Ibrahim M.R.,CTech Labs Edwar Technology |
Ihsan M.F.,CTech Labs Edwar Technology |
Maharani R.,CTech Labs Edwar Technology |
Taruno W.P.,CTech Labs Edwar Technology
AIP Conference Proceedings | Year: 2017
This study implemented nearest neighbor algorithm to classifies the position of phantom after scanned using Brain Electrical Capacitance Volume Tomography (ECVT). With k-Nearest Neighbors algorithms, we evaluated 496 values of capacitance measurement to find its nearest neighbors (highest similarity) and classifies its exact position in the sensor. The performance of this technique reached 93.33% of accuracy. © 2017 Author(s).
Muttakin I.,CTECH Labs Edwar Technology |
Yusuf A.,CTECH Labs Edwar Technology |
Widada W.,CTECH Labs Edwar Technology |
Taruno W.P.,CTECH Labs Edwar Technology
Telkomnika (Telecommunication Computing Electronics and Control) | Year: 2015
Capacitance measurement accuracy is affected by phase conformity between signal and reference. This work describes phase detection scheme which is necessary for phase synchronization in tomography application. Core processing for calculating phase and amplitude of the detected signal was built on FPGA (Field-Programmable Gate-Array) platform. Phase shift demodulation algorithm employs IP core provided by Xilinx FPGA. Direct digital synthesizer (DDS), multiplier, accumulator, and CORDIC (coordinate rotation digital computer) modules were used as excitation-reference signal generator, signal multiplication, accumulation, and conversion to polar coordinate in order to conduct trigonometric operation respectively. Hardware design was emulated on MATLAB-Xilinx System Generator to observe its performance. Phase detection range 0-114.58° and mean absolute error 0.58° have been achieved. Data processing rate solely at digital signal stage was approximately 100data/s suitable for 32-channel electrical capacitance volume tomography (ECVT) system.