• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.4
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• pp.215-222
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• 2009

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.

• Speech Sciences
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• v.12 no.3
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• pp.19-33
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• 2005

Tremor is a main factor of parkinsonism. Voice tremor may be the first, later or the only symptom of a neurological disease and its frequency, amplitude, and regularity may differ among the diseases of different neural subsystems. Differential diagnosis between idiopathic Parkinson's disease (IPD) and multiple system atrophy (MSA) has been difficult. This study included three groups: (1) 6 IPD patients; (2) 6 MSA patients; and (3) 20 ageand sex-matched normal controls. The MDVP (Multidimensional Voice Program) was used to analyze the sustained /a/phonation. The results were as follows: (1) frequency perturbation parameters (jitter, sPPQ, Vf0) and FTRI of tremor parameter of two patient groups were statistically different from those of the controls (p < .01); (2) measures were higher in short-term and long-term f0 and amplitude perturbation in MSA than IPD; (3) however, any acoustic parameters between IPD and MSA were not statistically different; except for the rate of frequency tremor, 4$\sim$5 Hz in IPD, 5$\sim$11 Hz in MSA and (4) the pattern of regularity for voice tremor through histogram indicated that amplitude of IPD was irregular while both f0 and amplitude of MSA were irregular. In conclusion, F0, rate of frequency tremor, and pattern of f0 regularity may be predictors for differential diagnosis. These findings might signify that voice tremor of parkinsonism was resulted from modulation of f0.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.28 no.2
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• pp.71-78
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• 2017

Voice disorder is classified into three categories, structural, neurogenic and functional dysphonia. Neurogenic dysphonia refers to a disruption in the nerves controlling the larynx. Common examples of this include complete or partial vocal cord paralysis, spasmodic dysphonia. Also it occurs as part of an underlying neurologic condition such as Parkinson's disease, myasthenia gravis, Lou Gehrig's disease or disorder of the central nervous system that causes involuntary movement of the vocal folds during voice production. Functional dysphonia is a voice disorder in the absence of structual or neurogenic laryngeal characteristics. A near consensus exist that Muscle tension dysphonia (MTD) is functional voice disorder wherein hyperfunctional laryngeal muscle activity whereas Spasmodic dysphonia (SD) is neurogenic, action-induced focal laryngeal dystonia including several subtype. Both Adductor type spasmodic dysphonia (AdSD) and MTD may be associated with excessive supraglottic contraction and compensation, resulting in a strained voice quality with spastic voice breaks. It makes these two disorders extremely difficult to differentiate based on clinical interpretation alone. Because treatment for AdSD and MTD are quite different, correct diagnosis is important. Clinician should be aware of the specific vocal characteristics of each disease to improve therapeutic outcome.

• Journal of Sasang Constitutional Medicine
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• v.28 no.4
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• pp.309-319
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• 2016

Objectives This study was aimed to analyze the reliability of vocal features and probabilities for being in Sasang constitutional types calculated from Sasang constitutional voice diagnosis system according to operator presence. Methods We acquired 96 voice recordings from one male and one female for 4 days. For the first 2 days, the subjects recorded their voice by themselves. For the last 2 days, they recorded according to the instruction of an operator following the standard operating procedure. We analyze the standard deviations of vocal features, probabilities for being three constitutional types, Tae-Eum (TE), So-Yang (SY), and So-Eum (SE) Results In the case of the female, coefficients of variations of the voice variables and the probabilities for being each constitutional type were all within 20%. In the case of the male, coefficients of variations were all within 20% except one variable. Even if there was no instruction from the operator, standard deviations of the probability did not increase for both genders. When recorded without the operator, for male, the probability for being SE decreased by 3.2%. For female, the probability for being TE increased by 5.438%, and that of SE decreased by 3.057%, and that of SY decreased by 2.394%. Conclusions When recorded without operators, for men, there was a significant difference in the probability for being SE. And for women, there were significant differences in the probabilities for all constitutional types.

• Korean Journal of Bronchoesophagology
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• v.7 no.2
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• pp.161-167
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• 2001

Background and Objectives： Total laryngectomy is often required for advanced cases. But this operation induced the many inconvenience of basic daily life. Early diagnosis of laryngeal cancer is very important to prevent from this disastrous condition. In this point of view, mass screening test for early detection of laryngeal cancer is necessary. Screening test using voice has many advantages such as simple, less interventional. Voice collection by Automatic Response System(ARS) is comfortable and easy to got acoustic sample. Thus author tried to got the acoustic parameters which can differentiate normal, benign. and malignant laryngeal diseases and also checked the availability of parameters on neural network system. Materials and Methods: Author has evaluated the voice from 17 laryngeal cancer patients and 45 benign laryngeal disease patients who visited at Department of Otolaryngology, Pusan National University Hospital from May 1998 to April 2001, and 15 normal control. Author chose the sir Parameters (Jitt. vFo, Shim, vAm, NHR, SPI) that was thought to be related with voice collected by ARS among thirty-three parameters analysed by a Multi-Dimensional Voice Program (MDVP). Two-step neural network was used for the availability of six parameters. Results: The detection rate of normal voice by ARS voice analysis is 78.5% and detection rate of abnormal voice was 97.1 o/o. Among abnormal voice, the detection rate of benign laryngeal diseases and laryngeal cancers were 82.4 o/o, 70.6% respectively. Conclusion: Author concluded that six parameters and Matlab based neural network software may be effective in development of acoustic screening system for laryngeal cancer and further study should be necessary for development of new acoustic parameters.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10B
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• pp.1062-1069
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• 2009

The kidney diseases is a big social problem what is suffering sequela of metabolic syndrome due to obesity. Therefore, it is most important that early to take the appropriate action; it does not have symptoms Abnormalities of the kidney. With this, in mind, this paper wish to propose the method to can diagnosis by non self-consciousness, non-imprisonment, analgesia of kidney disease through the voice analysis. To configure the entire system is developed to combines the voice analysis, watching the face color and this paper is designed the method to diagnosis kidney disease based on labial. In this paper, organized each kidney disease patients and healthy people group and we would like to analyze, compare with output in experiment morphology analysis and numerical value analysis of voice information. Secondly, auscultation theory of Oriental medicine and linguistic, phonetics analyze out interrelation to extraction peculiar elements of kidney about voice deduction deduced relation of the first formants frequency. Such result of experimentation, deduced widely to be formed the first formants frequency bandwidth value of kidney patients group than normal group. Finally, diagnosing an kidney diseases in only labial sound, calculated about misdiagnosis probability.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.355-357
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• 2019

Now that we are entering an aging society, the user interface for new devices and IoT technology is very inconvenient for senior generation. To improve this, we propose an AI technology-based intelligent senior assistant voice recognition system. This system implements Cloud platform based API to accumulate data for machine learning processing, provides content for diagnosis and prevention of dementia, and provide chat-bot content for senior generation. We hope that senior generations will increase the accessibility and convenience of IoT devices and new technology devices with our system.

• Journal of Sasang Constitutional Medicine
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• v.24 no.1
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• pp.13-20
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• 2012

1. Objectives : It is very important to classify people into Sasang constitution correctly in SCM. There have been many researches for this and several tools have been developed for diagnosis of Sasang constitution. In our study, we introduce a new web application for Integrated Sasang Constitutional Diagnosis (ISCD) ${\beta}$-version and algorithm on the base of face, body shape, voice and questionnaire. 2. Development : The web application of ISCD ${\beta}$-version was designed to be used easily for subject, staffs, and oriental medical doctors. For this purpose, we developed a web-application of Integrated Sasang Constitutional Diagnosis ${\beta}$-version using mysql database, tomcat web system, JSP, JAVA, and C++ languages. 3. Current State : The ISCD ${\beta}$-version could be accessed at http://210.218.196.115/SDT/login.jsp. The ISCD ${\beta}$-version consisted of 3 parts, for staffs, subject and oriental medical doctors. The system has been managed since February 2011. Currently 7 oriental hospitals have used the system and 1,439 subjects have been diagnosed by the system. 4. Conclusion and future work : Although many researchers have tried to develop a system or an algorithm for diagnosis of subject's constitution, we could have not used the system based on objective information of human body type, characters, symptoms. In this study, we describe a web application of objective diagnosis algorithm as ISCD ${\beta}$-version. This system may help an oriental medical doctors to make a decision of Sasang constitutional diagnosis easily and correctly.

• Journal of Sasang Constitutional Medicine
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• v.24 no.3
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• pp.34-41
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• 2012

Objectives In this study, we developed a mock-up of the system for Sasang Constitutional (SC) diagnosis. This system consists of 5 devices which are the face analyzer, the voice analyzer, the skin analyzer, the pulse analyzer, and the computer-based questionnaire. Our goal is to evaluate the repeatability of the system. Methods Each device is capable of classifying SC types. The classification probability of the integrated system for the SC types was obtained by summing the probability from each device. For evaluating the repeatability of the system, we collected data for 5 subjects, and repeated the measurement three times for each individual. The average and standard deviation were used for calculating the Coefficient of Variation. Results The results showed that the repeatability of the classification probability of the integrated system is about 8%, which implies the system is repeatable. Conclusions To increase usability of this system, it is desirable for the system to offer information on health condition of the user. The integrated constitutional diagnosis system will be upgraded to complement the convenience and to develop the diagnostic algorithm for the user's health condition.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.5
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• pp.1210-1217
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• 2008

Sasang medicine is our country's unique traditional medicine based on the classification of individual physical constitution. In the Sasang medicine, what is considered the most important task is to categorize Sasang constitution exactly. Therefore, security of objective elements and diagnosis index is a problem awaiting solution in Sasang constitution classification. To this the paper abstracted result value from objectification, visualization, a fixed quantity of Sasang constitution to analyze face image signals and voice signals. And, comparing the differences constitution would like to develop system classification of Sasang constitution. Specially, image and voice signals are different because of gender, age, region so it composed Sasang constitution group to 40-50 years women in Seoul. To extract of these image and voice signals wanted to perform comparison, analysis in constitution. Finally, it would like to prove a significance of research result through experiment.