http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
압전센서를 이용한 코골이와 심박 검출을 위한 자동 알고리즘
에르덴바야르,박종욱,정필수,이경중,Urtnasan, Erdenebayar,Park, Jong-Uk,Jeong, Pil-Soo,Lee, Kyoung-Joung 대한의용생체공학회 2015 의공학회지 Vol.36 No.5
In this paper, we proposed a novel method for automatic detection for snoring and heart beat using a single piezoelectric sensor. For this study multi-rate signal processing technique was applied to detect snoring and heart beat from the single source signal. The sound event duration and intensity features were used to snore detection and heart beat was found by autocorrelation. The performance of the proposed method was evaluated on clinical database, which is the nocturnal piezoelectric snoring data of 30 patients that suffered obstructive sleep apnea. The method achieved sensitivity of 88.6%, specificity of 96.1% with accuracy of 95.6% for snoring and sensitivity of 94.1% and positive predictive value of 87.6% for heart beat, respectively. These results suggest that the proposed method can be a useful tool in sleep monitoring and sleep disordered breathing diagnosis.
CIC형 보청기용 범용 이어쉘 제작을 위한 파라미터 추출 및 시뮬레이션
에르덴바야르,전유용,박규석,송영록,이상민,U, Erdenebayar.,Jeon, Y.Y.,Park, G.S.,Song, Y.R.,Lee, S.M. 대한의용생체공학회 2010 의공학회지 Vol.31 No.4
Most of the ear shells of hearing aids are manufactured manually, and it is one of the reasons that the cost of the custom-made hearing aids can be increased. Thus it is required to manufacture the ready-made ear shell for the purpose of easy manufacturing and decrease in cost. In this study, we extract parameters in order to manufacture the ready-made ear shell for CIC type hearing aids and simulate to reconstruct the ear shell using the extracted parameters. To parameter extraction, we set up the eleven parameters for the ready-made ear shell based on anatomical characteristics of the ear canal, and we found values of the parameters from twenty-one impressions in their 20s and twelve impressions in their 60s using aperture detection and feature detection algorithms. Classifying the parameters by size, we also determine the parameters of ready-made ear shell into three types for people in their 20s and two types for people in their 60s. Each ready-made ear shell was simulated to reconstruct using figured parameters, and evaluated the rate of agreement with unused impressions for setting parameters. To evaluate the ready-made ear shell, we calculate the volume ratio and intersection between of the each impression and ready-made ear shell, and the intersection ratio using the intersection volume and ready-made ear shell volume. As a result, the volume ratio was about 70%, and volume match ratio was also up to 70%. It means that the ready-made ear shell we simulated is the significantly matched to impression.
코골이용 압전센서를 이용한 수면무호흡 검출에 관한 예비 연구
에르덴바야르,이효기,김호중,이경중,Urtnasan, Erdenebayar,Lee, Hyo-Ki,Kim, Hojoong,Lee, Kyoung-Joung 대한의용생체공학회 2014 의공학회지 Vol.35 No.4
This paper proposed a method that can automatically classify sleep apnea by using features extracted from pulse rate variability(PRV) signals induced from piezo snoring sensor for patients with obstructive sleep apnea(OSA). We have extracted eight features(NN, SDNN, RMSSD, NN10, NN50, LF, HF and LF/HF ratio) based on time and frequency analyses of PRV. Sleep apnea was classified by a linear discriminant analysis(LDA). A performance was evaluated using snore recordings from 13 patients with OSA (ages: $54.5{\pm}10.5$ years, body mass index: $26.3{\pm}2.5kg/m^2$, apnea-hypopnea index: $19.2{\pm}6.0/h$). The sensitivity and specificity were $78.9{\pm}0.9%$ and $78.9{\pm}0.9%$ for training set and $77.7{\pm}10.9%$ and $79.0{\pm}2.8%$ for test set, respectively. Our study demonstrated the feasibility of implementing a piezo snoring sensor based on a portable device as a simple and cost-effective solution for contributing to the OSA screening.
보청기용 범용 이어쉘을 위한 설계 파라미터에 관한 연구
에르덴바야르(Erdenebayar-Urtnasan),전유용(Yu-Yong Jeon),박규석(Gyu-Seok Park),송영록(Young-Rok Song),이상민(Sang-Min Lee) 대한전기학회 2011 전기학회논문지 Vol.60 No.5
In this study, main parameters: aperture, first bend and second bend which express a structure of ear canal are extracted in order to modeling and manufacture the ready-made ear shells of hearing aids. The proposed parameter extraction method consists of 2 important algorithms, aperture detection and feature detection. In the aperture detection algorithm, aperture of 3-D scanned virtual ear impression and parameters relating to ear shell of hearing aid are determined. The feature detection algorithm detects first bend, second bend, and related parameters. Through these two algorithms, parameters for aperture, first bend, and second bend are extracted to model the ready-made ear shell of hearing aid. The values of these extracted parameters from 36 people’s right ear impression are analyzed and measured statistically. As a result of the analysis, it has been found that it is possible to classify ready-made ear shell parameters by age and size. The ready-made ear shell parameters are classified 3-size for 20 years old and 2-size for 60 years olde. Using 3D rhino program, virtual ready-made ear shell is reconstructed by parameters of every type, and simulated to model it. A final product was produced by transferring simulation result with rapid prototyping system. The modeled ready-made ear shell is evaluated with the objective and subjective method. Objective method is the comparison volume ratio and overlapped volume ratio of ear impression from randomly chosen 18 people and ready-made ear shell. And subjective method is that the final product of ready-made ear shell is used by users and the satisfaction number drawn from well fitting and comfortable testing was evaluated. In the result of the evaluation, it has been found that volume ration is 70%, big and middle size ready-made ear shell products are possible, and the satisfaction number is high.