• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.57-58
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• 2022

Sleep apnea (SA) is a common chronic sleep disorder that disrupts breathing during sleep. Clinically, the standard for diagnosing SA involves nocturnal polysomnography (PSG). However, this requires expert human intervention and considerable time, which limits the availability of SA diagnoses in public health sectors. Therefore, ECG-based methods for SA detection have been proposed to automate the PSG procedure and reduce its discomfort. We propose a preprocessing method to convert the one-dimensional time series of ECG into two-dimensional images using the Gramian Angular Field (GAF) algorithm, extract temporal features, and use a two-dimensional convolutional neural network for classification. The results of this study demonstrated that the proposed method can perform SA detection with specificity, sensitivity, accuracy, and area under the curve (AUC) of 88.89%, 81.50%, 86.11%, and 0.85, respectively. Our experimental results show that SA is successfully classified by extracting preprocessing transforms with temporal features.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4367-4385
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• 2016

With millions of people across the globe suffering from Parkinson's disease (PD), an objective, confirmatory test for the same is yet to be developed. This research aims to develop a system which can assist the doctor in objectively saying whether the patient is normal or under risk of PD. The proposed work combines the eye-hand co-ordination behaviour with the DaTscan images in order to determine the risk of this disorder. Initially, eye-hand coordination level of the patient is assessed through a hardware module. Then, the DaTscan image is analysed and used to extract certain geometrical parameters which shall indicate the presence of PD. These parameters are then finally fed into a Multi-Layer Perceptron Neural Network using Levenberg-Marquardt (LM) Back propagation training algorithm. Experimental results indicate that the proposed system exhibits an accuracy of around 93%.

• Imaging Science in Dentistry
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• v.34 no.2
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• pp.91-97
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• 2004

Purpose : This study was performed to evaluate the diagnostic value of both planar and SPECT imagings by comparing the results with the clinical and other imaging modalities findings. Materials and Methods: A total of 578 joints with TMJ complaints were examined using planar scintigraphy and SPECT. The planar scintigraphy and SPECT findings were analyzed and compared to the clinical findings of pain, clicking, crepitus and limitation of mouth opening. Moreover we compared the accuracy of the planar scintigraphy and SPECT methods with the one of the panoramic, transcranial, tomographic and MR imaging methods. Results: The planar scintigraphy and SPECT methods showed a high sensitivity of 0.76-0.84 and low specificity of 0.25-0.45 toward the clinical findings: pain, clicking, crepitus and mouth opening restriction. Simple radionuclide uptake ratio was high in each group of patients with pain, crepitus, limitation of mouth opening (p < 0.05) complaints, in each group with positive bone changes on panoramic, transcranial or tomographic images, and in disc displaced group. Conclusion: Although both planar and SPECT imagings have limited specificity, these techniques are sensitive for detection of internal derangement of the TMJ.

• ETRI Journal
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• v.44 no.4
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• pp.613-623
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• 2022

Autism spectrum disorder (ASD) is a developmental disorder associated with cognitive and neurobehavioral disorders. It affects the person's behavior and performance. Autism affects verbal and non-verbal communication in social interactions. Early screening and diagnosis of ASD are essential and helpful for early educational planning and treatment, the provision of family support, and for providing appropriate medical support for the child on time. Thus, developing automated methods for diagnosing ASD is becoming an essential need. Herein, we investigate using various machine learning methods to build predictive models for diagnosing ASD in children using facial images. To achieve this, we used an autistic children dataset containing 2936 facial images of children with autism and typical children. In application, we used classical machine learning methods, such as support vector machine and random forest. In addition to using deep-learning methods, we used a state-of-the-art method, that is, automated machine learning (AutoML). We compared the results obtained from the existing techniques. Consequently, we obtained that AutoML achieved the highest performance of approximately 96% accuracy via the Hyperpot and tree-based pipeline optimization tool optimization. Furthermore, AutoML methods enabled us to easily find the best parameter settings without any human efforts for feature engineering.

• Journal of Oral Medicine and Pain
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• v.48 no.4
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• pp.181-185
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• 2023

We present a case report of a 52-year-old male patient who suffered head trauma in a car accident and subsequently experienced taste and smell disorders. Following the accident, the patient reported difficulty detecting salty and sour tastes and diminished olfactory perception. Neurosurgical evaluation revealed subarachnoid and subdural hemorrhages, while otolaryngology investigations revealed hyposmia-a decreased sense of smell. Upon referral to the Department of Oral Medicine, a comprehensive assessment revealed a general bilateral reduction in taste sensation, particularly ageusia for salty taste. Electric taste-detection thresholds significantly exceeded the normal ranges. Integrating our findings from neurosurgery, otolaryngology, and oral medicine resulted in a diagnosis of mixed chemosensory disorder attributed to head trauma. This case highlights the intricate interplay of alterations in taste and smell following head injury, emphasizing the significance of multidisciplinary evaluations in diagnosing mixed chemosensory disorders resulting from traumatic brain injury.

• Journal of Korean Neurosurgical Society
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• v.29 no.2
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• pp.188-195
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• 2000

Objective : Essential tremor(ET) is the most common movement disorder, however, there has been little agreement in the neurologic literature regarding diagnostic criteria for ET. Familial ET is an autosomal dominant disorder presenting as an isolated postural tremor. The main feature of ET is postural tremor of the arms with later involvement of the head, voice, or legs. In previous studies, it was reported that ET susceptibility was inherited in an autosomal dominant inheritance. As previous results, it would suggest that ET might be associated with defect of mitochondrial or nuclear DNA. Recent studies are focusing on molecular genetic detection of movement disorders, such as essential tremor and restless legs syndrome. Moreover, authors have analysed mitochondrial DNA(mtDNA) from the blood cell of positive control(PC) and ET patients via long and accurate polymerase chain reaction(LA PCR). Materials & Methods : Blood samples were collected from PC and 9 ET patients. Total DNA was extracted twice with phenol followed by chloroform : isoamylalcohol. For the analysis of mtDNA, LA PCR was performed by mitochondrial specific primers. Results : With this technique, deletions of large quantities were detected within several regions of mtDNA in ET patients except for D-loop and CO I regions. Conclusion : The authors believe that ET is a genentic disorder with deficiency of mitochondrial DNA multicomplexes and mitochondiral dysfunction could be one of major causative factors of ET. Mitochondrial dysfunction may play an important role in the pathogenesis and possibility of disease progression among familial group with ET patients.

• Journal of Radiation Industry
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• v.3 no.1
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• pp.25-29
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• 2009

Microarrays can be used to screen thousands of binding events in a parallel and high throughput fashion and are of major importance in disease diagnosis and drug discovery. The use of radioisotope is conventionally regarded as one of the most sensitive detection methods. Atherosclerosis is a common disorder affecting arterial blood vessels. It happens when fat, cholesterol, and other substances made in the arterial blood vessels form a hard substances called plaque. Lipoprotein-associated phospholipase $A_2$ ($Lp-PLA_2$), a phospholipase $A_2$ enzyme, is used as a marker for cardiac disease. The detection of $Lp-PLA_2$ was accomplished by using radioactive [$^3H-acetyl$] PAF as a substrate and a feasibility study on RI biochip application to detection of $Lp-PLA_2$, a risk factors of atherosclerosis was performed. Inhibitive activity of a native plant extract was also determined by using the RI biochip. It was found to be applicable to a high-throughput screening of inhibitors for developing atherosclerosis therapeutic agents.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.28 no.2
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• pp.96-105
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• 2017

Objectives: The purpose of this study is to investigate the professional knowledge and perceptions of the early screening of Autism Spectrum Disorder (ASD) in practitioners who have contact with patients with ASD. Methods: A survey was carried out among 674 practitioners in total, where practitioners are defined as those who work at primary medical centers, public institutions, educational institutions and treatment institutions. The survey was carried out both online and offline, and it mainly focused on 1) knowledge about ASD symptoms, 2) knowledge about the early screening of ASD, 3) measures taken after ASD detection, 4) thoughts on the development of early screening tools for ASD, and 5) the current status of ASD treatment. The data collected were analyzed through descriptive statistics, analysis of frequency and cross tabulation analysis using SPSS WIN 22.0. Results: The results of this study suggest that the practitioners were not aware of the exact symptoms of ASD and their professional knowledge and the environment for early screening were insufficient. Furthermore, very few and inappropriate measures were taken after the detection of ASD. In addition, there was a high demand for early ASD screening tools to be used on site and, regarding treatment, the significance of the implementation of evidence based treatments as well as the continuity of relevant research came to the fore. Conclusion: It seems that there is a lack of knowledge and perception of the early screening of ASD and that education and training among practitioners is urgently required. This issue is discussed in more detail in the paper.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.4
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• pp.212-217
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• 2019

In this paper, a sleep management pillow system for snoring detection and respiration measurement is investigated. The sleep management pillow system consists of four force sensing resistor(FSR) sensors, two microphones(MIC), a pillow, a measurement system. Four FSR sensors attached at the bottom part of the pillow are used for respiration measurement and snoring detection. Two microphones located at the middle left and right of the pillow are utilized for only snoring detection. The respiration and the snoring of ten young people were measured using the sleep management pillow system composed of a data acquisition board, interface circuit, and personal computer. The measurement accuracy of the respiration was about 98% and the measurement accuracy of the snoring was about 97%. The experiment results show that the sleep management pillow system can be used for snoring detection and respiration rate measurement during sleeping.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.14 no.1
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• pp.112-122
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• 2003

Objectives：Considerable data indicate that diminished serotonergic activity is related to aggressive behavior. In order to understand the biological etiology in conduct disorder, we studied the relationships of plasma serotonin and 5-HIAA levels in conduct disorders to measures of aggression, violation of rules and oppositional defiant behavior. Methods：Subjects were selected from inpatients and outpatients department of the Division of Child and Adolescent Psychiatry of Seoul National University Hospital. 41 conduct disorders(18 childhoodonset type, 23 adolescent-onset type) and 23 normal controls were included in this study. For the assessment of aggression, rule violation and oppositional behavior, parents completed the rating scale for conduct disorder and oppositional behavior based on the DSM-IV diagnostic criteria. Plasma serotonin and 5-HIAA levels were determined by HPLC with electrochemical detection. Results：1) Plasma 5-HT and 5-HIAA levels were not significantly different among childhood-onset conduct disorder, adolescent-onset conduct disorder and normal control subjects. 2) No significant correlations were found between plasma 5-HT levels and aggression or rule violation. 3) Plasma 5-HT levels showed significant positive correlations with oppositional behavior both in childhood-onset conduct disorder and adolescent-onset conduct disorder. 4) Age-related changes were not found in plasma 5-HT and 5-HIAA levles. Conclusion：Our findings do not support the hypothesis that dysregulation of serotonergic function may be associated with aggresson. Instead, our data suggest that serotonergic function is more closely related with oppositional behavior than aggression.