter was applied to the IMU data to remove high-frequency noise. Sum vector magnitude 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).