• Proceedings of the KSLP Conference
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• 2003.11a
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• pp.149-149
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• 2003

후두질환 감별용 음성 분석방법인 multi-dimensional voice program (MDVP)으로 분석이 불가능할 정도로 주기성이 크게 훼손된 후두암 말기의 음성 에 대하여 효과적인 감별을 하기 위하여, 몇 가지 켑스트럼(cepstrum) 파라미터를 비롯하여, 주기성 및 그 동요 정도, 영교차율(zero-crossing rate, ZCR), 스텍트럼 중심 (spectral centroid, SC) 등 다양한 특징 파라미터를 이용한 감별 실험을 수행하였다. 후두암 감별 실험을 위해 부산대학교 병원 이비인후과에서 수집한 정상 남자 음성 데이터 50개, 양성 후두질환 남자 음성 데이터 50개 및 남성 후두암 환자 음성 데이터 105개를 사용하였다. 음성 데이터는 단모음 /아/ 발성만을 사용하였고, 정상인과 양성후두질환 환자, 그리고 MDVP 분석이 가능한 후두암 환자 음성 데이터 중 2/3는 학습에, 나머지 113은 감별실험에 사용하였다. 후두암 감별을 위한 분류기로는 Gaussian Mixture Model(GMM) 분류기를 사용하였으며, 이때 모델의 복잡도를 표현하는 mixture 수는 1에서 10까지 가변시키면서 가장 좋은 성능을 나타내는 값으로 결정하였다. 또한 모든 실험에서 켑스트럼 분석의 차수는 동일하게 12차로 고정시켰다. (중략)

• Proceedings of the KSLP Conference
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• 1998.11a
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• pp.185-185
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• 1998

배경 : 양성성대질환에 대한 기저막영역과 성대고유층에 대한 연구를 통해서 양성성대질환의 조직병리학적 특성이 밝혀지고 있으며, 질환발생과 관련된 병인과 병태가 밝혀지고 있다. 목적 : 양성성대질환의 병리학적 특성에 맞게 후두미세수술시 성대 고유층 최상층을 최대한 보호하고 병변부위만을 제거할 수 있는 성대점막하주입술의 유용성을 알아보고자 하였다. (중략)

• Journal of Biomedical Engineering Research
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• v.23 no.3
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• pp.197-205
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• 2002

The objectives of this Paper is to implement a diagnostic classifier of differential laryngeal diseases from acoustic signals acquired in a noisy room. For this Purpose, the voice signals of the vowel /a/ were collected from Patients in a soundproof chamber and got mixed with noise. Then, the acoustic Parameters were analyzed, and hierarchical neural networks were applied to the data classification. The classifier had a structure of five-step hierarchical neural networks. The first neural network classified the group into normal and benign or malign laryngeal disease cases. The second network classified the group into normal or benign laryngeal disease cases The following network distinguished polyp. nodule. Palsy from the benign laryngeal cases. Glottic cancer cases were discriminated into T1, T2. T3, T4 by the fourth and fifth networks All the neural networks were based on multilayer perceptron model which classified non-linear Patterns effectively and learned by an error back-propagation algorithm. We chose some acoustic Parameters for classification by investigating the distribution of laryngeal diseases and Pilot classification results of those Parameters derived from MDVP. The classifier was tested by using the chosen parameters to find the optimum ones. Then the networks were improved by including such Pre-Processing steps as linear and z-score transformation. Results showed that 90% of T1, 100% of T2-4 were correctly distinguished. On the other hand. 88.23% of vocal Polyps, 100% of normal cases. vocal nodules. and vocal cord Paralysis were classified from the data collected in a noisy room.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.14 no.1
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• pp.16-25
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• 2003

Background and Objectives : Electroglottography(EGG) is a non-invasive method of monitoring the vocal cord vibration by measuring the variation of physiological impedance across the vocal folds through the neck skin. It reveals especially the vocal fold contact area and is widely used for basic laryngeal researches, voice analysis and synthesis. The purpose of this study is to investigate the effectiveness of EGG parameters in differential diagnosis of laryngeal cancer. Materials and Methods : The author investigated 10 laryngeal cancer and 25 benign laryngeal disease patients who visited at the Department of Otolaryngology, Pusan National University Hospital. The EGG equipment was devised in the author's Department. Among various parameters of EGG, closed quotient(CQ), speed quotient(SQ), speed index(SI), Jitter, Shimmer, Fo were determined by an analysis program made with MATLAB 6.5$^{\circledR}$(Mathwork, Inc.). In order to differentiate various laryngeal diseases from pathologic voice signals, the author has used the electroglottographic parameters using the neural network of multilayer perceptron structure. Results : SQ, SI, Jitter and Shimmer values except those of CQ and Fo showed remarkable differences between benign and malignant laryngeal disease groups. From the artificial neural network, the percentage of differentiating the laryngeal cancer was over 80% in SQ, SI, Jitter, Shimmer except for CQ and Fo. These results indicated that it is possible to discriminate the benign and malignant laryngeal diseases by EGG parameters using the artificial neural network. Conclusion : If parameters of EGG which can reveal for the pathology of laryngeal diseases are additionally developed and the current classification algorithm is improved, the discrimination of laryngeal cancer will become much more accurate.

• Proceedings of the KSLP Conference
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• 1998.11a
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• pp.183-183
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• 1998

음성이 성대진동에 의해서 생성된다는 것이 밝혀진 이래로 이것을 확인해 보기 위한 많은 노력이 있어왔다. 특히 성대의 빠른 진동을 느린 움직임으로 정확하게 관찰하기 위해서 후두스트로보스코프같은 기구가 사용되고 있지만, 이것은 실제 시간에 따른 성대움직임을 보는 것이 아니고, 또 불규칙한 진동이 나타날 경우에는 성대점막의 움직임을 관찰하는 것이 불가능한 단점이 있었다. 저자들은 초 당 8000 개의 연속된 영상을 기록할 수 있는 videokymography를 이용하여 성대점막의 실제 시간에 따른 움직임을 관찰해보고, 후두질환에서 나타나는 영상을 확인해 보기 위하여 본 연구를 시작하였다. (중략)

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.26 no.1
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• pp.34-39
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• 2015

Background and Objectives:The Voice Handicap Index (VHI) evaluates the patients perception of impact of voice disorder in term of functional, physical, emotional factors. The purpose of this study was to evaluate the change of patient's subjective voice handicap index before and after laryngeal microsurgery for benign vocal cord lesions. Materials and Methods:We analyzed 55 patients who received laryngeal microsurgery for benign vocal cord disease from January 2011 to February 2013 retrospectively. There were 50 vocal nodules, 3 vocal polyps, 2 vocal cysts. VHI were analyzed before surgery and 3 months after surgery. Results:The VHI scores showed statistically significant reductions postoperatively in functional and emotional VHI (p=0.01 and p=0.034). Also, Emotional VHI score after microsurgery was higher in female than male [adjusted odd ratio (AOR)=0.292 ; 95% confidence interval, CI=0.098-0.869, p=0.01]. Conclusion:In other words, males experience significant more emotional effects that are improved after microscopic surgery.

• Proceedings of the KSLP Conference
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• 2001.11a
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• pp.166-166
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• 2001

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.30 no.1
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• pp.34-38
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• 2019

Background and Objectives : The aim of this study is verify the correlation between benign laryngeal mucosal disease and metabolic syndrome. Materials and Method : Data for patients diagnosed with benign laryngeal mucosal disease and metabolic syndrome from 2006 to 2015 were selected for analysis from the National Health Insurance Service database. Results : The prevalence of Metabolic syndrome was 2,179,785 out of 6,437,051 patients (33.86%). The prevalence of benign laryngeal mucosal disease was 516,594 out of 6,437,051 patients (8.03%). Metabolic syndrome was a risk factor for benign laryngeal mucosal disease [hazard ratio: 0.99, 95% confidence interval: 0.984-0.997] after adjusting for age and other variables including age, gender, smoking status, alcohol intake, exercise, body mass index, and diabetes. The number of metabolic syndrome components was also risk factor. Conclusion : Metabolic syndrome was related to the incidence of benign laryngeal mucosal disease. However this correlation did not seem to be high.

• Proceedings of the KSLP Conference
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• 2007.03a
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• pp.24-24
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• 2007

• Proceedings of the KOR-BRONCHOESO Conference
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• 1991.06a
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• pp.18-18
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• 1991

후두유두종은 호흡기계에 발생하는 양성종양중 가장 흔한 질환으로 연령에 따라 소아형과 성인형으로 분류하는데 다발성 병변이 흔하고 재발율이 높다고 알려져 있다. 후두유두종의 원인으로는 human papillomavirus의 감염으로 생각되며 잠복 감염으로 인하여 후두유두종이 재발된다고 알려져 있다. Gissman등에 의해 HPV 11이 발견되었음이 보고된 이래 최근까지 HPV 6와 11이 후두유두종의 원인이 된다고 알려져 있다. HPV의 검출에는 Southern blotting이나 in-situ hybridization 방법이 알려져 있는데 저자들은 현재까지의 바이러스 검색방법 중 가장 예민한 방법인 PCR을 이용하여 후두유두종의 HPV DNA를 조사하여 보고자 한다. 저자들은 1989년 10월부터 1900년 12월까지 서울대병원 이비인후과에서 수술을 시행받은 후두유두종 환자 15예를 대상으로 하였으며 이중 소아형은 9예이었고 성인형은 6예였으며 대부분 다발성 병변이었다. HPV 6는 15예중 10예에서 HPV 11은 15예중 6예에서 발견되었으며 두가지 형이 같이 발견된 경우는 1예가 있었다. 소아형의 경우에는 HPV 6와 11이 각각 5예로 비슷한 비율로 검출된 반면 성인형에서는 HPV 6가 주로 검출되었다.