The goal of this research is to develop an automatic machine to apply an array of electrodes to the human scalp to record electroencephalograms (EEGs). The EEG is widely utilized method to evaluate neurological function. Recent advances in computer and information systems have greatly enhanced high resolution EEG technology which permits recording, transmitting, storing, and analyzing hundreds of channels of data from densely located electrodes to map the functional activity of the brain. However, the procedures for affixing EEG electrodes on the human scalp have experienced little improvement. The required tedious and primitive manual operations have been a well known problem in the EEG community This problem is severely limiting the wide acceptance of the high-resolution EEG technology in clinical applications.
We aim to solve this problem by designing new types of electrodes and developing an automatic system to affix electrodes to the scalp. In our Phase I STTR we have constructed several key mechanical and electronic components, and demonstrated the feasibility of our approach. We propose to continue this innovation in Phase II R&D. Our primary objectives are to construct a complete prototype system and to evaluate its performance.

Proposed Commercial Applications

The high costs of labor and slow turn-over of equipment due to EEG electrode manipulation are immense in the operation of clinical and research EEG laboratories. Therefore, the low-cost automatic EEG electrode placement system is expected to be well received by the EEG community. as a highly marketable commercial product.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Small Business Technology Transfer (STTR) Grants - Phase II (R42)
Project #
2R42NS036888-02
Application #
6022022
Study Section
Special Emphasis Panel (ZRG1-IFCN-7 (02))
Program Officer
Heetderks, William J
Project Start
1997-09-16
Project End
2001-08-31
Budget Start
1999-09-15
Budget End
2000-08-31
Support Year
2
Fiscal Year
1999
Total Cost
Indirect Cost
Name
Computational Diagnostics, Inc.
Department
Type
DUNS #
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Sun, Mingui; Jia, Wenyan; Liang, Wei et al. (2012) A low-impedance, skin-grabbing, and gel-free EEG electrode. Conf Proc IEEE Eng Med Biol Soc 2012:1992-5