Mahalanobis Taguchi System을 이용한 파킨슨병 환자의 음성분석을 통한 진단에 관한 연구
Diagnosis of Parkinson’s Disease by Voice Disorder Using Mahalanobis Taguchi System
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초록
Human voice reacts very sensitively to human’s minute physical condition. For instance, human voice disorders affect patients profoundly especially in the case of Parkinson’s disease. Acoustic tools such as MDVP, can function as an equipment that measures various voice in different objects. Many different approaches have been applied for analyzing the voice disorders for diagnosis of Parkinson’s disease. According to the voice data of suspected Parkinson’s patients from UCI Machine Learning Repository, it is reported to have 23 people with Parkinson’s disease and 8 healthy people. Applying Mahalanobis Taguchi System (MTS) for diagnosis of Parkinson’s disease, the correct diagnosis performance is compared to previous research results.
Abstract
Human voice reacts very sensitively to human’s minute physical condition. For instance, human voice disorders affect patients profoundly especially in the case of Parkinson’s disease. Acoustic tools such as MDVP, can function as an equipment that measures various voice in different objects. Many different approaches have been applied for analyzing the voice disorders for diagnosis of Parkinson’s disease. According to the voice data of suspected Parkinson’s patients from UCI Machine Learning Repository, it is reported to have 23 people with Parkinson’s disease and 8 healthy people. Applying Mahalanobis Taguchi System (MTS) for diagnosis of Parkinson’s disease, the correct diagnosis performance is compared to previous research results.
참고문헌 (17)
- 강영애, "파킨슨병 환자와 정상 노인의 음성비교", 말소리와 음성과학, 1(1), pp.99~107 (2009), 한국음성학회
- 이옥분, "강도및 음도조절을 이용한 훈련이 파킨슨병 환자의 음성및 발화 명료도 개선이 미치는 효과", 음성과학, 8(3), pp.173~184 (2001)
- 최성희, "파킨슨증의 음성진전 : 감별진단을 위한 예비연구", 말소리와 음성과학, 12(3), pp.19~23 (2005), 한국음성학회
- Max A Little, "Exploiting Nonlinear Recurrence and Fractal Scaling Properties for Voice Disorder Dection", Biomedical Online, 6, pp.23~ (2007)
- Felix Javier Jimenez-Jimenez, "Acoustic Voice analysis in untreated patients with Parkinson’s disease", Parkinson’s and Realted Disorders, 3(2), pp.111~116 (1997)
- Julia K. MacCallum, "Acoustic Analysis of asperiodic voice perturbation and nonlinear dynamic properties in esophagcal phonation", Journal of Voice, 23(3), pp.283~290 (2003)
- Javier Gamboa, "Acoustic Voice Anaysis in patients with Parkinson’s disease treated with dopaminergic drugs", Journal of Voice, 11(3), pp.314~320 (1997)
- Taguchi, G, "The Mahalanobis-Taguchi Strategy : A Pattern Technology" (2002), John Wiley and Sons, Inc.
- Taguchi, G, "New Trends in Multivariate Diagnosis", Indian Journal of Statistics, 62(B), pp.2233~2248 (2000)
- 홍정의, "Mahalanobis Taguchi System을 이용한 다변량 시스템의 해석에 관한 연구", 산업경영시스템학회지, 32(1), pp.20~25 (2009), 한국산업경영시스템학회
- 홍정의, "Mahalanobis Taguchi System을 이용한 자동차 브레이크 성능 만족도를 고려한 설계조건 선정에 관한 연구", 산업경영시스템학회지, 30(1), pp.41~47 (2007), 한국산업경영시스템학회
- Hong, Jung-Eui, "A Comparison study of Mahalanobis Taguchi System and nueral network for multivariate pattern recognition", 2005 ASME IMECE Proceedings (2005)
- E. A. Cudney, "An Evaluation of Mahalanobis Taguchi System and Neural Network for Multivariate Pattern Recognition", Journal of Industrial and System Engineering, 1(2), pp.139~150 (2007)
- "Mahalanobis Distance : A Theoretical and Practical Approach"[URL]
- Hayashi, S., "A New Manufacturing Control System using Mahalanobis Distance for Maximizing Productivity", IEEE Transactions, pp.59~62 (2001)
- R. Jugulum, "Discussion of A review and analysis of Mahalanobis- Taguchi System", Technometrics, 45(1) (2003)
- R. Jugulum, "Comparison between Mahalanobis-Taguchi-System and Artificial Neural Networks", Journal of Quality Engineering Society, 10(1), pp.60~73 (2002)