Chon, Ki

Ki Chon, Ph.D.
Krenicki Professor of Biomedical Engineering
Research Interests:  
Medical instrumentation, biomedical signal processing, and identification and modeling of physiological systems.
Bronwell 209, 260 Glenbrook Road, Unit 3247 
University of Connecticut
Storrs, CT 06269-3247
Office Phone: (860) 486-4767
Office Fax: (860) 486-4767
BS University of Connecticut
MS University of Iowa
MS University of Southern California
PhD University of Southern California
Postdoc MIT  

Research Summary:

Research in my laboratory involves medical instrumentation, biosignal processing, modeling, simulation and development of novel algorithms to understand dynamic processes and extract distinct features of physiological systems.  Currently, there are six research projects ongoing in my laboratory:

  • Evaluation of the effects of oxygen toxicity and hyperbaric environments on the autonomic nervous system:  The goal is to develop noninvasive approaches for early detection of and differentiation between fatal and non-fatal decompression sickness (DCS).  Both swine and human experiments are being conducted to test the robustness of our algorithm for early detection and prediction of DCS.
  • Real-time detection of atrial fibrillation, atrial flutter and atrial tachycardia from surface ECG:  The goal is to develop real-time algorithms for accurate detection of atrial fibrillation, flutter and tachycardia that are especially applicable for Holter monitoring devices.
  • Spatio-temporal analysis of renal autoregulation:  The goal is to understand how nephrons synchronize to autoregulate renal blood flow using laser speckle imaging techniques.  
  • Noninvasive assessment of diabetic cardiovascular autonomic neuropathy (DCAN) from surface ECG or pulse oximeter:  The goal is to develop noninvasive approaches for early detection of DCAN. Diabetic and control mice are used to collect ECG data and validation of computational data analysis results is measured against Western blot and immunohistochemistry.
  • Vital sign monitoring from optical recordings with a mobile phone: The goal is to utilize a mobile phone video camera to extract vital sign and physiological parameters, which may include heart rate, oxygen saturation, respiratory rate, atrial fibrillation detection, blood loss detection, and the dynamics of the autonomic nervous system.
  • Wearable devices for vital sign monitoring: The goal is to develop wearable devices (e.g., chest strap, wearable shirt and watches) and new sensors (e.g., dry ECG, skin conductance and EMG electrodes) to measure vital sign and physiological parameters for both dry and water immersion conditions.

Honors and Awards:

  • Fellow, IEEE
  • Fellow, National Academy of Inventors
  • Fellow, International Academy of Medical and Biological Engineering (IAMBE)
  • Fellow, American Institute for Medical and Biological Engineering (AIMBE)
  • Fellow, Asia-Pacific Artificial Intelligence Association
  • Program Co-Chair, 28th International Conference of the IEEE EMBS, 2006, NYC.
  • Krenicki Endowed Chair Professor at UConn
Selected Publications:

Google Scholar Citations Link

PubMed Citations Link

  1. Moon, J., H.F. Posada-Quintero, and K.H. Chon, Risk Factor, symptom, and mechanism identification for cardiovascular disease using literature embedding model with genotype and phenotype information, Expert Systems with Applications, In Press

  2. Hossain, M.B., H.F. Posada-Quintero, and K.H. Chon, A deep convolutional autoencoder for automatic motion artifact removal in electrodermal activity, IEEE Trans BME, In Press.

  3. Mohagheghian, F. D. Han, A. Peitzsch, N. Nishita, E. Ding, E. L. Dickson, D. DiMezza, E. M. Otabil, K Noorishirazi, J. Scott, D. Lessard, Z. Wang, C. Whitcomb, K.-V. Tran, T.P. Fitzgibbons, D.D. McManus and K.H. Chon,  Optimized Signal Quality Assessment for Photoplethysmogram Signals using Feature Selection, IEEE Trans BME, In Press.

  4. Han, D., S.K. Bashar, J. Lazaro, F. Mohagheghian, A. Peitzsch, N. Nishita, E. Ding, E. Dickinson, D. DiMezza, J. Scott, C. Whitcomb, T.P. Fitzgibbons, D.D. McManus, and K.H. Chon, A real-time PPG peak detection method for accurate determination of heart rate during sinus rhythm and cardiac arrhythmia, Biosensors, 12 (2), 82, 2022.

  5. Hajeb, S., A. Casella, M. Valentine, and K.H. Chon, Enhancing the Accuracy of Shock Advisory Algorithm in Automated External Defibrillators during Ongoing Cardiopulmonary Resuscitation using a Deep Convolutional Encoder-Decoder filtering Model, Expert Systems with Applications, 203:117499, 2022.