Smart BioMedical Lab

Welcome to SmartBioMed Lab (Dr. Jo Woon Chong)

SmartBioMed Lab explores the fundamental science of physiology and biomedical engineering to discover new knowledge and apply it to future biomedical technologies. SmartBioMed Lab has long-term expertise in

 
1) Artificial Intelligence for Smart Health Monitoring, which are all based on physiology, signal processing, image processing, and machine learning algorithms
2) Physiology-Based Medical Instrumentation
3) Smartphone- or Smartwatch-Based Mobile Health Monitoring
4) Biomedical Signal Processing
5) Advanced Heavy-Ion Radiotherapy for Cancer Treatment
6) Identification and Modeling of Physiological Systems
7) On-Device AI
8) From Fashion to Function

Click here to check the publication of Jo Woon Chong

News (Oct 2025 - Jan 2026)

[2025. 12. 23] Award! The Fitology Team, supervised by Professor Jo Woon Chong, consists of Seungmin Lee, Junjae Park, and Nahyun Lee, with support from Myungjun Kim received the President’s Award at the 2025 Fall SKKU Interdisciplinary Research Credit Program. Please see the details here (https://eee.skku.edu/eee/news.do?mode=view&articleNo=211355&article.offset=0&articleLimit=10). 

[2025. 12. 2] Top 1.7% Journal! "The role of scent congruence with luxury brand image in consumers’ emotions, memory, and brand resonance: A mixed-methods approach using EEG and quantitative analyses" by S. Kim*, H. J. Chang, B. L. Ortiz, and J. W. Chong* has been accepted in the Journal of Retailing and Consumer Services (*: corresponding authors).

[2025. 10. 16] Top 2.5% Journal! "Smart home healthcare using artificial intelligence of things: Emergency prediction and prevention for cerebrovascular disease patients" by J. Baek, J. W. Chong*, K. Cho*, and L. Lim*, has been published in the Engineering Application of Artificial Intelligence (*: corresponding authors).

[2025. 10. 15] Grant Proposal! Our project, “Regulating sensory stimuli in spatial environments: Enhancing cognition and memory while reducing stress in individuals with Alzheimer’s,” has been selected to receive the CHHS Alzheimer’s Seed Grant (United States), in collaboration with Sungkyunkwan University, KAIST and Texas Tech University.

[2025. 10. 1] Alumni News! Dr. Bengie L. Ortiz (PhD Alumni) is now Postdoctoral Associate at Rutgers University.

News (May-Sep 2025)

[2025. 9. 25] "Impact of Fundus Image Quality on Deep Learning-Based Glaucoma Detection" Heejae Kim, Myeongjun Kim, Soo Min Oh, Jo Woon Chong, is accepted to International Conference On Consumer Electronics (ICCE) Asia 2025, South Korea. 

[2025. 9. 25] "Efficient Vectorization of Binary Sketches for Consumer Product Customization Using Image Processing" Yanjing Jin, Hee Jo, M. Kim, H. Baek, H. J. Chang, Jo Woon Chong, is accepted to International Conference On Consumer Electronics (ICCE) Asia 2025, South Korea. 

[2025. 9. 25] "Proposal of a Quantitative Performance Evaluation Methodology for IMU Sensor Modules Using a Low-Cost Testbed Based on Smartphone IMU" Myeongjun Kim, Seungmin Lee, Junjae Park, Nahyun Lee, Jo Woon Chong, is accepted to International Conference On Consumer Electronics (ICCE) Asia 2025, South Korea. 

[2025. 9. 23] "Automated Glaucoma Classification in Fundus Images Using Multi-Backbone Feature Fusion" Juhee Han, Soo Min Oh, Hee Jo, L. Bengie Ortiz, Yifan Li, and J. W. Chong" is accepted to IEEE BIBE 2025, Greece. 

[2025. 9. 2] "Towards Proactive Home Healthcare: Leveraging In-home Contactless Sensors and Multimodal Deep Learning for Emergency Prediction in Older Patients with Neurological Disorders" J. Baek, K. Cho, J.W. Chong, L. Lim*, is accepted to World Congress on Design and Health, 2025, Singapore.

[2025. 9. 1] Alumni News! Jaewon Seong (MS Alumni) is now PhD Student at University of Wisconsin-Milwakeee

[2025. 7. 31] "Real-Time Passenger Movement Estimation for Subway Door Safety Using Deep Learning" Hee Jo, L. Lim*, J.W. Chong*, is accepted to IEEE ITEC-AP Conference, 2025, Singapore.

[2025. 5. 15] Top 3.7% Journal! "An Interpretable AI for Smart Homes: Identifying Fall Prevention Strategies for Older Adults Using Multimodal Deep Learning" by J. Baek⁺, Yifan Li⁺, L. Lim*, and J. W. Chong*, has been published in the IEEE Journal of Biomedical and Health Informatics (⁺: first authors, *: corresponding authors)