W. Hong Yeo, Ph.D. ME, Georgia Institute of Technology  

Committee Members:  

Frank Hammond, Ph.D.  

ME, Georgia Institute of Technology  

Minoru Shinohara, Ph.D.  

Biological Sciences, Georgia Institute of Technology  

Todd Sulchek, Ph.D.  

ME, Georgia Institute of Technology  

Audrey Duarte, Ph.D.  

Psychology, Georgia Institute of Technology 

Study of soft materials, flexible electronics, and machine learning for fully portable and wireless brain-machine interfaces 

Wireless, wearable electroencephalograms and dry non-invasive electrodes can be utilized to allow recording of brain activity on a mobile subject to allow for unrestricted movement. Additionally, multilayer microfabricated flexible circuits, combined with a soft materials platform, provide imperceptible wearable electronics for wireless, portable, long-term recording of brain signals. This proposal focuses on sharing the study outcomes in soft materials, flexible electronics, and machine learning for universal brain-machine interfaces that could offer remedies in communication and movement for these individuals. Integration of materials, mechanics, circuit, and electrode design results in an optimized brain-machine interface allowing for rehabilitation and overall improved quality of life.