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Electroencephalography for Early Detection of Alzheimer’s Disease in Subjective Cognitive Decline
Shim YongSoo,Yang Dong Won,Ho SeongHee,Hong Yun Jeong,Jeong Jee Hyang,Park Kee Hyung,Kim SangYun,Wang Min Jeong,Choi Seong Hye,Kang Seung Wan 대한치매학회 2022 Dementia and Neurocognitive Disorders Vol.21 No.4
Background and Purpose: Early detection of subjective cognitive decline (SCD) due to Alzheimer’s disease (AD) is important for clinical research and effective prevention and management. This study examined if quantitative electroencephalography (qEEG) could be used for early detection of AD in SCD. Methods: Participants with SCD from 6 dementia clinics in Korea were enrolled. 18F-florbetaben brain amyloid positron emission tomography (PET) was conducted for all the participants. qEEG was performed to measure power spectrum and source cortical activity. Results: The present study included 95 participants aged over 65 years, including 26 amyloid PET (+) and 69 amyloid PET (−). In participants with amyloid PET (+), relative power at delta band was higher in frontal (p=0.025), parietal (p=0.005), and occipital (p=0.022) areas even after adjusting for age, sex, and education. Source activities of alpha 1 band were significantly decreased in the bilateral fusiform and inferior temporal areas, whereas those of delta band were increased in the bilateral cuneus, pericalcarine, lingual, lateral occipital, precuneus, posterior cingulate, and isthmus areas. There were increased connections between bilateral precuneus areas but decreased connections between left rostral middle frontal area and bilateral frontal poles at delta band in participants with amyloid PET (+) showed. At alpha 1 band, there were decreased connections between bilateral entorhinal areas after adjusting for covariates. Conclusions: SCD participants with amyloid PET (+) showed increased delta and decreased alpha 1 activity. qEEG is a potential means for predicting amyloid pathology in SCD. Further longitudinal studies are needed to confirm these findings.
Facial Emotion Recognition in Older Adults With Cognitive Complaints
Shim YongSoo 대한치매학회 2023 Dementia and Neurocognitive Disorders Vol.22 No.4
Background and Purpose: Facial emotion recognition deficits impact the daily life, particularly of Alzheimer’s disease patients. We aimed to assess these deficits in the following three groups: subjective cognitive decline (SCD), mild cognitive impairment (MCI), and mild Alzheimer’s dementia (AD). Additionally, we explored the associations between facial emotion recognition and cognitive performance. Methods: We used the Korean version of the Florida Facial Affect Battery (K-FAB) in 72 SCD, 76 MCI, and 76 mild AD subjects. The comparison was conducted using the analysis of covariance (ANCOVA), with adjustments being made for age and sex. The Mini-Mental State Examination (MMSE) was utilized to gauge the overall cognitive status, while the Seoul Neuropsychological Screening Battery (SNSB) was employed to evaluate the performance in the following five cognitive domains: attention, language, visuospatial abilities, memory, and frontal executive functions. Results: The ANCOVA results showed significant differences in K-FAB subtests 3, 4, and 5 (p=0.001, p=0.003, and p=0.004, respectively), especially for anger and fearful emotions. Recognition of ‘anger’ in the FAB subtest 5 declined from SCD to MCI to mild AD. Correlations were observed with age and education, and after controlling for these factors, MMSE and frontal executive function were associated with FAB tests, particularly in the FAB subtest 5 (r=0.507, p<0.001 and r=−0.288, p=0.026, respectively). Conclusions: Emotion recognition deficits worsened from SCD to MCI to mild AD, especially for negative emotions. Complex tasks, such as matching, selection, and naming, showed greater deficits, with a connection to cognitive impairment, especially frontal executive dysfunction.
Effects of Controlled ZnO Surface Morphology upon the PCE of OPV
Won Hyun Shim,Kyu Hwan Lee,Yongsoo Jeong,Young Dok Kim,Dong Chan Lim 한국표면공학회 2010 한국표면공학회 학술발표회 초록집 Vol.2010 No.11
In this study, the effects of ZnO surface morphology on the performance of organic solar cells are systematically investigated. ZnO surface can be nanostructured by ZnO nanoparticles and carbon nanotubes which embedded into ZnO sol-gel solutions. OSCs with ZnO nano-ridge structure show better performance than those with smooth surface. And also, the OSCs fabricated in the present work were also shown to be highly resistant towards (photo-) degradation, suggesting that the strategy of solar cell fabrication introduced herein is of significant importance for various applications.
Harnessing the Power of Voice: A Deep Neural Network Model for Alzheimer’s Disease Detection
Park Chan-Young,Kim Minsoo,Shim YongSoo,Ryoo Nayoung,Choi Hyunjoo,Jeong Ho Tae,Yun Gihyun,Lee Hunboc,Kim Hyungryul,Kim SangYun,Youn Young Chul 대한치매학회 2024 Dementia and Neurocognitive Disorders Vol.23 No.1
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.
ZnO nanosheets decorated with CdSe and TiO2 for the architecture of dye-sensitized solar cells.
Kim, Young Tae,Park, Mi Yeong,Choi, Kang Ho,Tai, Wei Sheng,Shim, Won Hyun,Park, Sun-Young,Kang, Jae-Wook,Lee, Kyu Hwan,Jeong, Yongsoo,Kim, Young Dok,Lim, Dong Chan American Scientific Publishers 2011 Journal of Nanoscience and Nanotechnology Vol.11 No.3
<P>Pure and TiO2- and CdSe-deposited ZnO nanosheets aligned vertically to the surface of ITO (Indium tin oxide) are prepared using electrodeposition, which is used for building blocks of dye sensitized solar cell. A significant improvement in the photovoltaic efficiency can be obtained by depositing TiO2 or CdSe on ZnO. Photoluminescence spectra show that the TiO2 and CdSe nanostructures suppress the recombination of the electron-hole pair of ZnO. We suggest that the interface charge transfer at TiO2-ZnO and CdSe-ZnO should be responsible for the suppression of the electron-hole pair recombination and enhanced solar cell efficiency by TiO2 and CdSe nanostructures.</P>
김영재(Youngjae Kim),유영석(Youngseuck Yoo),심원철(Wonchul Shim),박창성(Changsung Park),정재우(Jaewoo Joung),오용수(Yongsoo Oh) 대한전기학회 2006 대한전기학회 학술대회 논문집 Vol.2006 No.7
This paper presents the effect of driving waveform for piezoelectric bend mode inkjet printhead with optimized mechanical design. Experimental and theoretical studies on the applied driving waveform versus jetting characteristics were performed. The inkier head has been designed to maximize the droplet velocity, minimize voltage response of the actuator and optimize the firing frequency to eject ink droplet. The head design was carried out by using mechanical simulation. The printhead has been fabricated with Si(l00) and SOI wafers by MEMS process and silicon direct bonding method. To investigate how performance of the piezoelectric ceramic actuator influences on droplet diameter and droplet velocity, the method of stroboscopy was used. Also we observed the movement characteristics of PZT actuator with LDV (Laser Doppler Vibrometer) system, oscilloscope and dynamic signal analyzer. Missing nozzles caused by bubbles in chamber were monitored by their resonance frequency. Using the water based ink of viscosity of 4.8 cps and surface tension of 0.025N/m, it is possible to eject stable droplets up to 20㎑, 4.4㎧ and above 8pL at the different applied driving waveforms.
Na Seunghee,Kang Dong Woo,Kim Geon Ha,Kim Ko Woon,Kim Yeshin,Kim Hee-Jin,Park Kee Hyung,Park Young Ho,Byeon Gihwan,Suh Jeewon,Shin Joon Hyun,Shim YongSoo,Yang YoungSoon,Um Yoo Hyun,Oh Seong-il,Wang Sh 대한치매학회 2024 Dementia and Neurocognitive Disorders Vol.23 No.1
Background and Purpose: Dementia subtypes, including Alzheimer’s dementia (AD), dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD), pose diagnostic challenges. This review examines the effectiveness of 18F-Fluorodeoxyglucose Positron Emission Tomography (18F-FDG PET) in differentiating these subtypes for precise treatment and management. Methods: A systematic review following Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines was conducted using databases like PubMed and Embase to identify studies on the diagnostic utility of 18F-FDG PET in dementia. The search included studies up to November 16, 2022, focusing on peer-reviewed journals and applying the gold-standard clinical diagnosis for dementia subtypes. Results: From 12,815 articles, 14 were selected for final analysis. For AD versus FTD, the sensitivity was 0.96 (95% confidence interval [CI], 0.88–0.98) and specificity was 0.84 (95% CI, 0.70–0.92). In the case of AD versus DLB, 18F-FDG PET showed a sensitivity of 0.93 (95% CI 0.88-0.98) and specificity of 0.92 (95% CI, 0.70–0.92). Lastly, when differentiating AD from non-AD dementias, the sensitivity was 0.86 (95% CI, 0.80–0.91) and the specificity was 0.88 (95% CI, 0.80–0.91). The studies mostly used case-control designs with visual and quantitative assessments. Conclusions: 18F-FDG PET exhibits high sensitivity and specificity in differentiating dementia subtypes, particularly AD, FTD, and DLB. This method, while not a standalone diagnostic tool, significantly enhances diagnostic accuracy in uncertain cases, complementing clinical assessments and structural imaging.