Adaptive Signal Conditioning and Calibration for Microelectromechanical System

A strong analogy exists between today's MEMS device and the first prototypes of the transistor. Research and development in semiconducto devices made the integration of millions of transistors into a single chip possible. It is anticipated that similar market forces will deman the integration of hundreds and later thousands of MEMS based sensors and actuators onto the same substrate in the next decade. For seamless integration of such devices either as plug and play components or as elements of standard cell libraries, several adaptive signal conditioning and self-calibration techniques are proposed and will be investigated during this project. The Phase I study will utilize an experimental setup composed of analog field programmable gate arrays, several discrete components, and several types of commercially available MEMS sensors, in addition to some experimental piezoelectric microphone elements. Our objective is to validate the techniques, architectures and circuits for neural and adaptive signal conditioning and self-calibration. MEMS and related systems represent a break-through development in sensor and actuator technology. Enabling technologies for higher levels of integration and hybrid devices will have a broad impact in th assembly of complete systems for high precisionwsmart sensing and processing applications.