• Journal of Biomedical Engineering Research
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• v.36 no.5
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• pp.169-176
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• 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
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• v.16 no.1
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• pp.1-8
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• 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.

• Journal of Biomedical Engineering Research
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• v.44 no.6
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• pp.384-391
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• 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).

• Speech Sciences
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• v.15 no.1
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• pp.63-72
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• 2008

Various acoustic features were extracted and analyzed to estimate the inter- and intra-speaker variability of emotional speech. Tokens of vowel /a/ from sentences spoken with different modes of emotion (sadness, neutral, happiness, fear and anger) were analyzed. All of the acoustic features (fundamental frequency, spectral slope, HNR, H1-A1 and formant frequency) indicated greater contribution to inter- than intra-speaker variability across all emotions. Each acoustic feature of speech signal showed a different degree of contribution to speaker discrimination in different emotional modes. Sadness and neutral indicated greater speaker discrimination than other emotional modes (happiness, fear, anger in descending order of F-ratio). In other words, the speaker specificity was better represented in sadness and neutral than in happiness, fear and anger with any of the acoustic features.

• Korean Journal of Health Education and Promotion
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• v.6 no.1
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• pp.60-65
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• 1989

A statistical analysis was made on 15,971 surgically operated patients at D-Medical Center in the year of 1978 and 1988. 1,416 cancer patients among them were classified by sex, age, and malignant tumor site. The obtained results indicated that trend of male cancer was generally similar to the results of nation wide study. But, specific phenomenon was found in the case of female cancer in Daegu-Kyungbuk area. Among females the frequency rank was uterine cervix (35.77%), breast (17.97%), stomach (11.65%) in 1988. The frequency of uterine cervix was higher than other area. Breast cancer was highly ranked tumor compare with other area, and its age distribution also appeared in much younger decade.

• Korean Journal of Acupuncture
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• v.31 no.2
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• pp.66-78
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• 2014

Objectives : The specificity of acupuncture point has been a highly controversial subject. Existing researches said that ion-distribution differences are observed on the acupuncture point. This study was conducted under the assumption that multiple ionic changes induced by muscle fatigue would be different between the acupuncture point with non-acupuncture point. Methods : To induce the identical fatigue, twenty subjects performed the knee extension/flexion exercise using the Biodex System 3. ST32 and ST33 as well as adjacent non-acupuncture points were selected. We measured blood lactate and analyzed the median frequency(MF) and peak torque. To obtain the information on the extracellular fluid(ECW), intracellular fluid(ICW) and cell membrane indirectly, we used the multi-frequency bioelectrical impedance analysis(MF-BIA) method. Results : MF, peak torque and blood lactate level of all measurement sites were gradually returned to normal. Re resistance of ST32 had a stronger response, but a non-acupuncture point adjacent to ST33 had a larger response up to 20 minutes post exercise. Ri resistances were similar for both acupoints and non-acupoints. The $C_m$ capacitance of ST32 had a stronger response after inducing fatigue, but ST33 had a smaller response than a non-acupuncture point adjacent to it. Conclusions : In comparison with before and after inducing fatigue, the specificity of acupuncture points was not clearly observed. Hence, we concluded that the body composition factors extraction method had the limitation as a method of finding the specificity of acupuncture points by inducing fatigue.

• Journal of Biomedical Engineering Research
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• v.34 no.4
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• pp.182-188
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• 2013

This study aims to develop a practical algorithm which can detect freezing of gait(FOG) in patients with Parkinson's disease(PD). Eighteen PD patients($68.8{\pm}11.1yrs.$) participated in this study, and three($68.7{\pm}4.0yrs.$) of them showed FOG. We suggested two time-domain algorithms(with 1-axis or 3-axes acceleration signals) and compared them with the frequency-domain algorithm in the literature. We measured the acceleration of left foot with a 3-axis accelerometer inserted at the insole of a shoe. In the time-domain method, the root-mean-square(RMS) acceleration was calculated in a moving window of 4s and FOG was defined as the periods during which RMS accelerations located within FOG range. The parameters in each algorithm were optimized for each subject using the simulated annealing method. The sensitivity and specificity were same, i.e., $89{\pm}8%$ for the time-domain method with 1-axis acceleration and were $91{\pm}7%$ and $90{\pm}8%$ for the time-domain method with 3-axes acceleration, respectively. Both performances were better in the time-domain methods than in the frequency-domain method although the results were statistically insignificant. The amount of calculation in the time-domain method was much smaller than in the frequency-domain method. Therefore it is expected that the suggested time domain algorithm would be advantageous in the systematic implementation of FOG detection.

• Journal of Sensor Science and Technology
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• v.22 no.5
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• pp.338-345
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• 2013

Premature ventricular contractions are the most common of all arrhythmias and may cause more serious situation like ventricular fibrillation and ventricular tachycardia in some patients. Therefore, the detection of this arrhythmia becomes crucial in the early diagnosis and the prevention of possible life threatening cardiac diseases. Most methods for detecting arrhythmia require pp interval, or the diversity of P wave morphology, but they are difficult to detect the p wave signal because of various noise types. Thus, it is necessary to use noise-free R wave. So, the new approach for the detection of PVC is presented based on the rhythm analysis and the beat matching in this paper. For this purpose, we removed baseline wandering of low frequency band and made summed signals that are composed of two high frequency bands including the frequency component of QRS complex using the wavelet filter. And then we designed R wave detection algorithm using the adaptive threshold and window through RR interval. Also, we developed algorithm to classify PVC using RR interval. The performance of R wave and PVC detection is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate average detection rate of 99.76%, sensitivity of 99.30% and specificity of 98.66%; accuracy respectively for R wave and PVC detection.

• Journal of Biomedical Engineering Research
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• v.31 no.5
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• pp.375-384
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• 2010

The purpose of this study is to determine whether there is a correlation between the segmental bio-impedance measurement with the frequency modulations and the life-style disease of obesity. An obesity is not simply the factor for estimating the life-style disease of obesity, but also the risk factor occurring. There are many methods (BMI, WHR, Waist, CT, DEXA, BIA, etc.) for measuring a degree of obesity; the bio-impedance measurement is more economic and more effective than others. The physical examination, the blood test, the medical imaging diagnosis and the bio-impedancemeasurementswithmultiple frequencies for each body parts have been conducted for 77 people. The estimated value has been calculated through a segmental bio-impedance model based on multi-frequency that was created to reflect the highest correlation by analyzing correlation with linear regression analysis method for the measured bio-impedance and the risk factors. Then we compared with the clinical diagnosis. In case of high level cholesterol, low HDL-C and high LDL-C for life-style disease, the sensitivity is 80~100%and the specificity is 83~100%. This study has shown conclusively that bio-impedance can be a possible predictor to analyze the disease risk rate of population and individual health maintenance. And also the multi-frequency segmental bio-impedance can be used as early predictor to estimate the life-style disease of obesity.

• The Korean Journal of Mycology
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• v.32 no.2
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• pp.71-78
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• 2004

This study was conducted to investigate the diversity and occurrence frequency of ectomycorrhizal fruit bodies by planting sites from June 2000 to October 2001. A total of 3 classes 3 subclasses 8 orders 22 families 41 genera and 72 species (including two varieties) including saprophytic and ectomycorrhizal fungi was investigated. The mushrooms are classified into 9 families 21 genera and 48 species in Agaricales, 5 families 11 genera and 13 species in Aphllophorales, 3 families 3 genera and 4 species in Heterobasidiomycetes and 5 families 6 genus and 7 species in Gasteromycetdae. A total of 7 families 11 genera 30 species (2,451 ea.) of ectomycorrhizal mushroom was investigated. The occurrence frequency of mushrooms was 1,225, 179 and 130 times for Laccaria vinaceoavellanea, Amanita longistriata and Laccaria amethystea, respectively. The mushroom occurrence of ectomycorrhizal fungi was closely related to climatic conditions such as high air temperature, relative humidity and lots of rainfall from July to August. Diversity and distribution of ectomycorrhizal fungi by plots were very different because of variable local environments and different host plants in experimental plots. Laccaria vinaceoavellanea has showed very low host range of plant specificity because of mushroom occurrence in only Quercus sp. and Amanita longistriata, Russula bella and Inocybe sp. have showed wide host range of plant specificity because of mushroom occurrence in coniferous and broadleaved trees. The environment which has a favorable influence of mushroom occurrence was soil pH, organic matter and T/N ratio of soil enviromental and humidity of climatic environment.