%0 PDF %T A Micromachined Torsional Electric Field Sensor %A Ligonde, Gardy. %D 2018-06-04T10:04:04.934-04:00 %8 2018-06-04 %R http://localhost/files/nz806b62h %X Abstract: Neuroimaging is a relatively new discipline within medicine and psychology that is used to study the nervous system and can also help diagnose anomalies in cognitive functions. Unfortunately, the most popular techniques available (i.e. magnetic resonance imaging) are expensive, time-consuming, and inaccessible to most. Furthermore, emerging markets in virtual reality and education are also interested in creating new applications that would primarily rely on brain sensing technology. This research project is part of an internally funded program at Draper that is seeking to develop a sensor that would measure electric fields that are emitted from the outermost layer of the brain (usually ~1mV/m around 10-12Hz). If successful, this method would be relatively cheaper than most commercial techniques with the added benefits of being mobile and providing real-time measurements. In this thesis, a system level model was developed for characterizing the behavior of the device due to an electric field input as well as vibrations. A numerical model is also added to complement the electrostatics to capture any flux diversion that may influence the field strength near the device during operation. The micromachining process as well as the assembly are described. Results show agreement with modeling parameters. First, the expected resonant frequencies of the mechanical modes of the device during each major of the fabrication process are well predicted. Second, the scale factor of the device increases linearly with the amount of voltage applied to the system, which agrees with the model. Results suggest that the sensor's Brownian resolution limit with a 900V bias at resonance (2.5 kHz) will be 2.5 V/m/√Hz, and at low frequencies (~ 10 Hz) will be 1.5 mV/m/√Hz. Due to room vibrations, which are not attenuated by the current single-point laser vibrometry measurement method used for experiments, this resolution limit has not yet been approached. However, if a more optimal measurement scheme were used, that could approach the Brownian limit, which has been done in other MEMS systems, this resolution limit may plausibly be achievable in the future. At resonance this resolution would be nearly three orders of magnitude better than required for brain sensing applications. At low frequencies, the Brownian limit is of the same order as the required resolution. This thesis not only demonstrates the ability of the sensor to measure electric fields, but also develops a model and offers insights on further modifications that can be made to improve sensor performance.; Thesis (M.S.)--Tufts University, 2018.; Submitted to the Dept. of Mechanical Engineering.; Advisor: Robert White.; Committee: James Bickford, and Jason Rife.; Keyword: Mechanical engineering. %[ 2022-10-12 %9 Text %~ Tufts Digital Library %W Institution