Date of Award
Master of Science in Electrical Engineering (MSEE)
Electrical, Computer, and Biomedical Engineering
Frederick J. Vetter
There are many new developments in technology in the last decades. Even though the world is moving towards more autonomy, the human in the loop control of technology is still crucial. To improve efficiency and advance the technology further, there are new ways of human to machine interfaces (HMI) being developed: for example, eye control, voice control, brain control interface (BCI), gesture control, etc. All of these new paradigms of control face some common issues such as adoption, learning curve, and reliability. The goal for this project is to demonstrate a new state machine approach for gesture classification and demonstrate a use case for gesture classification.
Cipoletta, David O., "STATE MACHINE APPROACH FOR GESTURE CLASSIFICATION" (2019). Open Access Master's Theses. Paper 1741.
Available for download on Monday, December 13, 2021