Browsing by Author "Love, Andrew R."

Now showing 1 - 2 of 2
  • Thumbnail Image
    Automatically Locating Sensor Position on an E-textile Garment Via Pattern Recognition
    Love, Andrew R. (Virginia Tech, 2009-09-30)
    Electronic textiles are a sound platform for wearable computing. Many applications have been devised that use sensors placed on these textiles for fields such as medical monitoring and military use or for display purposes. Most of these applications require that the sensors have known locations for accurate results. Activity recognition is one application that is highly dependent on knowledge of the sensor position. Therefore, this thesis presents the design and implementation of a method whereby the location of the sensors on the electronic textile garments can be automatically identified when the user is performing an appropriate activity. The software design incorporates principle component analysis using singular value decomposition to identify the location of the sensors. This thesis presents a method to overcome the problem of bilateral symmetry through sensor connector design and sensor orientation detection. The scalability of the solution is maintained through the use of culling techniques. This thesis presents a flexible solution that allows for the fine-tuning of the accuracy of the results versus the number of valid queries, depending on the constraints of the application. The resulting algorithm is successfully tested on both motion capture and sensor data from an electronic textile garment.
  • Thumbnail Image
    A Modular Flow for Rapid FPGA Design Implementation
    Love, Andrew R. (Virginia Tech, 2015-03-10)
    This dissertation proposes an alternative FPGA design compilation flow to reduce the back-end time required to implement an FPGA design to below the level at which the user's attention is lost. To do so, this flow focuses on enforcing modular design for both productivity and code reuse, while minimizing reliance on standard tools. This can be achieved by using a library of precompiled modules and associated meta-data to enable bitstream-level assembly of desired designs. In so doing, assembly would occur in a fraction of the time of traditional back-end tools. Modules could be bound, placed, and routed using custom bitstream assembly with the primary objective of rapid compilation while preserving performance. This turbo flow (TFlow) aims to enable software-like turn-around time for faster prototyping by leveraging precompiled components. As a result, large device compilations would be assembled in seconds, within the deadline imposed by the human attention span.