• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.1
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• pp.35-43
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• 2000

This paper was studied on developmental direction of telecommunications for disabilities welfare. Method of this study is delphi method. Persons with disabilities is classed as motor disability, visual handicap, hearing impairment, and language and speech disorders. Persons with motor disability is needs as follow, speed recognition technology, video recognition technology, breath capacity recognition technology. Persons with visual handicap is needs as follow, display recognition technology, speed recognition technology, text recognition technology, intelligence conversion handling technology, video recognition - speed synthetic technology. Persons with hearing impairment and language - speech disorders is needs as follow, speed signal handling technology, speed recognition technology, intelligence conversion handling technology, video recognition technology, speed synthetic technology the results of this study is as follow: first, disabilities telecommunications organization must be constructed. Second, persons with disabilities in need of universal service. Third, Persons with disabilities in need of information education, Fourth, studying for telecommunications in need of support. Fifth, small telecommunications company in need of support. Sixth, software industry in need of new development. Seventh, Persons with disabilities in need of standard guideline for telecommunications.

• Journal of Biomedical Engineering Research
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• v.45 no.1
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• pp.26-36
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• 2024

Functional brain imaging techniques have been used to diagnose psychiatric disorders such as dementia, depression, and autism. Recently, these techniques have also been actively used to study hearing loss. The present study reviewed the application of the functional brain imaging techniques in auditory research, especially those focusing on hearing loss, over the past decade. EEG, fMRI, fNIRS, MEG, and PET have been utilized in auditory research, and the number of research studies using these techniques has been increasing. In particular, fMRI and EEG were the most frequently used technique in auditory research. EEG studies mostly used event-related designs to analyze the direct relationship between stimulus and the related response, and in fMRI studies, resting-state functional connectivity and block designs were utilized to analyze alterations in brain functionality in hearing-related areas. In terms of age, while studies involving children mainly focused on congenital and pre- and post-lingual hearing loss to analyze developmental characteristics with and without hearing loss, those involving adults focused on age-related hearing loss to investigate changes in the characteristics of the brain based on the presence of hearing loss and the use of a hearing device. Overall, ranging from EEG to PET, various functional brain imaging techniques have been used in auditory research, but it is difficult to perform a comprehensive analysis due to the lack of consistency in experimental designs, analysis methods, and participant characteristics. Thus, it is necessary to develop standardized research protocols to obtain high-quality clinical and research evidence.

• Dementia and Neurocognitive Disorders
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• v.23 no.1
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• pp.1-10
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• 2024

Background and Purpose: Voice, reflecting cerebral functions, holds potential for analyzing and understanding brain function, especially in the context of cognitive impairment (CI) and Alzheimer's disease (AD). This study used voice data to distinguish between normal cognition and CI or Alzheimer's disease dementia (ADD). Methods: This study enrolled 3 groups of subjects: 1) 52 subjects with subjective cognitive decline; 2) 110 subjects with mild CI; and 3) 59 subjects with ADD. Voice features were extracted using Mel-frequency cepstral coefficients and Chroma. Results: A deep neural network (DNN) model showed promising performance, with an accuracy of roughly 81% in 10 trials in predicting ADD, which increased to an average value of about 82.0%±1.6% when evaluated against unseen test dataset. Conclusions: Although results did not demonstrate the level of accuracy necessary for a definitive clinical tool, they provided a compelling proof-of-concept for the potential use of voice data in cognitive status assessment. DNN algorithms using voice offer a promising approach to early detection of AD. They could improve the accuracy and accessibility of diagnosis, ultimately leading to better outcomes for patients.

• Dementia and Neurocognitive Disorders
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• v.23 no.3
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• pp.146-160
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• 2024

Background and Purpose: The emotions of people at various stages of dementia need to be effectively utilized for prevention, early intervention, and care planning. With technology available for understanding and addressing the emotional needs of people, this study aims to develop speech emotion recognition (SER) technology to classify emotions for people at high risk of dementia. Methods: Speech samples from people at high risk of dementia were categorized into distinct emotions via human auditory assessment, the outcomes of which were annotated for guided deep-learning method. The architecture incorporated convolutional neural network, long short-term memory, attention layers, and Wav2Vec2, a novel feature extractor to develop automated speech-emotion recognition. Results: Twenty-seven kinds of Emotions were found in the speech of the participants. These emotions were grouped into 6 detailed emotions: happiness, interest, sadness, frustration, anger, and neutrality, and further into 3 basic emotions: positive, negative, and neutral. To improve algorithmic performance, multiple learning approaches were applied using different data sources-voice and text-and varying the number of emotions. Ultimately, a 2-stage algorithm-initial text-based classification followed by voice-based analysis-achieved the highest accuracy, reaching 70%. Conclusions: The diverse emotions identified in this study were attributed to the characteristics of the participants and the method of data collection. The speech of people at high risk of dementia to companion robots also explains the relatively low performance of the SER algorithm. Accordingly, this study suggests the systematic and comprehensive construction of a dataset from people with dementia.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.2
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• pp.129-134
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• 2010

Diseases such as cardiovascular illnesses, according to the National Statistical Office opened reveals that 600-800 people were killed, blood pressure, arteriosclerosis, heart disease, stroke, etc. will be a flow of blood disorders that occur in cardiovascular illnesses today are fulfilling the Master / Slave samangryulin disease appears high. Died of cardiovascular disease also told them the correct first aid survival when patients are accounted for approximately 40% of emergency rapid response is required. Therefore, this paper, the weak classifier in the AdaBoost algorithm to generate a strong classifier by combining effects throughout the analysis to measure the ECG, and cardiovascular disease that occurred to you as soon as the emergency management system that can deliver on the proposed Desk was. The electrocardiogram data measured by the ZigBee-based sensors, communication devices and emergency transport for emergency alarms in the determination and monitoring of the management desk by providing health services to enable the delivery was fast.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.2
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• pp.121-127
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• 2015

A reduction of motor performance due to brain disorders can be screened by evaluating force tracking capabilities (FTCs). Existing studies have examined FTCs mainly using simple sinusoidal waves, of which repeated profiles have a critical limitation due to a learning effect in force tracking. The present study examined the effects of personal factors (age and gender) and sinusoidal wave factors (central force and complexity) on FTCs of healthy adults using composite sinusoidal wave profiles (CSWPs). FTCs were measured using Finger $Touch^{TM}$ for 30 seconds and quantified in terms of time within the target range (TWR, accuracy measure) and relative RMSE (RRMSE, variability measure). A total of 90 healthy adults in 20s to 70s with the equal gender ratio participated in the experiment consisting of combinations of 2 central force levels (6 N and 10 N) and 2 complexity levels (approximate entropy, ApEn = 0.03 and 0.06) of CSWPs. Significantly decreased FTCs (lower TWR and higher RRMSE) were found in aged adults, females, the low central force, and the high complexity. The detailed FTC decrements include a 43% reduced TWR and a 85% increased RRMSE of older adults in 70s as compared to those in 20s, a 17% reduced TWR and a 17% increased RRMSE of female as compared to those of male, a 30% reduced TWR and a 108% increased RRMSE at central force = 6N when compared to those at central force = 10N, and a 19% reduced TWR and a 30% increased RRMSE at ApEn = 0.06 as compared to those at ApEn = 0.03. The characteristics of FTCs for CSWPs can be of use in establishing an assessment protocol of motor performance for screening brain disorders.

• The Journal of the Korea Contents Association
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• v.17 no.2
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• pp.623-636
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• 2017

The use of virtual reality(VR)-based interventions for students with autism spectrum disorders(ASD) has received special attention as evidence-based practices for its feasiblity, practicality, and appropriateness. However, there is little research to investigate the effects of VR-based intervention for students with ASD in Korea. This study identifies and reviews studies applying VR-based interventions. In total, 13 experimental studies were found that examine the effects of VR interventions published from 1990 to 2016. The selected studies were analyzed by 6 variables including publication year, participants, research design, independent variable, dependent variable, and outcome. The results of this study showed the feasibility of the implementing VR-based interventions in various age group students with ASD. In addition, the utilization of VR techniques was particularly effective in improving a wide range of social communication skills including facial recognition, empathy, joint attention, understanding social context, and resolving issues due to limited cognitive abilities. Several recommendations for the future study on VR-based intervention for students with ASD such as interdisciplinary approach to VR-based interventions, support needs regarding characteristics of ASD, generalization and maintenance of acquired technology, and consideration for participants' cultural background. were discussed.

• Journal of Korea Entertainment Industry Association
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• v.13 no.3
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• pp.249-258
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• 2019

The health care services are the most basic social institutions that are provided to citizen including disabled persons for improvement of health. However, the study of the difference of health care services according to the speech therapy use in the people with speech-language disorders was insufficient. The aim of this investigation was to compare the awareness of health care services and characteristics of people with speech-language disorders according to speech therapy use. The researchers selected 229 people with language disorder using raw data of National Survey of the Disabled Person (2017). We compared the characteristics and health care services of people with speech-language disorders by distinguishing between speech therapy non-users and speech therapy users. Among the 229 people with language disorder, speech therapy users were 37 persons (16.2%). In comparison with non-users, users were younger, more preschoolers, more family incomes, and intellectual disabilities and autistic disorder were the most common types of disability enrollment. Users had a lower proportion of unmet medical needs than non-users. For the reasons of unmet medical need, there were 6.8% and 6.3% of the "economic reasons" and "communication difficulties" Both users and non-users responded that "disability management services" need to be strengthened by the government. In conclusion, we suggest that access to health care services needs to be increased to lower the barriers of speech therapy use.

• Journal of Korean Neuropsychiatric Association
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• v.57 no.2
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• pp.190-208
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• 2018

Objectives To initiate and develop a treatment guideline in multidisciplinary approaches for related professions who are either working and/or living with children and adolescents with neurodevelopmental disorders who show behavioral problems. Methods To collect and reflect opinions from multiple professions who assumedly have different interventions or mediations on behavioral problems, a self-report survey and Focus Group Interview (FGI) were conducted for a group of child and adolescent psychiatrists, behavioral therapists, special education teachers, social welfare workers, and caregivers. Results According to a self-report survey and FGI results from multiple professional groups, aggressive behavior is the mostly common behavioral problem necessitating urgent interventions. However, both mainly used intervention strategies and effective treatment methods were different depending on professional backgrounds, such as pharmacological treatment, parent training, and behavior therapy, even though they shared an importance of improving communication skills. In addition, there was a common understanding of necessity to include parent training in a guideline. Lastly the data suggested lack of proper treatment facilities, qualified behavior therapists, and lack of standardized treatment guideline in the field needed to be improved for a quality of current therapeutic services. Conclusion It is supported that several subjects should be included in the guidelines, such as how to deal with aggressive behavior, parent training, and biological aspects of neurodevelopmental disorders. Also, it is expected that publishing the guideline would be helpful to above multiple professions as it is investigated that there are lack of treatment facility and qualified behavioral therapists compared to need at the moment.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.3
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• pp.311-322
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• 2014

This study was conducted to assess the impact of work-related musculoskeletal disorders (WMSDs) on health related quality of life (QoL) in the firefighter under the recent IT environment. The data were collected by face to face interview using a structured questionnaire in the 366 respondents. WMSDs symptoms were measured by a self-assessed questionnaire on symptom table of NIOSH and health-related QoL was measured by SF-36. The prevalence of WMSDs was 38.0% in upper limbs, 35.5% in the low back, 21.6% in lower limbs, and 59.3% in two or more parts of the body. Subjects with symptoms of WMSDs had significantly lower scores in 7 dimensions of QoL except 'emotional role limitation' than those without symptoms of WMSDs at the area of upper extremities (neck, shoulder, arm/wrist, and hand/wrist/fingers). On the other hand, subjects with symptoms of WMSDs had significantly lower scores on all QoL dimensions than those without symptoms of WMSDs at the area of lower back or lower extremities. These results suggest that WMSDs had a negative effect on QoL. Therefore, prevention of WMSDs should be considered intervention strategies for improvement of QoL, especially in firefighters.