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Jungyoon Kim
Jungyoon Kim
Adresse e-mail validée de kent.edu
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ISSAQ: An Integrated Sensing Systems for Real-Time Indoor Air Quality Monitoring
J Kim, C Chu, S Shin
IEEE Sensors Journal 14 (12), 4230 - 4244, 2014
2302014
The Use of Deep Learning to Predict Stroke Patient Mortality
J Cheon, S., Kim, J., & Lim
International Journal of Environmental Research and Public Health 16 (11), 1876, 2019
1242019
Unobtrusive Monitoring to Detect Depression for Elderly with Chronic Illnesses
JY Kim, N Liu, HX Tan, CH Chu
IEEE Sensors Journal, 2017
882017
A Deep Neural Network-Based Method for Early Detection of Osteoarthritis Using Statistical Data
S Lim, J., Kim, J., & Cheon
International journal of environmental research and public health 16 (7), 1281, 2019
752019
Identifying Traffic Context Using Driving Stress: A Longitudinal Preliminary Case Study
HKK OV Bitkina, J Kim, J Park, J Park
Sensors 19 (9), 2152, 2019
712019
A context-aware reminder system for elders based on fuzzy linguistic approach
S Zhou, CH Chu, Z Yu, J Kim
Expert Systems with Applications 39 (10), 9411-9419, 2012
332012
Applying deep learning technology for automatic fall detection using mobile sensors
X Wu, Y Zheng, CH Chu, L Cheng, J Kim
Biomedical Signal Processing and Control 72, 103355, 2022
322022
IoT-Based Unobtrusive Sensing for Sleep Quality Monitoring and Assessment
JY Kim, CH Chu, MS Kang
IEEE Sensors journal 21 (3), 3799 - 3809, 2021
322021
Gaussian mixture models for detecting sleep apnea events using single oronasal airflow record
H ElMoaqet, J Kim, D Tilbury, SK Ramachandran, M Ryalat, CH Chu
Applied Sciences 10 (21), 7889, 2020
252020
Design of a smart gas sensor system for room air-cleaner of automobile-thick-film metal oxide semiconductor gas sensor
JY Kim, SW Kang, TZ Shin, MK Yang, KS Lee
2006 International Forum on Strategic Technology, 72-75, 2006
232006
Development of a statistical model to classify driving stress levels using galvanic skin responses
J Kim, J Park, J Park
Human Factors and Ergonomics in Manufacturing & Service Industries 30 (5 …, 2020
192020
IoT-Based Unobtrusive Physical Activity Monitoring System for Predicting Dementia
J Kim, S Cheon, J Lim
IEEE ACCESS 10, 26078 - 26089, 2022
172022
Time domain characterization for sleep apnea in oronasal airflow signal: A dynamic threshold classification approach
J Kim, H ElMoaqet, DM Tilbury, SK Ramachandran, T Penzel
Physiological Measurement 40 (5), 054007, 2019
172019
SHINESeniors: Personalized services for active ageing-in-place
EY Liming, B., Gavino, A. I., Lee, P., Jungyoon, K., Na, L., Pi, T. H. P ...
In Smart Cities Conference (ISC2), 2015 IEEE First International, (pp. 1-2), 2015
17*2015
Analysis of Energy Consumption for Wearable ECG Devices
JY Kim, CH Chu
SENSORS, 2014 IEEE, 962 - 965, 2014
172014
A Deep Neural Network-Based Method for Prediction of Dementia Using Big Data
J Kim, J Lim
International Journal of Environmental Research and Public Health 18 (10), 5386, 2021
112021
Real-Time Ventricular Fibrillation Detection Using an Embedded Microcontroller in a Pervasive Environment
S Kwon, J Kim, CH Chu
Electronics 2018 7 (6), 88, 2018
112018
Designing integrated sensing systems for real-time air quality monitoring
JY Kim, CH Chu, SM Shin
2014 International Conference on Information Science & Applications (ICISA), 1-6, 2014
102014
Modeling Sleep Quality Depending on Objective Actigraphic Indicators Based on Machine Learning Methods
OV Bitkina, J Park, J Kim
International Journal of Environmental Research and Public Health 19 (16), 9890, 2022
82022
Using deep learning and smartphone for automatic detection of fall and daily activities
X Wu, L Cheng, CH Chu, J Kim
International Conference on Smart Health, 61-74, 2019
82019
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