Mingui Sun, PhD

  • Professor

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 460 publications.

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

Specialized Areas of Interest

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

Professional Organization Membership

American Institute for Medical and Biological Engineering
Institute of Electrical and Electronics Engineers

Education & Training

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

Research Activities

• A Leadless EEG Sensor

Non-Convulsive Seizures (NCS) and Non-Convulsive Status Epilepticus (NCSE) are critical neurophysiological conditions which do not have overt clinical signs. These conductions can be diagnosed only with EEG monitoring. Unfortunately, approximately 2% of the patients in the ICU undergo continuous EEG monitoring. Primary reasons for the underuse of this technology is due to the complexity in setting up EEG equipment in busy, human resource constrained ICU. Dr. Sun is developing a self-contained EEG sensor in the size of a U.S. quarter with no electrode leads. By simply pressing the EEG sensor against the unprepared scalp and twisting slightly, the device can grasp the skin firmly and start acquiring and transmitting EEG wirelessly to a bedside monitor, a smartphone, a tablet, or a Bluetooth enabled device within an ambulance. With these unique features, the aforementioned problem can be solved. 

• Losing Weight Electronically: An AI and Control Systems Approach 

There is a strong and urgent need to find solutions for prediabetes which has a profound impact on American health. Although there is no cure for diabetes, prediabetes is reversible by

  1. eating more healthfully,
  2. losing weight, and
  3. exercising more.

To help people make these lifestyle changes, the National Institutes of Health developed the Diabetes Prevention Program (DPP). Participants in the lifestyle change groups undergo intensive training to eat less fat and fewer calories and increase exercise. The lifestyle change program has successfully prevented or delayed type 2 diabetes. However, the vigorous diet control program and the substantial time commitments have caused high dropouts. Dr. Sun’s multidisciplinary research team is investigating an electronic approach to lose weight. Three technologies are utilized:

  1. wearable sensors and a stationary camera will acquire each participant’s diet and physical activity data passively and objectively,
  2. AI algorithms will process these data to assess energy intake and expenditure automatically, significantly reducing the current manual procedural burdens on participants, and
  3. a closed-loop feedback control system will regulate energy balance based on the information provided by the sensors and mathematical models.

All the electronically obtained information will be provided weekly to both the DPP coach and participants who work collaboratively to achieve a personalized weight loss goal. At the end of Dr. Sun’s technological developments, a pilot study will be conducted to evaluate the feasibility of the proposed weight control system involving research participants who are both prediabetic and overweight.