The following information was submitted:
Transactions: INTERNATIONAL JOURNAL of MATHEMATICAL MODELS AND METHODS IN APPLIED SCIENCES
Transactions ID Number: 17-177
Full Name: Lai Khin Wee
Position: Researcher
Age: ON
Sex: Male
Address: Max Planck Ring-9
Country: GERMANY
Tel:
Tel prefix:
Fax:
E-mail address: khin-wee.lai@tu-ilmenau.de
Other E-mails: eko@utm.my, kwlai2@live.utm.my
Title of the Paper: Innovative Waveform Generator Designs for Ultrasound Therapy Machine using programmable FPGA approaches
Authors as they appear in the Paper: Lai Khin Wee, Eko Supriyanto
Email addresses of all the authors: khin-wee.lai@tu-ilmenau,de, eko@utm.my
Number of paper pages: 9
Abstract: The current ultrasound therapy machines are implementing continuous waveform, which in fact, is not an optimum technique for therapy treatment process. Apparently, pulse waveform appearing as a more effectively way of signal generation in terms of its power consumption, low cost hardware and short timing used. In order to overcome these drawbacks of conventional therapy machines, we proposed a programmable pulse generator for pulse waveform production with high frequency more than 1MHz through Cyclone 2 Field Programmable Gate Array (FPGA) development board. The generator is developed with maximum controllable 10 number of burst and clock frequency 50MHz. Register Transfer Level designs with Very-High-Speed Integrated Circuit Hardware Description Language (VHDL) coding are also implemented throughout this project. Pin assignment was used to assign the pin connection in FPGA for linkage of input and output data of FPGA. The result of generated waveforms were observe!
d using oscilloscope. Based on the findings, the developed programmable FPGA is able to produce high frequency signal effectively and accurately.
Keywords: Ultrasound, field programmable gate array (FPGA), pulse generator, waveform, therapy
EXTENSION of the file: .pdf
Special (Invited) Session: A Novel Programmable Waveform Generator for Ultrasound Therapy Machine using FPGA
Organizer of the Session: 659-276
How Did you learn about congress:
IP ADDRESS: 141.24.14.68
