Mingui Sun, PhD

Professor


Mingui Sun

Contact

412-648-9234

Biography

Mingui Sun, PhD, received a BS degree in instrumental and industrial automation in 1982 from the Shenyang Chemical Engineering Institute in Shenyang, China, and an MS degree in electrical engineering in 1986 from the University of Pittsburgh, where he also earned a PhD degree in electrical engineering in 1989. He was later appointed to the faculty in the Department of Neurological Surgery.

Dr. Sun’s research interests include neurophysiological signals and systems, biosensor designs, brain-computer interface, bioelectronics and bioinformatics. He has more than 400 publications.

Specialized Areas of Interest

Biomedical engineering; biomedical instrumentation; biomedical signal processing, computational neurophysiology, image and video processing; computer-assisted neuro-surgery and diagnosis.

Professional Organization Membership

American Institute for Medical and Biological Engineering
Institute of Electrical and Electronics Engineers
IEEE Engineering in Medicine and Biology Society
IEEE Circuit and Systems Society

Education & Training

BS, Instrumentation/Industrial Automation, Shenyang Chemical Institute, 1982
MS, Electrical Engineering, University of Pittsburgh, 1986
PhD, Electrical Engineering, University of Pittsburgh, 1989

Honors & Awards

Outstanding Research Poster Award, Tech Summit: Innovative Tools for Assessing Diet & Physical Activity for Health Promotion, 2016.

Selected Publications

Li Z, Jia W, Chen H-C, Wang K, Zuo W, Meng D, Sun M. Multiview Stereo and Silhouette Fusion via Minimizing Generalized Reprojection Error. Image and Vision Computing 33:1-14, 2015.

Chen H-C, Jia W, Sun X, Li Z, Li Y, Fernstrom JD, Burke LE, Baranowski T, Sun M. Saliency-aware food image segmentation for personal dietary assessment using a wearable computer. Measurement Science and Technology 26(2), 2015.

Li Z, Wei Z, Yue Y, Wang H, Jia W, Sun M. An adaptive hidden Markov model for activity recognition using a wearable multi-sensor device. Journal of Medical Systems 39:57, 2015.

Cheng F, Zhang H, Sun M, Yuan D. Cross-trees, Edge and Superpixel Priors-based Cost aggregation for Stereo matching. Pattern Recognition, 48(7):2269-2278, 2015.

Sun W, Wang H, Sun C, Guo B, Jia W, Sun M. Fast single image haze removal via local atmospheric light veil estimation. Computers & Electrical Engineering, online Jounal, March 2015.

Liao X, Yuan Z, Fai Q, Quo J, Zhen Q, Yu S, Tong Q, Si W, Sun M. Modeling and Predicting Tissue Movement and Deformation for High Intensity Focused Ultrasound Therapy,” PLoS One 10:e0127873, 2015.

Chyu MC, Austin T, Calisir F, Chanjaplammootil S, Davis MJ, Favela J, Gan H, Gefen A, Haddas R, Shen CL, Shieh JS, Su CT, Sun L, Sun M, Tewolde SN, Williams EA, Yan C, Zhang J, Zhang YT. Healthcare Engineering Defined: a White Paper. Journal of Healthcare Engineering 6(41):635-648, 2015.

Dudik JM, Coyle JL, El-Jaroudi A, Sun M, Sejdic E. A matched dual-tree wavelet denoising for tri-axial swallowing vibrations. Biomedical Signal Processing and Control 27:112-121, 2016.

A complete list of Dr. Sun's publications can be reviewed through the National Library of Medicine's publication database.

Research Activities

In the past year, Dr. Sun’s laboratory studied the following medical and health related devices and systems: 

eButton: A body-worn, cookie-sized electronic device for a variety of real-world applications, including human dietary evaluation, behavioral assessment, lifestyle monitoring, navigation for the blind, military training, and behavioral telemedicine.

eHat: A hat-like device with a looking-down camera for training and learning, such as infant care training, medical procedure training, and general training of sophisticated skills involving hand manipulation.

eBelt: An electronic waist belt embed with sensors for monitoring the quality of life and safety of the elderly and people with mental disorders. The device is entirely passive requiring no human maintenance. It is powered by an energy harvester based on the repetitive motion of respiration.

DreamNest: A wearable device for home-based remote clinical evaluation of sleep. It has essential functions of the current polysomnography (PSG), but adopts a completely different design using a new type of electroencephalographic (EEG) electrode. The device is wireless and leadless.

Magic Socks: A pair of textile wearable devices that provide both massage and electric simulation functions. It is used as a therapeutic device for treatment of the restless leg syndrome, a neurological sensory motor disorder.

Linus: A hat-like textile wearable device that delivers controlled therapeutic lights to the eyes to adjust circadian rhythm related sleep disorders.

Cough Monitor: A wearable device that monitors coughing. It is used as a clinical tool for pulmonary physicians to evaluate patients with lung diseases.

Single-Unit Wireless EEG Sensor: A coin sized device that can be applied to the scalp quickly for the measurement of brain waves (EEG). It is used for evaluation of neurological functions at the point of case, sports field, battlefield, and patient transportation vehicles.

CadioShirt: A comfortable shirt embedded with electronic sensors and textile electrodes for the monitoring of vital signs.

Magnetic Hand Tracker: This unobtrusive wearable system includes a set of adhesive magnetic fingernails and a wristband. Hand motion and gesture are computationally tracked based on the acquired variation of magnetic fields by an array of magnetometers.

PUMP: Pressure Ulcer Monitoring Platform (PUMP) is a maintenance-free electronic sensor system placed under the legs of a hospital bed which automatically monitors human-performed body rotations for ulcer prevention.