An intelligent instrumentation and a Kalman filter based dynamic model has been developed to find the position of ultrasonic transmitters in an inertial frame of reference. The position estimation method collects Actual Time of Flights (ATOF) and Difference in Time of Arrival (DTOA) data from the transducers. To show proof of concept in 1D, two ultrasonic receivers are used to provide position estimations of two transmitters in 1D using ATOF and DTOA approaches. A micro-controller based intelligent hardware on both transmitter and receiver side has been designed and implemented on printed circuit boards. The electronic circuits use a combination of analog and digital components that feed into the microcontroller to give the transmitter position estimates. The position estimate of the transmitters is obtained from the ATOF and DTOA of the wave bursts received at multiple receivers fixed at known locations. This information is then given to a Kalman filter algorithm for post processing to further increase the accuracy and robustness of the output results. An innovative scheme to tag each transmitter has also been developed and implemented. A first prototype has been built for the 1D case and has been thoroughly tested under numerous extreme conditions. Results are provided for this system as well as a detailed plan on how to extend this system to the 2D and 3D cases. Even though the system has been designed for realtime image guided surgery, it has many applications such as robotics, virtual reality and motion capture studies for ergonomics.3.2.1 Receiver Amplifier The receiver amplifier circuit, as shown in Figure 3.5, is comprised of two amplification stages. The first stage (consisting of OPA1, OPA2, R1, R2 and C1) provides a high differential gain at signal frequencies around 75 anbsp;...
|Title||:||Intelligent Instrumentation and a Robust Dynamic Model for an Ultrasonic Navigation System for Improved Neuro-surgery|
|Publisher||:||ProQuest - 2007|