Publications

2019

저지연 WSN을 위한 중앙집중형 멀티채널 스케줄링 알고리즘

이상수, 박철수, 손일수, “저지연 WSN을 위한 중앙집중형 멀티채널 스케줄링 알고리즘”, KICS, Vol 44, Nov 2019, KCI

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”, IEEE, Early access, Jan 2020, SCI

Optimal Feature Search for Vigilance Estimation Using Deep Reinforcement Learning

Woojoon Seok, Minsoo Yeo, Jiwoo You, Heejun Lee, Taeheum Cho, Bosun Hwang, Cheolsoo Park, “Optimal Feature Search for Vigilance Estimation Using Deep Reinforcement Learning”, MDPI, Vol 9, Jan 2020, SCI

Deep-ACTINet: End-to-End Deep Learning Architecture for Automatic Sleep-Wake Detection Using Wrist Actigraphy

Taeheum Cho, Unang Sunarya, Minsoo Yeo, Bosun Hwang, Yong Seo Koo, Cheolsoo Park, “Deep-ACTINet: End-to-End Deep Learning Architecture for Automatic Sleep-Wake Detection Using Wrist Actigraphy”, MDPI electronics, Vol 8, 1461, Dec 2019, SCI

Multivariate Time–Frequency Analysis of Electrohysterogram for Classifcation of Term and Preterm Labor

Jiwoo You · Youngjoo Kim· Woojoon Seok · Seungmin Lee· Donggyu Sim· Kwang Suk Park · Cheolsoo Park, “Multivariate Time–Frequency Analysis of Electrohysterogram for Classifcation of Term and Preterm Labor,” Journal of Electrical Engineering & Technology, vol. 14, no. 2, pp 897-916, March 2019, SCIE

2017~2018

Multimodal Drowsiness Detection Methods using Machine Learning Algorithms

Youngchul Kim, Minsoo Yeo, Illsoo Sohn, Cheolsoo Park, “Multimodal Drowsiness Detection Methods using Machine Learning Algorithms”, IEIE Transactions on Smart Processing and Computing, vol 7, no 5, pp361, October 30 2018

Machine learning in biomedical engineering

Park Cheolsoo; Took Clive Cheong, Seong Joon-Kyung, “Machine learning in biomedical engineering”, Biomedical Engineering Letters, Vol 8, No 1, pp 1-3, February 2018

Automatic Malware Detection with Machine Learning Algorithms in a Smart Office Environment

Minsoo Yeo, Ilsub Bang, Donghyun Kim, Abbas Ahmad, Hamza Baqa, Jaeseung Song, and Cheolsoo Park, “Automatic Malware Detection with Machine Learning Algorithms in a Smart Office Environment”, IEIE Transactions on Smart Processing and Computing, Vol.7 No.4 pp.313 August, 2018

Recognition of Human Motion with Deep Reinforcement Learning

W. Seok, C. Park, “Recognition of Human Motion with Deep Reinforcement Learning”, IEIE Transactions on Smart Processing and Computing, vol. 7, no. 3, June 2018

Flexible and Printed PPG Sensors for Estimation of Drowsiness

G. -S. Ryu, J. You, V. Lostianovskii, E. -B. Lee, Y. Kim, C. Park*, and Y. -Y. Noh* (*co-corresponding authors), “Flexible and Printed PPG Sensors for Estimation of Drowsiness”, IEEE Transactions on Electron Devices, vol. 65, no. 7, pp 2997-3004, July 2018 (SCIE, IF =2.62)

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, pp367-389, Dec 2017

Correlation Assisted Strong Uncorrelating Transform Complex Common Spatial Patterns for Spatially Distant Channel Data

Y Kim, J You, H Lee, S Lee, C Park, “Correlation Assisted Strong Uncorrelating Transform Complex Common Spatial Patterns for Spatially Distant Channel Data”, Computational Intelligence and Neuroscience, Vol 2018, Article ID 4281230, pp 9, April 2018 (SCIE, IF=1.649)

Deep ECGNet: An optimal deep learning framework for monitoring mental stress using ultra short-term ECG signals

B Hwang, J You, T Vaessen, M Germeys, C Park, B Zhang, “Deep ECGNet: An optimal deep learning framework for monitoring mental stress using ultra short-term ECG signals”, Telemedicine Journal and e-Health, Vol 24, No 10, Oct 2018

Flexible and implantable capacitive microelectrode for bio-potential acquisition

S Lee, H Byeon, B Kim, J Lee, J Jeong, J Lee, J Moon, C Park, H Choi, S Lee, “Flexible and implantable capacitive microelectrode for bio-potential acquisition”, BioChip Journal, Vol.11, pp.153-163, June 2017 (SCIE, IF=1.4)

Automatic Detection of Sleep Stages based on Accelerometer Signals from a Wristband

M. Yeo, Y. Koo and C. Park, “Automatic Detection of Sleep Stages based on Accelerometer Signals from a Wristband,” IEIE Transactions on Smart Processing and Computing, Vol 6, No 1, pp 21-26, Feb 2017

2015~2016

Quaternion Common Spatial Patterns

S. Enshaeifar, C. C. Took, C. Park, D. P. Mandic, “Quaternion Common Spatial Patterns” IEEE Transactions on Neural Systems and Rehabilitation Engineering, Nov. 2016 (SCIE, IF=3.972)

Motor Imagery Classification Using Mu and Beta Rhythms of EEG with Strong Uncorrelating Transform Based Complex Common Spatial Patterns

Y. Kim, J. Ryu, 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, vol. 2016, Sep (SCIE, IF=1.649)

Estimation of Brain Connectivity during Motor Imagery Tasks using Noise-Assisted Multivariate Empirical Mode Decomposition

K. Lee, 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” Journal of Electrical Engineering and Technology, vol. 11, no. 6, pp 1812-1824, Nov. 2016 (SCIE, IF=0.597)

Strong Uncorrelated Transform Applied to Spatially Distant Channel EEG Data(2015)

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

Time-Frequency Analysis of Electrohysterogram for Classification of Term and Preterm Birth(2015)

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

Review of Data-Driven Multivariate and Multiscale Methods(2015)

C. Park, “Review of Data-Driven Multivariate and Multiscale Methods” IEIE Transactions on Smart Processing and Computing, vol. 4, pp 89-96, Apr. 2015

Self-adhesive and Capacitive Carbon Nanotube-based Electrode to Record Electroencephalograph Signals from the Hairy Scalp(2015)

S. Lee, J. Kim, C. Park, J. Hwang, J. Hong, K. Lee, S. Lee, “Self-adhesive and Capacitive Carbon Nanotube-based Electrode to Record Electroencephalograph Signals from the Hairy Scalp” IEEE Transactions on Biomedical Engineering, vol 63, no 1, pp 138-147, Dec. 2015 (SCI, IF=4.288)

2013~2014

Adaptive Multiscale Time-Frequency Analysis

Naveed ur Rehman, David Looney, Cheolsoo Park, Danilo P. Mandic, “Adaptive Multiscale Time-Frequency Analysis”, Springer Handbook of Bio-/Neuroinformatics, Berlin, 2014

MULTIVARIATE EXTENSIONS OF EMPIRICAL MODE DECOMPOSITION

Naveed ur Rehman, David Looney, Alireza Ahrabian, Cheolsoo Park, Danilo P. Mandic, “MULTIVARIATE EXTENSIONS OF EMPIRICAL MODE DECOMPOSITION”, Hilbert-Huang Transform and Its Applications, 47-67, 2014

EEG gamma band oscillations differentiate the planning of spatially directed movements of the arm versus eye: multivariate empirical mode decomposition analysis(2014)

C. Park, M. Plank, J. Snider, S. Kim, H. Huang, S. Gepshtein, T. Coleman and H. Poizner, “EEG gamma band oscillations differentiate the planning of spatially directed movements of the arm versus eye: multivariate empirical mode decomposition analysis” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol 22, no 5, pp 1083-1096, June 2014

Augmented Complex Common Spatial Patterns for Classification of Noncircular EEG from Motor Imagery Tasks(2014)

C. Park, C. C. Took, and D. P. Mandic, “Augmented Complex Common Spatial Patterns for Classification of Noncircular EEG from Motor Imagery Tasks” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol 22, no. 1, pp. 1-10, Jan. 2014

EMD via MEMD: Multivariate noise-aided computation of standard EMD(2013)

N. U. Rehman, C. Park, N. E. Huang and D. P. Mandic, “EMD via MEMD: Multivariate noise-aided computation of standard EMD” Advances in Adaptive Data Analysis, vol. 5, no. 2, pp. 1-25, Apr. 2013

Classification of motor imagery BCI using multivariate empirical mode decomposition(2013)

C. Park, D. Looney, N. U. Rehman, A. Ahrabian, and D. P. Mandic, “Classification of motor imagery BCI using multivariate empirical mode decomposition” IEEE Transactions on Neural Systems and Rehabilitation Engineering vol. 21, no. 1, pp. 10-22, 2013

2007~2012

The In-the-Ear Recording Concept: User Centered and Wearable Brain monitoring(2012)

D. Looney, P. Kidmose, C. Park, M. Ungstrup, M. L. Rank, K. Rosenkranz, D. P. Mandic, “The In-the-Ear Recording Concept: User Centered and Wearable Brain monitoring” Pulse, IEEE, vol. 3, no. 6, pp. 32-42, Nov. 2012

Real-time electrical measurement of L929 cellular spontaneous and synchronous oscillation(2012)

M. Marimuthu, C. Park, S. Kim and C. Choi “Real-time electrical measurement of L929 cellular spontaneous and synchronous oscillation” International Journal of Nanomedicine vol. 7, pp 83-92, 2012

The Complex Local Mean Decomposition(2011)

C. Park, D. Looney, M. V. Hulle, D. P. Mandic “The Complex Local Mean Decomposition” Neurocomputing vol. 27, no. 6, pp. 867-875, 2011

Time-Frequency Analysis of EEG Asymmetry using Bivariate Empirical Mode Decomposition(2011)

C. Park, D. Looney, P. Kidmose, M.Ungstrup and D.P. Mandic “Time-Frequency Analysis of EEG Asymmetry using Bivariate Empirical Mode Decomposition” IEEE Transactions on Neural Systems and Rehabilitation Engineering vol. 19, no. 4, pp. 366-373, 2011

Classification of Glucose Concentration in Diluted Urine using the Low-Resolution Raman Spectroscopy and Kernel Optimization Method(2007)

C. Park, K. Kim, J. Choi, K. Park “Classification of Glucose Concentration in Diluted Urine using the Low-Resolution Raman Spectroscopy and Kernel Optimization Method” Physiological Measurement vol. 28, pp. 583-593, 2007

PC-Based Tele-Audiometry(2007)

J. Choi, H.Lee, C. Park, S. Oh, K. Park “PC-Based Tele-Audiometry” Telemedicine and E-Healthvol. 13, pp. 501-508, 2007