Calibration Decision System of MEMS Gyroscope for Bio-Inertial Application

This Ph.D. dissertation presents a development of calibration methods of microelectromechanical (MEMS) gyroscopes for a vestibular prosthesis. The vestibular prosthesis senses head orientation and provides electrical stimulation to the ampullary nerves. The prosthesis utilizes a micro sensing element, which is susceptible to environmental changes resulting in drift. Consequently, encoding the input rotation to stimulate pulses using a MEMS sensing architecture would mislead the nervous system and inadvertently cause additional damage to other sensing organs. Not mitigating the issues of short-term and long-term drift would take away all benefits of the prosthesis. The focus of this dissertation is toward algorithm design and hardware development for the identification of sources of errors in bias and scale-factor of a MEMS gyroscope and to introduce sensor calibration methods for providing accurate electrical stimulation. A Silicon micromachined Quad Mass Gyroscope (QMG) was used, as a test structure device, and was utilized to identify sensor-level calibration algorithms needed for the prosthesis. For this realization, a standalone electronics platform for MEMS gyroscope characterization was designed and developed to identify the needed control algorithms to satisfy the required bandwidth and linearity of the prosthesis. As a calibration technique for the prosthesis system, a flexible solution platform for integration and data processing from multiple foot-mounted inertial sensors was designed and developed for the purpose of providing an aiding solution to calibrate the prosthesis sensitivity and drift. The developed calibration methods demonstrated the potential to identify sources of errors and compensate for the drift, a functionality that would not be possible by simply utilizing off-the-shelf MEMS gyroscopes for the vestibular prosthesis