• 월간산업보건
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• s.381
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• pp.32-54
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• 2020

소방공무원의 노출 위험과 그에 따른 건강영향 중에서 파킨슨병에 대한 연구를 고찰하고, 파킨슨병을 진단받은 소방공무원에 대한 업무 관련성 평가의 기초자료를 제공하고자 한다. 이에 소방공무원의 유해인자 노출특성을 파악하고, 이들과 파킨슨병과의 연관성을 살펴보았다.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.353-358
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• 2021

Parkinson's disease is the second most common degenerative brain disease after Alzheimer's in old age. Symptoms of Parkinson's disease are factors that reduce the quality of life in daily life, such as shaking hands, slowing behavior and cognitive function. Parkinson's disease that can slow the progression of the disease through early diagnosis. To diagnoze Parkinson's disease early, an algorithm was implemented to extract features using wav2vec and to diagnose the presence or absence of Parkinson's disease with deep learning(ANN). As a results of the experiment, the accuracy was 97.47%. It was better than the results of diagnosing Parkinson's disease using the existing neural network. The audio voice file could simply reduce the experiment process and obtain improved results.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.10
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• pp.421-428
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• 2014

Like Alzheimer's disease, Parkinson's Disease(PD) is one of the most common neurodegenerative brain disorders. PD results from the deterioration of dopaminergic neurons in the brain region called the substantia nigra. Currently there is no cure for PD, but diagnosing in its early stage is important to provide treatments for relieving the symptoms and maintaining quality of life. Unlike many diagnosis methods of PD which use a single biomarker, we developed a diagnosis method that uses both biochemical biomarkers and imaging biomarkers. Our method uses ${\alpha}$-synuclein protein levels in the cerebrospinal fluid and diffusion tensor images(DTI). It achieved an accuracy over 91.3% in the 10-fold cross validation, and the best accuracy of 72% in an independent testing, which suggests a possibility for early detection of PD. We also analyzed the characteristics of the brain fiber pathways of Parkinson's disease patients and normal elderly people.

• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.135-143
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• 2020

Parkinson's Disease (PD) is one of the three major old-age onset neurodegenerative diseases, its incidence rate is increasing worldwide as being an aging society. The number of PD patients has increased from 3 million in 1990 to 6.2 million in 2015 and is expected to increase to 12.4 million by 2040. Although many therapeutic candidates have been under development, but not yet been suggested the therapeutics of PD. For analyzing the trends and the status of convergence of technologies in the PD therapeutics, we classified into six sub-categories using global patent information and analyzed the level of technical competitiveness and technology convergence according to year, country, applicant, and technical description. These results can be used as a fundamental understanding for the current technical trend and the status of convergence of PD therapeutics, and establish the direction and strategy of R&D.

• The Journal of the Acoustical Society of Korea
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• v.38 no.3
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• pp.308-313
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• 2019

Parkinson's disease, one of the three major diseases in old age, has more than 70 % of patients with speech disorders, and recently, diagnostic methods of Parkinson's disease through speech signals have been devised. In this paper, we propose a method of diagnosis of Parkinson's disease based on deep residual gated recurrent neural network using speech features. In the proposed method, the speech features for diagnosing Parkinson's disease are selected and applied to the deep residual gated recurrent neural network to classify Parkinson's disease patients. The proposed deep residual gated recurrent neural network, an algorithm combining residual learning with deep gated recurrent neural network, has a higher recognition rate than the traditional method in Parkinson's disease diagnosis.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.55-65
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• 2022

Elderly people with Parkinson's disease have higher rates of physical and mental risk factors for falls than non-Parkinson's disease elderly. The purpose of this study is to investigate this by using national data that includes the entire population of the elderly in Korea. As a secondary analysis study using data survey on the elderly by the Ministry of Health and Welfare in 2017, there were a total of 103 elderly people with Parkinson's disease, and a total of 96 subjects were analyzed excluding missing values. In the elderly with Parkinson's disease, the factor most influencing the fall was IADL, and IADL is related to motor control function. Decreased motor control limits physical movements essential for daily life, and even affects self-protective behavior in emergency situations, affecting falls. Based on the research results that IADL can affect falls, various exercise therapies for fall prevention interventions in the elderly with Parkinson's disease can be suggested.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.753-756
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• 2014

파킨슨병은 도파민계 신경이 파괴되는 질병으로 알츠하이머병과 함께 대표적인 퇴행성 뇌 질환으로 병의 진행을 완화시킬 수 있는 치료법이 존재하기 때문에 병의 진단이 굉장히 중요하다. 파킨슨병을 진단하기 위한 과거의 연구는 대부분 단일 생체지표를 이용하는 것이었지만 이러한 방법에는 한계성이 존재한다. 따라서 본 연구에서는 생화학적 생체지표인 뇌척수액 내의 ${\alpha}-synuclein$ 단백질 수치와 영상학적 생체지표인 확산 텐서 영상의 여러 모수들을 결합한 융합 생체지표를 특징으로 사용하는 파킨슨병 진단 모델을 개발하고 성능을 평가하였다. 10-fold cross validation 에서 모든 성능지표에 대해 최고 100%를 보였으며, cross validation 의 과적합을 감안하더라도 파킨슨병의 조기진단에 유용하게 사용될 수 있는 가능성을 제시하였다.

• Korean Journal of Psychosomatic Medicine
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• v.11 no.1
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• pp.25-35
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• 2003

Objectives: The aim of this study was to investigate 1) the prevalence of depressive symptoms, 2) the severity of depressive symptoms, 3) the correlation of depressive symptoms with clinical variables, and 4) factors that contribute to depressive symptoms in patients with Parkinson's disease. Methods: One hundred eighteen patients with Parkinson's disease referred from the Parkinson's Disease Clinic of Dong-A University Hospital, Busan, Korea, completed a self-administered questionnaire package, which included basic demographic data, the Beck Depression Inventory, the Parkinson's disease quality of life questionnaire, the Symptom Checklist-90-Revision(SCL-90-R), and the Spielberger's State-Trait Anxiety Inventory. In addition, a structured interview and a complete neurological examination, including the Hoehn and Yahr stage, the motor part of the Unified Parkinson's Disease Rating Scale(some selected scales of UPDRS part III), the Schwab and England Activities of Daily Living scale(ADL), and the Korean version of Mini-Mental State Examination were performed. Results: 1) Based on BDI score, subjects were divided into four groups:severely(40.7%), moderately(13.6%) and mildly(12.7%) depressive and non-depressive(33.1%). 2) The severity of depressive symptom in Parkinson's disease was positively correlated with Hoehn and Yahr(H & Y) stage(r=0.34, p<0.0001), the severity of motor symptom(r=0.35, p<0.0001), and trait anxiety inventory(r=0.33, p<0.001). On the other hand, the severity of depressive symptom was negatively correlated with educational level(r=-0.34, p<0.001), ADL(r=-0.37, p<0.0001) and Parkinson's disease quality of life (PDQL)(r=-0.69, p<0.0001). Among several clinical variables, the PDQL was the most influential factor predicting whether the depressive symptom was present or not. Conclusion: This study suggests that depressive symptom is very prevalent among patients with Parkinson's disease. Data from this study indicate that medical staffs who take care of patients with Parkinson's disease should pay attention to finding and treating depressive symptom among their patients. With appropriate psychiatric intervention, patient's depressive symptom can be minimized or alleviated and thus, the quality of life in these patients is likely enhanced.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.2
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• pp.141-151
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• 2007

Parkinson's disease is one of the most frequent neurodegenerative diseases, which mainly affects the elderly. Parkinson's disease is often difficult to differentiate from atypical parkinson diorder such as progressive supranuclear palsy, multiple system atrophy, dementia with Lewy body, and corticobasal ganglionic degeneration, based on the clinical findings because of the similarity of phenotypes and lack of diagnostic markers. The accurate diagnosis of Parkinson's disease and atypical Parkinson disorders is not only important for deciding on treatment regimens and providing prognosis, but also it is critical for studies designed to investigate etiology and pathogenesis of parkinsonism and to develop new therapeutic strategies. Although degeneration of the nigrostriatal dopamine system results in marked loss of striatal dopamine content in most of the diseases causing parkinsonism, pathologic studies revealed different topographies of the neuronal cell loss in Parkisonism. Since the regional cerebral glucose metabolism is a marker of integrated local synaptic activity and as such is sensitive to both direct neuronal/synaptic damage and secondary functional disruption at synapses distant from the primary site of pathology, an assessment of the regional cerebral glucose metabolism with F-18 FDG PET is useful in the differential diagnosis of parkinsonism and evaluating the pathophysiology of parkisonism.

• The Journal of the Acoustical Society of Korea
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• v.41 no.6
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• pp.655-661
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• 2022

Since speech impairment is prevalent in patients with Parkinson's disease (PD), speech recognition systems suitable for these patients are needed. In this paper, we propose a speech recognition system that effectively recognizes the speech of patients with PD. The speech recognition system is firstly pre-trained with the Globalformer using the speech data from healthy people, and then fine-tuned using relatively small amount of speech data from the patient with PD. For this analysis, we used the speech dataset of healthy people built by AI hub and that of patients with PD collected at Inha University Hospital. As a result of the experiment, the proposed speech recognition system recognized the speech of patients with PD with Character Error Rate (CER) of 22.15 %, which was a better result compared to other methods.