Alumni
Jiwoo You
PhD student, University of Groningen (Rijksuniversiteit Groningen, RUG). Jiwoo You is currently a PhD student at the Johann Bernoulli Institute of Mathematics and Computer Science (JBI) of University of Groningen (RUG), Netherlands. He is currently jointly working with the Kapteyn Astronomical Institute. He received his B.Eng. and M.Eng. degree in computer engineering from Kwangwoon University in Seoul, Republic of Korea, in 2011 and 2015, respectively. His research interests include image processing and biomedical signal processing.
Journal Article
Well-fitting Flexible PPG Sensor and Drowsiness Detection Algorism for possible Emotional Service (In preparation) Jiwoo You, Vladislav Kostianovskii, Youngjoo Kim, Eung-Bin Lee, Yong-Young Noh, Choelsoo Park, “Well-fitting Flexible PPG Sensor and Drowsiness Detection Algorism for possible Emotional Service”
Well-fitting Flexible PPG Sensor and Drowsiness Detection Algorism for possible Emotional Service (In preparation) Gi-Seong Ryu, Jiwoo You, Vladislav Kostianovskii, Youngjoo Kim, Eung-Bin Lee, Yong-Young Noh, Choelsoo Park, “Well-fitting Flexible PPG Sensor and Drowsiness Detection Algorism for possible Emotional Service”
Multivariate Time-Frequency Analysis of Uterine Electromyogram for Separation of Term and Preterm Labor (Submitted) J. Ryu, Y. Kim (Equal Contributor), S. M. Lee, D. Sim, K. S. Park and C. Park, “Multivariate Time-Frequency Analysis of Uterine Electromyogram for Separation of Term and Preterm Labor,”
Motor Imagery Classification Using Mu and Beta Rhythms of EEG with Strong Uncorrelating Transform Based Complex Common Spatial Patterns Y. Kim, J. Ryu (Equal Contributor), K. Kim, C. C. Took, D. P. Mandic, C. Park, “Motor Imagery Classification Using Mu and Beta Rhythms of EEG with Strong Uncorrelating Transform Based Complex Common Spatial Patterns”, Computational Intelligence and Neuroscience Sep. 2016
Estimation of Brain Connectivity during Motor Imagery Tasks using Noise-Assisted Multivariate Empirical Mode Decomposition K.B. Lee, K.K. Kim, J. Song, J. Ryu, Y. Kim, C. Park, “Estimation of Brain Connectivity during Motor Imagery Tasks using Noise-Assisted Multivariate Empirical Mode Decomposition”, JEET, vol. 11, 2016.
Time-Frequency Analysis of Electrohysterogram for Classification of Term and Preterm Birth J. Ryu and C. Park, “Time-Frequency Analysis of Electrohysterogram for Classification of Term and Preterm Birth”, IEIE Transactions on Smart Processing and Computing, vol. 4, pp 103-109, Apr. 2015
Perceptual Quality-based Video Coding with Foveated Contrast Sensitivity J. Ryu, D. Sim, “Perceptual Quality-based Video Coding with Foveated Contrast Sensitivity”, Journal of Broadcasting Engineering, vol. 19, no. 4, pp. 468-477, Jul 2014
Low-complexity generalized residual prediction for SHVC K. Kim, J. Ryu, and D. Sim, “Low-complexity generalized residual prediction for SHVC”, IEEK Transactions on Smart Processing & Computing, vol. 2, no. 6, pp. 345-349, Dec. 2013
Rate control to reduce bitrate fluctuation on HEVC J. Yoo, J. Nam, J. Ryu and D. Sim, “Rate control to reduce bitrate fluctuation on HEVC”, IEEK Transactions on Smart Processing & Computing, vol. 1, pp. 152-160, Dec. 2012
No-reference peak signal to noise ratio estimation based on generalized Gaussian modeling of transform coefficient distributions J.-W. Ryu, S.-O. Lee, D.-G. Sim and J.-K. Han, “No-reference peak signal to noise ratio estimation based on generalized Gaussian modeling of transform coefficient distributions”, Optical Engineering, vol. 51, no. 2, pp. 027401, Feb. 2012
Communication
An Accurate Real-time ECG/PPG Peak Detection Using Viterbi Algorithm J. Ryu, C. Park, “An Accurate Real-time ECG/PPG Peak Detection Using Viterbi Algorithm”, 2017 Korean Conference on Semiconductors, HongChoen, Korea, Feb. 2017
ECG-based Drowsiness Level Detection using Hidden Markov Model J. Ryu, Y. Kim, K. Kim, O. Kwon, B. Lee, R. Heo, H. Oh and C. Park, “ECG-based Drowsiness Level Detection using Hidden Markov Model”, 2016 International BioMedical Engineering Conference, Seoul, Korea, Nov. 2016
Hidden Markov Model (HMM)-based Accelerometer Analysis for Sleep Detection J. Ryu and C. Park, “Hidden Markov Model (HMM)-based Accelerometer Analysis for Sleep Detection”, The Korea Society of edical & Biological Engineering, Busan, Korea, March 2016
EEG-based Emotion Recognition using Machine Learning Algorithms J. Ryu and C. Park, “EEG-based Emotion Recognition using Machine Learning Algorithms”, u-Healthcare 2015, Osaka, Japan, Nov. 2015
Classification of Emotion EEG using Machine Learning Algorithms J. Ryu and C. Park, “Classification of Emotion EEG using Machine Learning Algorithms”, IEEK Fall Conference 2015, Wonju, Korea, Nov. 2015
Classification of Motor Imagery EEG using Strong Uncorrelated Transform Complex Common Spatial Patterns Y. Kim, J. Ryu and C. Park, “Classification of Motor Imagery EEG using Strong Uncorrelated Transform Complex Common Spatial Patterns”, IBEC 2014, Gwangju, Korea, Nov. 2014
Classification of Term and Preterm Labor Using Multivariate Empirical Mode Decomposition of EHG Signal J. Ryu, Y. Kim and C. Park, “Classification of Term and Preterm Labor Using Multivariate Empirical Mode Decomposition of EHG Signal”, IBEC 2014, Gwangju, Korea, Nov. 2014
A fast radial distortion correction algorithm based on the statistical analysis of edge orientations J. Ryu, H. Ryu, D. Sim, “A fast radial distortion correction algorithm based on the statistical analysis of edge orientations”, Workshop on Image Processing and Image Understanding (IPIU 2014), Jeju, Korea, Feb.2014
Perceptual Quality-based Transform Coefficient Suppression in High Efficiency Video Coding J. Ryu, S. Lee and D. Sim, “Perceptual Quality-based Transform Coefficient Suppression in High Efficiency Video Coding”, 2014 International Workshop on Advanced Image Technology (IWAIT 2014), Bangkok, Tailand, Jan. 2014
A real-time, morphology-based algorithm for glasses-wearing eye detection J. Ryu, J. Lee, H. Sin, D. Sim, “A real-time, morphology-based algorithm for glasses-wearing eye detection”, Proceedings of the Korean Society of Broadcast Engineers Conference, Seoul, Korea, Nov. 2013
Low-complexity generalized residual prediction for SHVC K. Kim, J. Ryu and D. Sim, “Low-complexity generalized residual prediction for SHVC”, ISO/IEC JTC1/SC29/WG11 (JCTVC-O0107), Geneva, CH, Oct. 2013
Generalized residual prediction with motion vector clipping for SHVC K. Kim, H. Jo, J. Ryu, D. Sim and S.-J. Oh, “Generalized residual prediction with motion vector clipping for SHVC”, ISO/IEC JTC1/SC29/WG11 (JCTVC-N0106), Vienna, AT, Jul 2013
Image-based visual discomfort analysis system for stereoscopic display J. Ryu, S. Lee, D. Sim, “Image-based visual discomfort analysis system for stereoscopic display”, Proceedings of the Korean Society of Broadcast Engineers Conference, Jeju, Korea, Jun 2013
No-reference PSNR estimation of H.264/AVC video J. Ryu, S. Lee, D. Sim, “No-reference PSNR estimation of H.264/AVC video”, Proceedings of the Korean Society of Broadcast Engineers Conference, Jeju, Korea, Jul 2010
Patent
Apparatus for measuring bio signal in the ear internal type KOR 10-2015-0055885, C. Park, J. Ryu, Y. Kim and K. Kim, “Apparatus for measuring bio signal in the ear internal type”, Apr 2015
Apparatus for detecting febrile seizure by measuring electroencephalogram and control method thereof KOR 10-2014-0159157, K. Kim, Y. Kim, C. Park, J. Ryu and Y. Kim, “Apparatus for detecting febrile seizure by measuring electroencephalogram and control method thereof”, Nov. 2014
Method and apparatus for perceptual quality-based video encoder based on JND of visual angle KOR 2014-0016969, J. Ryu, S. Lee and D. Sim, “Method and apparatus for perceptual quality-based video encoder based on JND of visual angle”, Feb 2014
Method and apparatus for generating inter-later reference pictures in multilayered video coding KOR 1020130138706, K. Kim, H. Jo, D. Sim and J. Ryu, “Method and apparatus for generating inter-later reference pictures in multilayered video coding”, Nov 2013
Preprocessing apparatus for a query image and a search object image in a content-based image searcher which uses a sketch query, capable of easily searching an image which is similar to a sketch image through a transformation of the sketch query and a database image and a method thereof KOR 1013260830000, K. Yoon, D. Sim, J. Ryu and W. Lim, “Preprocessing apparatus for a query image and a search object image in a content-based image searcher which uses a sketch query, capable of easily searching an image which is similar to a sketch image through a transformation of the sketch query and a database image and a method thereof”, Oct 2013
Youngjoo Kim
PhD student, University of Groningen (Rijksuniversiteit Groningen, RUG).
Youngjoo Kim is currently employed at ASML's headquaters in the Netherlands. Previously, she was a PhD student in the Scientific Visualization and Computer Graphics (SVCG) group, within the Johann Bernoulli Institute of Mathematics and Computer Science (JBI) of University of Groningen (RUG), Netherlands.
She received her BS and MS degree in computer engineering from Kwangwoon University, Seoul, Republic of Korea, in 2015 and 2017, respectively. Her research interests include visual analytics in big data and blind signal processing with applications in astronomy and biomedicine.
Journal Article
Correlation Assisted Strong Uncorrelating Transform Complex Common Spatial Patterns for Spatially Distant Channel Data Y. Kim, J. You, H. Lee, S.M. Lee, and C. Park, “Correlation Assisted Strong Uncorrelating Transform Complex Common Spatial Patterns for Spatially Distant Channel Data”, Computational Intelligence and Neuroscience, May 15, 2018. (doi:10.1155/2018/4281230)
Multivariate Time-Frequency Analysis of Uterine Electromyogram for Separation of Term and Preterm Labor (Accepted) J. Ryu, Y. Kim (Equal Contributor), S. M. Lee, D. Sim, K. S. Park and C. Park, “Multivariate Time-Frequency Analysis of Uterine Electromyogram for Separation of Term and Preterm Labor”, JEET, 2018.
Flexible and Printed PPG Sensors for Estimation of Drowsiness G.-S. Ryu, J. You, V. Kostianovskii, E.-B. Lee, Y. Kim, C. Park, and Y.-Y. Noh, “Flexible and Printed PPG Sensors for Estimation of Drowsiness”, IEEE Transactions on Electron Devices, Vol. 65, No. 7, pp. 2997-3004, 2018.
Motor Imagery Classification Using Mu and Beta Rhythms of EEG with Strong Uncorrelating Transform Based Complex Common Spatial Patterns Y. Kim, J. Ryu, K.K. Kim, C.C Took, D.P. Mandic, C. Park, “Motor Imagery Classification Using Mu and Beta Rhythms of EEG with Strong Uncorrelating Transform Based Complex Common Spatial Patterns”, Computational Intelligence and Neuroscience, Oct 3, 2016. (doi:10.1155/2016/1489692)
Estimation of Brain Connectivity during Motor Imagery Tasks using Noise-Assisted Multivariate Empirical Mode Decomposition K.B. Lee, K.K. Kim, J. Song, J. Ryu, Y. Kim, C. Park, “Estimation of Brain Connectivity during Motor Imagery Tasks using Noise-Assisted Multivariate Empirical Mode Decomposition”, JEET, vol. 11, 2016.
Strong Uncorrelated Transform Applied to Spatially Distant Channel EEG Data Y. Kim and C. Park, “Strong Uncorrelated Transform Applied to Spatially Distant Channel EEG Data”, IEIE Transactions on Smart Processing and Computing, vol. 4, pp. 97-102, Apr. 2015.
Communications
Classification of Human Attention to Multimedia Lecture H. Lee, Y. Kim, and C. Park, “Classification of Human Attention to Multimedia Lecture”, 32 nd International Conference on Information Networking (ICOIN), Chiang Mai, Thailand, Jan. 2018.
Pattern Recognition of Human Arm Movement Using Deep Reinforcement Learning – W. Seok, Y. Kim, and C. Park, “Pattern Recognition of Human Arm Movement Using Deep Reinforcement Learning”, 32nd International Conference on Information Networking (ICOIN), Chiang Mai, Thailand, Jan. 2018.
Correlation Between Empathy and Experience in Human Emotion from EEG Signal H. Lee, B.S. Hwang, Y. Kim, and C. Park, “Correlation Between Empathy and Experience in Human Emotion from EEG Signal”, 2017 u-Healthcare international conference, Seoul, Korea, Dec. 2017.
Feature Extraction Using Correlation Preserving Transform Based on Complex Common Spatial Patterns Y. Kim and C. Park, “Feature Extraction Using Correlation Preserving Transform Based on Complex Common Spatial Patterns”, 2017 Korean Conference on Semiconductors (KCS), Gangwon-do, Korea, 2017.
ECG-based Drowsiness level detection using Hidden Markov Model J. Ryu, Y. Kim, C. Park, et al., “ECG-based Drowsiness level detection using Hidden Markov Model” IBEC 2016, Seoul, Korea, 2016.
Effects of visual and auditory delta band stimuli on sleep H. Lee, M. S. Yeo, Y. Kim, C. Park, et al., “Effects of visual and auditory delta band stimuli on sleep”, IBEC 2016, Seoul, Korea, 2016.
Stress Measurement Using the Accelerometer Y. Kim, J. Ryu, C. Park, et al., “Stress Measurement Using the Accelerometer”, 2016 International Biomedical Engineering Conference (IBEC), Seoul, Korea, 2016.11
낮잠 중 청각 자극을 통한 운동 기억력 고착화에 관한 연구 김영주, 류지우, 박철수 외., “낮잠 중 청각 자극을 통한 운동 기억력 고착화에 관한 연구”, 2016융합 스마트 클라우드 컴퓨팅 학술대회, 대한민국, 2016.10.
HRV-based Drowsiness Detection using Machine Learning Classifiers 김영주, 류지우, 박철수, “HRV-based Drowsiness Detection using Machine Learning Classifiers”, The Korea Society of Medical & Biological Engineering 2016, Korea, 2016.5
Motor Imagery EEG Classification Using Correlation Preserving Complex Common Spatial Patterns Algorithm Y. Kim, C. Park, “Motor Imagery EEG Classification Using Correlation Preserving Complex Common Spatial Patterns Algorithm”, u-Healthcare, Osaka, Japan, 2015
기계학습을 이용한 운동 심상 뇌전도의 분류 (2015) “기계학습을 이용한 운동 심상 뇌전도의 분류 (2015)”, 김영주, 박철수, 2015 추계 전자공학회
Classification of Motor Imagery EEG using Strong Uncorrelated Transform Complex Common Spatial Patterns Y. Kim, J. Ryu and C. Park, “Classification of Motor Imagery EEG using Strong Uncorrelated Transform Complex Common Spatial Patterns”, IBEC 2014, Gwangju, Korea, 2014
Classification of Term and Preterm Labor Using Multivariate Empirical Mode Decomposition of EHG Signal J. Ryu, Y. Kim and C. Park, “Classification of Term and Preterm Labor Using Multivariate Empirical Mode Decomposition of EHG Signal”, IBEC 2014, Gwangju, Korea, 2014
Patent
뇌파 측정을 통한 열성경련 감지장치 및 그 제어방법 (APPARATUS FOR DETECTING FEBRILE SEIZURE BY MEASURING ELECTROENCEPHALOGRAM AND CONTROL METHOD THEREOF) 김규민, 김영철, 박철수, 류지우, 김영주, 출원번호: 10-2014-0159157 (접수번호 1-1-2014-1100631-12), 출원일자: 2014년 11월 14일
귓속 내장형 생체 신호 측정 장치 (APPARATUS FOR MEASURING BIO SIGNAL IN THE EAR INTERNAL TYPE) 박철수, 류지우, 김영주, 김규민, 출원번호: 10-2015-0055885 (접수번호 1-1-2015-0386333-51), 출원일자: 2015년 04월 21일
Award
Best Paper Award Poster session, IBEC 2016, Best Paper Award, 2016.11.12
Best Paper Award Oral session, 전자공학회 주최 2016 Convergence/Smart/Cloud Computing Conference, 2016.10.15
Graduated First in Class Bachelor’s degree, Dept. of Computer Engineering, KW University, 2015
Best Paper Award Oral session, IBEC 2014, Best Paper Award, 2014.11.22
Engineering Excellence Award Annual Engineering Design Competition, Dept. of Electronics and Communication Engineering, KW University, 2014
Unang Sunarya
Unang Sunarya received his PhD degree in Computer Engineering Department at Kwangwoon University, South korea.
He received Diploma degree from Bandung State Polytechnic (POLBAN), BS and MS degree from Telkom University, Indonesia. His research interest include signal processing and electronic engineering.
Communications
Three Classification Classes of Gait Type Using Step Segmentation
U Sunarya, Y S.H, T Cho, S Baek, S Kim, J Roh, C Park, “Three Classification Classes of Gait Type Using Step Segmentation”, Engineering in Circadian Rhythm and Ubiquitous Healthcare (Uhealthcare), Kookmin University.
Gait Type Classification Using Support Vector Classification
U Sunarya, YS Hariyani, T Cho, YH Soo, S Kim, J Roh, C Park, “Gait Type Classification Using Support Vector Classification”, Korea Society of Medical and Biological Engineering (Kosombe), Kookmin University.
A Spiking Neural Network of Digit Classification Using Prior Probability as Supervised Learning Model Representative
U Sunarya, YS Hariyani, D Sim, C Park, “A Spiking Neural Network of Digit Classification Using Prior Probability as Supervised Learning Model Representative”, Korean Institute of Communications and Information Sciences (KICS) 한국통신학회 학술대회논문집
A study of Monte Carlo localization on robot operating system
Aini, F.R.Q., Jati, A.N., Sunarya, U., “A study of Monte Carlo localization on robot operating system”, 2016 International Conference on Information Technology Systems and Innovation, ICITSI 2016 – Proceedings
Finger vein recognition using perimeter and PCA
Prayogo, Y., Rizal, A., Sunarya, U., “Finger vein recognition using perimeter and PCA “, 2016. International journal of Tomography and Simulation
Design and implementation of wheelchair controller based electroencephalogram signal using microcontroller
Arzak, M.I., Sunarya, U., Hadiyoso, S., “Design and implementation of wheelchair controller based electroencephalogram signal using microcontroller”, 2016. International Journal of electrical and Computer Engineering
Journal Articles
A Binary Sleep Classification of BCG Signal using Random Search-Optimized Random Forest
Unang Sunarya, Hyunsoo Yu, Sayup Kim, Cheolsoo Park. “A Binary Sleep Classification of BCG Signal using Random Search-Optimized Random Forest”, Summer Annual Conference of IEIE, Jun, 2021, Jeju
Feature Analysis of Smart Shoe Sensors for Classification of Gait Patterns
Unang Sunarya, Yuli Sun Hariyani, Taeheum Cho, Jongryun Roh, Joonho Hyeong, Illsoo Sohn, Sayup Kim, Cheolsoo Park, “Feature Analysis of Smart Shoe Sensors for Classification of Gait Patterns”, Sensors 20 (21), 6253
Deep-ACTINet: End-to-End Deep Learning Architecture for Automatic Sleep-Wake Detection Using Wrist Actigraphy
T Cho, U Sunarya, M Yeo, B Hwang, YS Koo, C Park,
“Deep-ACTINet: End-to-End Deep Learning Architecture for Automatic Sleep-Wake Detection Using Wrist Actigraphy”, Electronics 8 (12), 1461
Internet of Things: Low Cost and Wearable SpO2 Device for Health Monitorin
RR Adiputra, S Hadiyoso, YS Hariyani. Internet of Things: Low Cost and Wearable SpO2 Device for Health Monitoring. International Journal of Electrical and Computer Engineering Vol. 8, Issue. 2, (Apr 2018): 939-945.
Yuli Sun Hariyani
Yuli Sun Hariyani received her PhD degree in Computer Engineering Department at Kwangwoon University, South Korea.
She received her BS and MS degree from Telkom University, Indonesia. Her research interest include image processing and biomedical image processing.
Communications
Deep Learning Based Heart Rate Estimation Using Smart Shoes Sensor
Suwhan Baek, Heesang Eom, Yuli-Sun Hariyani, Gwangho Kim, Jongryum Roh, Sayup Kim, Cheolsoo Park, “Deep Learning Based Heart Rate Estimation Using Smart Shoes Sensor,” 2020 IEEE International Conference on Consumer Electronics – Asia (ICCE-Asia), 2020, pp. 1-4
Dual Attention-Based Deep Learning Method for Nailfold Capillary Segmentation Yuli Sun Hariyani, Heesang Eom, Cheolsoo Park, “Dual Attention-Based Deep Learning Method for Nailfold Capillary Segmentation”,International Engineering in Medicine and Biology Conference, Berlin, Germany, 2019 07
YU-NET: An Improved Deep Learning method for Nailfold Capillary Segmentation Yuli Sun Hariyani, 엄희상, 박철수, “YU-NET: An Improved Deep Learning method for Nailfold Capillary Segmentation”, 대한의용생체공학회 춘계학술대회, 여수, 2019.05
A Spiking Neural Network of Digit Classification Using Prior Probability as Supervised Learning Model Representative
U Sunarya, Y Hariyani, D Sim, C. Park, “A Spiking Neural Network of Digit Classification Using Prior Probability as Supervised Learning Model Representative”, 한국통신학회, Jan. 23-25th 2019, 평창
Automated Capillary Image Segmentation using Deep Learning
Byeon-Ghwi Kim, Yuli Sun Hariyani, Cheolsoo Park, “Automated Capillary Image Segmentation using Deep Learning”, Ubiquitous Healthcare 2018 in Kyoto, International Science Innovation Building, Kyoto University, Dec. 11th -13th, 2018.
Nailfold Capillary Segmentation using Deep Learning
Yuli Sun Hariyani, C. Park*, “Nailfold Capillary Segmentation using Deep Learning”, SMIT2018-IBEC2018 Joint Conference in Grand Walkerhill Hotel, Seoul, Korea, November 8-10th, 2018
Journal Articles
Deep Learning-Based Optimal Smart Shoes Sensor Selection for Energy Expenditure and Heart Rate Estimation
Heesang Eom, Jongryun Roh, Yuli Sun Hariyani, Suwhan Baek, Sukho Lee, Sayup Kim, Cheolsoo Park, “Deep Learning-Based Optimal Smart Shoes Sensor Selection for Energy Expenditure and Heart Rate Estimation”, MDPI Sensors, Vol.21(21), SCI, IF=3.576
Optimization of Deep Neural Networks for Heartrate Estimation from Face Video Stream to Implement Smart Health-City
G. Kim, Y. S. Hariyani, S. Han, H. Lee, R. Sohn, and C. Park, “Optimization of Deep Neural Networks for Heartrate Estimation from Face Video Stream to Implement Smart Health-City,” The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 12, pp. 2220–2228, 2020.
Automated White Blood Cell Counting in Nailfold Capillary Using Deep Learning Segmentation and Video Stabilization
Byeonghwi Kim*, Yuli Sun Hariyani*, Young-Ho Cho, Cheolsoo Park, “Automated White Blood Cell Counting in Nailfold Capillary Using Deep Learning Segmentation and Video Stabilization”, MDPI Sensors, Vol.20(24), SCI, IF=3.275
Feature Analysis of Smart Shoe Sensors for Classification of Gait Patterns Unang Sunarya*, Yuli Sun Hariyani*, Taeheum Cho, Jongryun Roh, Joonho Hyeong , Illsoo Sohn, Sayup Kim, Cheolsoo Park, “Feature Analysis of Smart Shoe Sensors for Classification of Gait Patterns”, MDPI Sensors, Vol.20(21), SCI, IF=3.275
End-to-End Deep Learning Architecture for Continuous Blood Pressure Estimation Using Attention Mechanism
Heesang Eom, Dongseok Lee, Seungwoo Han, Yuli Sun Hariyani, Yonggyu Lim, Illsoo Sohn, Kwangsuk Park, and Cheolsoo Park, “End-to-End Deep Learning Architecture for Continuous Blood Pressure Estimation Using Attention Mechanism”, MDPI Sensors, Vol.20(8), SCI, IF=3.275
DA-CapNet: Dual Attention Deep Learning based on U-Net for Nailfold Capillary Segmentation Yuli Sun Hariyani, Heesang Eom, Cheolsoo Park, “DA-CapNet: Dual Attention Deep Learning based on U-Net for Nailfold Capillary Segmentation”, in IEEE Access, vol. 8, pp. 10543-10553, 2020. SCIE, IF=3.367
Internet of Things: Low Cost and Wearable SpO2 Device for Health Monitoring
RR Adiputra, S Hadiyoso, YS Hariyani, “Internet of Things: Low Cost and Wearable SpO2 Device for Health Monitoring”, International Journal of Electrical and Computer Engineering Vol. 8, Issue. 2, (Apr 2018): 939-945, IF=0.68
More Details >>
Youngchul Kim
CEO of PAS(www.pas07.com). He received a BS degree in computer engineering from kwangwoon University in Seoul, South Korea
Journal Article
Multimodal Drowsiness Detection Methods using Machine Learning AlgorithmsIEIE Transactions on Smart Processing & Computing Vol.7 No.5, October 2018
Patent
사용자의 졸음의 정도 혹은 집중력의 정도를 측정하기 위한 방법 및 이를 위한 웨어러블 디바이스(Wearable device and method for measuring the degree of drowsiness or concetration of the user) 박철수, 석우준, 여민수, 이희준, 김영철, 전태욱 출원번호: 10-2017-0058645, 출원일자: 2017년 05월 11일
Minsoo Yeo
Researcher at TaeWoong Medical Digital healthcare Divison.
Minsu Yeo received a BS degree in biomedical engineering. His research interests include bio-medical signal processing and embedded software.
Communications
손목 가속도 센서와 머신러닝 알고리즘을 이용한 자동 수면 패턴 분류 M Yeo, Y Koo, C Park, “손목 가속도 센서와 머신러닝 알고리즘을 이용한 자동 수면 패턴 분류”, 2018 대한의용생체공학회 춘계학술대회, 충주, 2018.05.
Flow-based Malware Detection Using Convolutional Neural Network M. Yeo, Y. Koo, Y. Yoon, T. Hwang, J. Ryu, J. Song, C. Park, “Flow-based Malware Detection Using Convolutional Neural Network”, The 32nd International ICOIN (Conference on Information Networking), Thailand, Chiang Mai, 2018
Convolutional Neural Network를 이용한 IoT기기의 주관적 수면데이터의 패턴 분석 여민수, 구용서, 박철수, “Convolutional Neural Network를 이용한 IoT기기의 주관적 수면데이터의 패턴 분석”, 제 52회 대한생체의공학회 추계학술대회, 한국, 전주, 2017
손목 팔찌의 가속도 자료를 사용한 자동 수면단계 감지 방법 여민수, 류지우, 박철수 “손목 팔찌의 가속도 자료를 사용한 자동 수면단계 감지 방법”, 제 24회 한국 반도체 학술대회, 한국, 강원도, 2017
Effects of Visual and Auditory Delta Band Stimuli on Sleep Heejun Lee, Minsoo Yeo, Youngjoo Kim, Hongjoo Lee, Junhee Jang, Jinwoo Yang, and Cheolsoo Park, “Effects of Visual and Auditory Delta Band Stimuli on Sleep”, IBEC (International Biomedical Engineering), Korea, Korea University, 2016
Automated Sleep Scoring Using Accelerometer Data from Wrist band M. Yeo, W. Park, D. Choi, D. Kim, S. Yoon, J. Ryu, Y. Koo and C. Park, “Automated Sleep Scoring Using Accelerometer Data from Wrist band”, IBEC (International Biomedical Engineering), Korea, Korea University, 2016
Journal Article
Automatic detection of sleep stages based on accelerometer signals from a wristband M. Yeo, Y. Koo, C. Park, “Automatic detection of sleep stages based on accelerometer signals from a wristband”, IEEK (Transactions on Smart Processing and Computing), Korea, 2016
Patent
사용자의 졸음의 정도 혹은 집중력의 정도를 측정하기 위한 방법 및 이를 위한 웨어러블 디바이스 (Wearable device and method for measuring the degree of drowsiness or concentration of the user) 박철수, 석우준, 여민수, 이희준, 김영철, 전태욱 출원번호: 10-2017-0058645 , 출원일자: 2017년 05월 11일
Awards
우수 포스터상 수상 포스터 부문, 대한의용생체공학회 춘계학술대회, 2018.05, “손목 가속도 센서와 머신러닝 알고리즘을 이용한 자동 수면 패턴 분류”
최우수 포스터 논문상 포스터 부문, 대한생체의공학회 추계학술대회, 2017.11.10, “Convolutional Neural Network를 이용한 IoT기기의 주관적 수면데이터의 패턴 분석”
Best Paper Award Poster session, IBEC 2016, 2016.11.12 “Effects of Visual and Auditory Delta Band Stimuli on Sleep”
Top Student Paper Award Oral session, IBEC 2016, 2016.11.12 “Automated Sleep Scoring Using Accelerometer Data from Wrist band”
Heejun Lee
PhD student, University of Groningen (Rijksuniversiteit Groningen, RUG).
Heejun Lee used to be a Researcher of LG.
He received a BS degree in computer engineering from Kwangwoon University in Seoul, South Korea. His research interests include bio-medical signal processing and wareable IT.
Journal Articles
Deep EEGNet: A Bayesian optimization based end-to-end deep learning design methodology for human emotion reconition using EEG signals Hwang Bosun, Lee Hee Jun, Jung Sung Woo, Park Cheolsoo, Zhang Byoung-Tak, “Deep EEGNet: A Bayesian optimization based end-to-end deep learning design methodology for human emotion reconition using EEG signals”, Telemedicine and e-Health, 2018
Correlation Assisted Strong Uncorrelating Transform Complex Common Spatial Patterns for Spatially Distant Channel Data Y. Kim, J. You, H. Lee, S.M. Lee, and C. Park, “Correlation Assisted Strong Uncorrelating Transform Complex Common Spatial Patterns for Spatially Distant Channel Data”, Computational Intelligence and Neuroscience, 2017
Lexical Planning in L2 Sentence Production: Evidence from ERPs J.Kwon*, H.Lee*, J.Shin, W.Chung, M.Park & C.Park,”Lexical Planning in L2 Sentence Production: Evidence from ERPs”,Journal of Cognitive Science vol 18-4, p367-389(23pages), 2018 (* First Author)
Communications
딥러닝 뇌파 분석을 통한 멀티미디어 강의 시청 집중도 분류 H Lee, C Park, “딥러닝 뇌파 분석을 통한 멀티미디어 강의 시청 집중도 분류”, 대한의용생체공학회 춘계학술대회, 충주, 2018.05.
Classification of Human Attention to Multimedia Lecture H. Lee, Y. Kim, C. Park,”Classification of Human Attention to Multimedia Lecture”, ICOIN(International Conference on Information Networking), Chiang Mai, Thailand, 2018
Correlation Between Empathy and Experience in Human Emotion from EEG Signal H. Lee, B.S Hwang, Y. Kim, C. Park, “Correlation Between Empathy and Experience in Human Emotion from EEG Signal”,U-healthcare, Seoul, Korea, 2017
멀티미디어 강의 중 집중력이 뇌파에 미치는 영향 이희준, 김종훈, 정민우, 이 진, 임영범, 박철수, “멀티미디어 강의 중 집중력이 뇌파에 미치는 영향”, KOSOMBE(Korea Society of Medical & Biological Engineering), Jeonju, Korea, 2017
Effects of visual and auditory delta band stimuli on sleep H. Lee, M. S. Yeo, H. J. Lee, D. S. Lee, J. H. Jang, J. W. Yang, C. Park, “Effects of visual and auditory delta band stimuli on sleep”, IBEC 2016, Seoul, Korea, 2016
Patent
웨어러블 디바이스가 근전도 패턴을 이용하여 사용자가 원하는 액션을 수행하는 방법 (Method for performing desired action of user using EMG pattern by wearable device)
박철수, 이희준, 석우준 전태욱 출원번호: 10-2018-0075853 , 출원일자: 2018년 06월 29일
사용자의 집중도를 판단하는 방법 및 이를 위한 웨어러블 디바이스 (Wearable device and method for determining concentration degree of user)
박철수 이희준 여민수 한승우 김규민, 출원번호: 10-2018-0060627 , 출원일자: 2018년 05월 28일
사용자의 졸음의 정도 혹은 집중력의 정도를 측정하기 위한 방법 및 이를 위한 웨어러블 디바이스 (Wearable device and method for measuring the degree of drowsiness or concentration of the user) 박철수, 석우준, 여민수, 이희준, 김영철, 전태욱 출원번호: 10-2017-0058645 , 출원일자: 2017년 05월 11일
Awards
우수 포스터상 수상 포스터 부문, 대한의용생체공학회 춘계학술대회, 2018.05, “딥러닝 뇌파 분석을 통한 멀티미디어 강의 시청 집중도 분류”
Best Poster Award Poster session, IBEC 2016, 2016.11.12 “Effects of visual and auditory delta band stimuli on sleep”
소리와 빛 자극이 수면 중에 미치는 영향에 대한 연구 (2016) 이희준, 여민수 2016 KWIX 우수상 수상
소리와 빛 자극이 수면 중에 미치는 영향에 대한 연구 (2016) 이희준, 여민수 2016 My Capstone 장려상 수상
Woojoon Seok
Researcher at Samsung DS(2021).
Researcher at KITECH(2020).
Woojoon Seok received a BS degree in robotics from Kwangwoon University in Seoul, South Korea. His research interests include bio-medical signal processing and machine learning algorithms
Communications
Pattern Recognition of Human Arm Movement Using Deep Reinforcement Learning W. Seok, C.Park,”Pattern Recognition of Human Arm Movement Using Deep Reinforcement Learning”, ICOIN, Chiang Mai, Thailand, January 10-12, 2018
강화학습 알고리즘을 통한 팔 동작 패턴 인식 석우준, 박철수, “강화학습 알고리즘을 통한 팔 동작 패턴 인식 “, 추계의용생체공학회, 대한민국, 전주, 2017
Patent
사용자의 졸음의 정도 혹은 집중력의 정도를 측정하기 위한 방법 및 이를 위한 웨어러블 디바이스 (Wearable device and method for measuring the degree of drowsiness or concentration of the user) 박철수, 석우준, 여민수, 이희준, 김영철, 전태욱 출원번호: 10-2017-0058645 , 출원일자: 2017년 05월 11일
Taehum Cho
Researcher at Modnbio.
Taeheum Cho is senior in Industrial and Organizational Psychology from Kwangwoon University in Seoul, South Korea. His research interests include internet of things and machine learning algorithms.
Communications
Classification of Motor Imagery Tasks Through Optimal Principal Components Selected Using Reinforcement Learning T. Cho, H. Lee, W. Seok, C. Park, “Classification of Motor Imagery Tasks Through Optimal Principal Components Selected Using Reinforcement Learning”, Ubiquitous Healthcare 2018 in Kyoto, International Science Innovation Building, Kyoto University, Dec. 11th -13th, 2018
Heesang Eom
Researcher at Seoul National University Hospital(Military Service).
Heesang Eom received a BS degree in software engineering from Korea Polytechnic University in Gyeonggi, South Korea. His research interests include bio-signal processing, deep learning algorithms and model optimization.
Journal Article
End-to-End Deep Learning Architecture for Continuous Blood Pressure Estimation Using Attention Mechanism
Heesang Eom, Dongseok Lee, Seungwoo Han, Yuli Sun Hariyani, Yonggyu Lim, Illsoo Sohn, Kwangsuk Park, Cheolsoo Park, “End-to-End Deep Learning Architecture for Continuous Blood Pressure Estimation Using Attention Mechanism”, Sensors 2020, 20(8), 2338. SCIE
DA-CapNet: Dual Attention Deep Learning based on U-Net for Nailfold Capillary Segmentation
Yuli Sun Hariyani, Heesang Eom, Cheolsoo Park, “DA-CapNet: Dual Attention Deep Learning based on U-Net for Nailfold Capillary Segmentation”, in IEEE Access, vol. 8, pp. 10543-10553, 2020. SCIE
Detection of Arrhythmia using 1D Convolution Neural Network with LSTM model
S. Han, W. Lee, H. Eom, J. Kim and C. Park, “Detection of Arrhythmia using 1D Convolution Neural Network with LSTM model”, IEIE Transactions on Smart Processing and Computing, Vol.9 No.04, 2020
Communications
Blood Pressure Estimation Using Deep Learning based on Attention Mechanism
Heesang Eom, Dongseok Lee, Seungwoo Han, Kwangsuk Park and Cheolsoo Park, “Blood Pressure Estimation Using Deep Learning based on Attention Mechanism”, u-Healthcare 2019, Dec 2019, Kookmin Universit
End-to-End 딥러닝 기반 부정맥 분류 연구
Seungwoo Han, Heesang Eom, Cheolsoo Park, “End-to-End 딥러닝 기반 부정맥 분류 연구”, KOSOMBE, Nov 7-9 2019, Inchon
Attention 메커니즘을 활용한 CNN-BiGRU 기반 수축기 혈압 추정
엄희상, 한승우, 이동석, 박광석, 박철수, “Attention 메커니즘을 활용한 CNN-BiGRU 기반 수축기 혈압 추정”, 대한의용생체공학회 추계학술대회, 인천, 2019.11
Blood Pressure Estimation Based on Convolutional Neural Network using ECG, PPG and BCG
H. Eom, S. Han, D. Lee, K. Park and C. Park, “Blood Pressure Estimation Based on Convolutional Neural Network using ECG, PPG and BCG”, International Engineering in Medicine and Biology Conference, Berlin, Germany, 2019 07
심전도와 맥파를 이용한 강화학습 기반 혈압 추정 알고리즘 한승우, 엄희상, 조태흠, 박광석, 박철수, “심전도와 맥파를 이용한 강화학습 기반 혈압 추정 알고리즘”, 대한의용생체공학회 춘계학술대회, 여수, 2019.05
심전도, 맥파 및 심탄도를 이용한 딥러닝 기반 혈압 추정
엄희상, 한승우, 박광석, 이동석, 박철수, “심전도, 맥파 및 심탄도를 이용한 딥러닝 기반 혈압 추정”, 대한의용생체공학회 춘계학술대회, 여수, 2019.05
심전도와 맥파를 이용한 딥러닝 기반 실시간 혈압 추정 연구
한승우, 엄희상, 박광석, 이동석, 박철수, “심전도와 맥파를 이용한 딥러닝 기반 실시간 혈압 추정 연구”, 한국통신학회 동계종합학술발표회, 평창, 2019.01
Patent
사용자의 혈압을 추정하기 위한 장치 및 방법 (Apparatus and Method for estimating user’s Blood Pressure) 박철수, 엄희상, 한승우, 율리 순 하리야니, 출원번호: 10-2019-0179386 , 출원일자: 2019년 12월 31일 사용자 인증 장치 및 방법 (Apparatus and method for learning user’s operation intention using artificial neural network 박철수, 율리 순 하리야니, 엄희상, 출원번호: 10-2018-0160757, 출원일자: 2018년 12월 13일
Wongyu Lee
Researcher at FOUNT.
Wongyu Lee received his BS degree in Mathematics from University of Minnesota-twin cities in the U.S. with minor in Computer science and Physics.
His research interests include machine learning algorithms, specifically, spiking neural network(SNN) and reinforcement learning.
Journal Article
Detection of Arrhythmia using 1D Convolution Neural Network with LSTM model
S. Han, W. Lee, H. Eom, J. Kim and C. Park, “Detection of Arrhythmia using 1D Convolution Neural Network with LSTM model”, IEIE Transactions on Smart Processing and Computing, Vol.9 No.04, 2020
Communications
Spiking Neural Network를 이용한 비지도 학습기반 MNIST data 분류
Seungwoo Han
PhD student, Tokyo University of Agriculture and Technology(東京農工大学, 日本).
Seungwoo Han received a MSc degree in software engineering from Kwangwoon University in Seoul, South Korea. His research interests include graph signal processing and representation learning.
Journal Article
Patent
사용자의 혈압을 추정하기 위한 장치 및 방법 (Apparatus and Method for estimating user’s Blood Pressure)
박철수, 엄희상, 한승우, 율리 순 하리야니, 출원번호: 10-2019-0179386 , 출원일자: 2019년 12월 31일
랜덤 소수 생성 방법 및 그를 위한 장치 (Method and Apparatus for generating Random Prime)
박철수, 유호영, 조만희, 한승우, 등록번호: 10-2217-9280000 , 등록일자: 2021년 02월 15일
사용자의 집중도를 판단하는 방법 및 이를 위한 웨어러블 디바이스 (Wearable device and method for determining concentration degree of user)
박철수, 이희준, 여민수, 한승우, 김규민, 출원번호: 10-2018-0060627 , 출원일자: 2018년 05월 28일
Certificate
Craftsman Motor Vehicles Maintenance
Human Resources Development Service of Korea, 취득일자: 2016년 9월 23일
Juhyeong Kim
Researcher at WOORI BANK.
Researcher at KETI(2021.08~2022.06)
Juhyeong Kim received his BS degree in Computer Engineering from Kwangwoon University in Seoul, South Korea. His research interests include machine learning algorithms, specifically, deep learning, reinforcement learning, and automated machine learning (AutoML).
Journal Article
Detection of Arrhythmia using 1D Convolution Neural Network with LSTM model S. Han, W. Lee, H. Eom, J. Kim and C. Park, “Detection of Arrhythmia using 1D Convolution Neural Network with LSTM model”, IEIE Transactions on Smart Processing and Computing, Vol.9 No.04, 2020
Communications
심전도 특징을 이용한 강화학습 개인 인증 시스템 김주형, 조태흠, 석우준, 박철수, “심전도 특징을 이용한 강화학습 개인 인증 시스템”, 대한의용생체공학회 추계학술대회, 인천, 2019.11
Reinforcement Learning Personal Authentication System Using ECG Feature J.H Kim, T.H Cho, W.J Seok, C.S Park, “Reinforcement Learning Personal Authentication System Using ECG Feature”, u-Healthcare 2019, Dec 2019, Kookmin University
Youjung Seo
Researcher at KLA.
Youjung Seo received her BS degree in psychology from Chung-Ang university, South Korea.
Her research interests include in biomedical signal processing, e-health and machine learning algorithms.
Journal Article
Continuous Blood Pressure Estimation using a 1D Convolutional Neural Network and an Attention Mechanism Seo, Y., Lee, J., Sunarya, U., Lee, K., Park, C. (2022), “Continuous Blood Pressure Estimation using a 1D Convolutional Neural Network and an Attention Mechanism” IEIE Transactions on Smart Processing & Computing, SCIE, IF=0.83
Communications
PPG, ECG 신호를 사용한 머신러닝 기반 혈압 추정 및 보정 알고리즘 서유정, 이원규, 손량희, 박철수, “PPG, ECG 신호를 사용한 머신러닝 기반 혈압 추정 및 보정 알고리즘”, 대한전자공학회 하계종합학술대회, 2021.06.30-07.02
머신러닝 기반 혈압 보정 알고리즘 서유정, 손량희, 박철수, “머신러닝 기반 혈압 보정 알고리즘”, 대한의용생체공학회 온라인 춘계학술대회, Online, 2021.05.12-14
웨어러블 디바이스를 이용한 PTT 혈압 예측을 위한 머신러닝 알고리즘 보정 방법 서유정, 이원규, 손량희, 박철수, “웨어러블 디바이스를 이용한 PTT 혈압 예측을 위한 머신러닝 알고리즘 보정 방법”, 대한전자공학회 추계학술대회, 광주, 2020.11.27 more detail >>
Ballistocardiogram을 이용한 딥러닝 기반 혈압 추정 서유정, 이원규, 고건영, 김대현, 조현우, 최재혁, 유재원, 손량희, 박철수, “Ballistocardiogram을 이용한 딥러닝 기반 혈압 추정”, 대한전자공학회 신호처리합동학술대회, Online, 2020.09.24-25
Patent
누워 지내는 환자를 헬스케어하기 위한 장치 (APPARATUS FOR HEALTH CARE OF PATIENTS WHO LIE DOWN) 박철수, 서유정, 유현수, 박윤태, 출원번호: 10-2021-0188903, 출원일자: 2021년 12월 27일
사용자의 손목에 착용 가능한 혈압 측정 장치 (BLOOD PRESSURE MEASURING DEVICE WERABLE ON WRIST OF USER) 박철수, 서유정, 이원규, 엄희상, 손량희, 출원번호: 10-2020-0160459, 출원일자: 2020년11월2일
Hyunsoo Yu
Researcher at LG Innotek.
Hyunsoo Yu received his BS degree in Robotics Engineering from Kwangwoon University in Seoul, South Korea.
His reasearch interests include in experiment setting, signal processing, machine learning and artificial Intelligence.
He is managing all experimental devices in this lab.
Journal Article
Automatic Sleep Scoring Using Intrinsic Mode based on Interpretable Deep Neural Networks.
Baek, J., Lee, C., Yu, H., Baek, S., Lee, S., Leec, S. and Park, C. (2022). Automatic Sleep Scoring Using Intrinsic Mode based on Interpretable Deep Neural Networks. IEEE Access, pp.1–1.
Explainable Sleep Staging Algorithm using a Single-channel Electroencephalogram.
Suwhan Baek, Jeawoo Baek, Hyunsoo Yu, Chungseop Lee, Cheolsoo Park.(2022).Explainable Sleep Staging Algorithm using a Single-channel Electroencephalogram. IEIE Transactions on Smart Processing & Computing,11(1),8-13.
Effect of a Recliner Chair with Rocking Motions on Sleep Efficiency.
Baek, S.; Yu, H.; Roh, J.; Lee, J.; Sohn, I.; Kim, S.; Park, C. Effect of a Recliner Chair with Rocking Motions on Sleep Efficiency. Sensors 2021, 21, 8214. (Co-first author)
End-to-end Automatic Sleep Staging Algorithm using Convolution Neural Network and Bidirectional LSTM.
Jaewoo Baek, Suwan Baek, HyunSu Yu, JungHwan Lee, Cheolsoo Park.(2021).End-to-end Automatic Sleep Staging Algorithm using Convolution Neural Network and Bidirectional LSTM. IEIE Transactions on Smart Processing & Computing, 10(6), 464-468.
Effect of an Inflatable Air Mattress with Variable Rigidity on Sleep Quality
Yu H, Shin O, Kim S, Park C, “Effect of an Inflatable Air Mattress with Variable Rigidity on Sleep Quality”, MDPI Sensors 2020, 20, 5317
more details >>
Communications
Convolutional Neural Network based Empirical Mode Decomposition for Time Series Data Analysis
Hyunsoo Yu, Suwhan Baek, Cheolsoo Park. “Convolutional Neural Network based Empirical Mode Decomposition for Time Series Data Analysis”, Summer Annual Conference of IEIE, Jun, 2021, Jeju
A Binary Sleep Classification of BCG Signal using Random Search-Optimized Random Forest
Unang Sunarya, Hyunsoo Yu, Sayup Kim, Cheolsoo Park. “A Binary Sleep Classification of BCG Signal using Random Search-Optimized Random Forest”, Summer Annual Conference of IEIE, Jun, 2021, Jeju
Decision Support System for Estimating Sleep Stages Using Single Channel EEG with Attention Mechanism
Suwhan Baek, Jaewu Baek, Hyunsoo Yu, Cheolsoo Park. “Decision Support System for Estimating Sleep Stages Using Single Channel EEG with Attention Mechanism”, Summer Annual Conference of IEIE, Jun, 2021, Jeju
Sleep Staging Automation from EEG signal with CNN
Suwhan Baek, Hyunsoo Yu, Cheolsoo Park. “Sleep Staging Automation from EEG signal with CNN”, Autumn Annual Conference of IEIE, Nov, 2020, Gwangju
more details >>
Comparison of Sleep Quality according to Swing Trajectories of the Reclining Mechanism
Jongryun Roh, Hyunsoo Yu, Cheolsoo Park, Sayup Kim. “Comparison of Sleep Quality according to Swing Trajectories of the Reclining Mechanism”, Autumn Conference Ergonomics Society of Korea, Oct, 2020, Jeju more details >>
Convolutional Neural Network Model Optimization for Single Channel Sleep Electroencephalogram Analysis
Hyunsoo Yu, Seungwoo Han, Cheolsoo Park, “Convolutional Neural Network Model Optimization for Single Channel Sleep Electroencephalogram Analysis”, Summer Annual Conference of IEIE, Aug. 2020, Jeju
more details >>
Jaewoo Baek
Researcher at Hanwha Systems.
Jaewoo Beak(백재우) received his B.Eng. and M.Eng. degree in computer engineering from Kwangwoon University in Seoul, Republic of Korea
His reasearch interests include biological signal processing ,machine learning, deep learning and reinforcement learning.
Journal Article
Explainable Sleep Staging Algorithm using a Single-channel Electroencephalogram. Suwhan Baek, Jeawoo Baek, Hyunsoo Yu, Chungseop Lee, Cheolsoo Park.(2022).Explainable Sleep Staging Algorithm using a Single-channel Electroencephalogram. IEIE Transactions on Smart Processing & Computing,11(1),8-13.
Automatic Sleep Scoring Using Intrinsic Mode based on Interpretable Deep Neural Networks. Jaewoo Baek, Choongseop Lee, Hyunsoo Yu, Suwhan Baek, Seokmin Lee, Seungmin Lee, and Cheolsoo Park, “Automatic Sleep Scoring Using Intrinsic Mode based on Interpretable Deep Neural Networks.”, IEEE Access, 30 March 2022, IF=3.367 more details >>
End-to-end Automatic Sleep Staging Algorithm using Convolution Neural Network and Bidirectional LSTM. Jaewoo Baek, Suwan Baek, HyunSu Yu, JungHwan Lee, and Cheolsoo Park. “End-to-end Automatic Sleep Staging Algorithm using Convolution Neural Network and Bidirectional LSTM.”, IEIE Transactions on Smart Processing & Computing, Dec 2021, 464-468, IF=0.83 more details >>
Communications
Decision Support System for Estimating Sleep Stages Using Single Channel EEG with Attention Mechanism Suwhan Baek, Jaewu Baek, Hyunsoo Yu, Cheolsoo Park. “Decision Support System for Estimating Sleep Stages Using Single Channel EEG with Attention Mechanism”, Summer Annual Conference of IEIE, Jun, 2021, Jeju
EEG 단체널 기반 Inception 네트워크와 순환 신경망을 결합한 자동 수면 단계 분류기 백재우, 이석민, 이영준, 이호찬, 박철수, “EEG 단체널 기반 Inception 네트워크와 순환 신경망을 결합한 자동 수면 단계 분류기”, 대한전자공학회 하계학술대회, 제주, 2021.06
Award
제 5회 산학연계 SW프로젝트 전시회 총장상(2021) 프로젝트명: 딥러닝 및 Auto ML 기반 시계열 데이터 분석을 통한 일상 생활 패턴 분석
Suwhan Baek
Researcher at Posco Holdings.
Suwhan Baek received his B.Eng. and M.Eng. degree in computer engineering from Kwangwoon University in Seoul, Republic of Korea
His research interests include overall Medical AI and Auto ML.
He is also attracted by reinforcement learning, generative models, and SNN
Journal Article
Communications
Deep Learning Based Heart Rate Estimation Using Smart Shoes Sensor
Baek, Suwhan, et al. “Deep Learning Based Heart Rate Estimation Using Smart Shoes Sensor”, 2020 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia). IEEE, 2020.
Arrhythmia Classification Using 1D-2D Conversion
S. Baek, S. Han, J. Lee, W. Lee, C. Park, “Arrhythmia Classification Using 1D-2D Conversion”, u-Healthcare 2019, Dec 2019, Kookmin University
Patents
“Method For Measuring Health Condition Of User And Apparatus Therefor”, S. Baek, C. Park, Kor-patents 10-2019-0157809, 2019.11
Saehim Kwon
Researcher at EMMA.
Saehim Kwon receivecd his BS degree in Software Engineering from Gangneung-Wonju National University in Wonju, South Korea.
His research interests include e-health, deep learning and machine learning algorithms.
Journal Article
Blood Pressure Estimation and Its Recalibration Assessment Using Wrist Cuff Blood Pressure Monitor. Youjung Seo, Saehim Kwon, Unang Sunarya, Sungmin Park, Kwangsuk Park, Daewoon Jung, Youngho Cho and Cheolsoo Park, “Blood Pressure Estimation and Its Recalibration Assessment Using Wrist Cuff Blood Pressure Monitor.”, Biomedical Engineering Letters, 23 March 2023
Communications
Patent
재보정을 이용한 혈압 측정 장치 박철수, 권새힘, 출원번호: 10-2022-0180132, 출원일자: 2022년 12월 21일
Choongseop Lee
Choongseop Lee(이충섭) received his B.Eng. and M.Eng. degree in computer engineering from Kwangwoon University in Seoul, Republic of Korea His reasearch interests include machine learning and computational neuroscience.
Journal Article
Patent
몽유병을 감지하는 엣지 디바이스
박철수, 양근보, 이충섭, 출원번호: 10-2022-0164099, 출원일자: 2022년 12월.
손톱주름 모세혈관 속 백혈구의 수를 산출하기 위한 뉴로모픽 컴퓨팅 장치
(NEUROMORPHIC COMPUTING DEVICE FOR CALCULATING THE NUMBER OF WHITE BLOOD CELLS IN THE CAPILLARIES OF THE NAIL FOLD)
박철수, 이충섭, 율리 선 하리야니, 백수환, 출원번호: 10-2021-0190464, 출원일자: 2021년 12월 28일
뉴로모픽 컴퓨팅 장치 (NEUROMORPHIC COMPUTING DEVICE)
박철수, 이원규, 이충섭, 출원번호: 10-2020-0161286, 출원일자: 2020년 11월 26일.
Geunbo Yang
Geunbo Yang(양근보) received his BS degree and MS degree in Computer Engineering from Kwangwoon University in seoul, South Korea. His research interests include machine learning algorithms, and SNN.
Journal Article
Unsupervised Spiking Neural Network with Dynamic Learning of Inhibitory Neurons
G Yang, W Lee, Y Seo, C Lee, W Seok, J Park, D Sim, C Park, “Unsupervised Spiking Neural Network with Dynamic Learning of Inhibitory Neurons”, MDPI Sensors, 2023, 7232, IF=3.847.
Intelligent Feature Selection for ECG-Based Personal Authentication Using Deep Reinforcement Learning
S Baek, J Kim, H Yu, G Yang, I Sohn, Y Cho, C Park, “Intelligent Feature Selection for ECG-Based Personal Authentication Using Deep Reinforcement Learning”, MDPI Sensors, 2023, IF=3.847.
GAN-based patient information hiding for an ECG authentication system
Y Kang, G Yang, H Eom, S Han, S Baek, S Noh, Y Shin, C Park, “GAN-based patient information hiding for an ECG authentication system”, Biomedical Engineering Letters, 2023, 197-297, IF=3.92.
Classification using a Spiking Neural Network: A Review
Y Park, U Sunarya, G Yang, C Lee, J Baek, S Baek, C Park, “Classification using a Spiking Neural Network: A Review”, IEIE Transaction on Smart Processing & Computing, 2023, 64-71.
Efficiently Updating ECG-Based Biometric Authentication Based on Incremental Learning
J Kim, G Yang, J Kim, S Lee, KK Kim, C Park, “Efficiently Updating ECG-Based Biometric Authentication Based on Incremental Learning”, MDPI Sensors 2021, 21, 1568, IF=3.735.
Energy-Efficient PPG-Based Respiration Rate Estimation Using Spiking Neural Networks
Geunbo Yang, Yougshin Kang, Peter H. Charlton, Panayiotis A. Kyriacou, Ko Keun kim, Ling Li, Chelsoo Park, “Energy-Efficient PPG-Based Respiratory Rate Estimation Using Spiking Neural Networks”, MDPI Sensors 2024, 24(12), IF=3.4
Communications
Supervise-based Random Sampled Spike Encoding Algorithm for Image Classification in Deep Spiking Neural Networks
양근보, 강영신, 박철수, “Supervise-based Random Sampled Spike Encoding Algorithm for Image Classification in Deep Spiking Neural Networks”, 대한의용생체공학회 춘계학술대회, May, 2023, 244-245.
Implementation of spiking neural network Using dynamic learning of Inhibition neurons
양근보, 박철수, “Implementation of spiking neural network Using dynamic learning of Inhibition neurons”, 대한전자공학회 학술대회, June, 2022, 879-881.
ECG-Based Heart Rate Estimation Using SVR with Spiking Neural Network
이충섭, 양근보, 박철수, “ECG-Based Heart Rate Estimation Using SVR with Spiking Neural Network”, 대한전자공학회 학술대회, June, 2022, 852-855.
Patent
몽유병을 감지하는 엣지 디바이스
박철수, 양근보, 이충섭, 출원번호: 10-2022-0164099, 출원일자: 2022년 12월.
확률 모델에 기반한 손상된 시계열 생체 신호의 복원 방법
박철수, 이지운, 양근보, 출원번호: 10-2022-0189990, 출원일자: 2022.12
사용자 인증 장치 및 방법
박철수, 양근보, 김준모, 출원번호: 10-2019-0179392, 출원일자: 2019.12
Jiseok Yang
Jiseok Yang received his BS degree in Department of Industrial Information System Engineering from Jeonbuk University in Jeonju, South Korea and his MS degree in Computer Engineering from Kwangwoon University in seoul, South Korea. His research interests include machine learning, Deep learning, GNN, Datamining
Journal Article
Predicting Car Rental Prices: A Comparative Analysis of Machine Learning Models
Jiseok Yang, Jinseok Kim, Hanwoong Ryu, Jiwoon Lee, Cheolsoo Park, “Predicting Car Rental Prices: A Comparative Analysis of Machine Learning Models“, MDPI Electronics, June 2024
Design of Metaverse Rental Car Price Prediction Method Through Machine Learning Techniques
Jiseok Yang, Hanwoong Ryu, Jiwoon Lee, Jihong Lee, Cheolsoo Park, “Design of Metaverse Rental Car Price Prediction Method Through Machine Learning Techniques“, Journal of Broadcast Engineering, Jan 2024
Communications
Large Language Models의 제로샷 기법을 적용한 렌터카 차량 가격 예측
양지석, 양근보, 이정환, 박철수, “Large Language Models의 제로샷 기법을 적용한 렌터카 차량 가격 예측” 대한전자공학회 하계학술대회 June, 2024
Real-Time Anomaly Detection in Industrial Cyber-Physical Systems Using Deep Learning based Bidirectional GRU
D. Kwon, Y. Kang, and J. Yang and C. Park, “Real-time Anomaly Detection in Industrial Cyber-Physical Systems Using Deep Learning based Bidirectional GRU”, IEIE Artificial Intelligence and Signal Processing, Sep 2023, pp. 239-241
Metaverse: Research Based Prediction Model of the Car Price in view of the Machine-learning MethodmJiseok Yang, Jinseok Kim, Jiwoon Lee, Hanwoong Ryu, Seonghyeok Yeo, Panjung Kim, Yoonki Kim, Jiyeun Lim, Hyunjoon Yoon, Cheolsoo Park, “Metaverse: Research Based Prediction Model of the Car Price in the view of the Machine-learning Method”, IEEE International Conference on Metaverse Computing, Networking and Applications (IEEE MetaCom 2023), June 2023, Kyoto, Japan
Award
우수 학생 논문상
“Large Language Models의 제로샷 기법을 적용한 렌터카 차량 가격 예측”, 양지석, 양근보, 이정환, 박철수, 대한전자공학회 하계학술대회, June, 2024
Patent
LLM 기반 차량 추천 시스템
박철수, 양지석, 류한웅, 출원번호: 10-2023-0190509, 출원일자: 2023년 12월, 대한민국.