DocumentCode :
2428089
Title :
A low power biomedical signal processor ASIC based on hardware software codesign
Author :
Nie, Z.D. ; Wang, L. ; Chen, W.G. ; Zhang, T. ; Zhang, Y.T.
Author_Institution :
Inst. of Biomed. & Health Eng. (IBHE), Shenzhen Inst. of Adv. Technol. (SIAT), Shenzhen, China
fYear :
2009
fDate :
3-6 Sept. 2009
Firstpage :
2559
Lastpage :
2562
Abstract :
A low power biomedical digital signal processor ASIC based on hardware and software codesign methodology was presented in this paper. The codesign methodology was used to achieve higher system performance and design flexibility. The hardware implementation included a low power 32bit RISC CPU ARM7TDMI, a low power AHB-compatible bus, and a scalable digital co-processor that was optimized for low power Fast Fourier Transform (FFT) calculations. The co-processor could be scaled for 8-point, 16-point and 32-point FFTs, taking approximate 50, 100 and 150 clock circles, respectively. The complete design was intensively simulated using ARM DSM model and was emulated by ARM Versatile platform, before conducted to silicon. The multi-million-gate ASIC was fabricated using SMIC 0.18 mum mixed-signal CMOS 1P6M technology. The die area measures 5,000 mum times 2,350 mum. The power consumption was approximately 3.6 mW at 1.8 V power supply and 1 MHz clock rate. The power consumption for FFT calculations was less than 1.5 % comparing with the conventional embedded software-based solution.
Keywords :
application specific integrated circuits; coprocessors; embedded systems; fast Fourier transforms; hardware-software codesign; medical signal processing; ARM DSM model; ARM Versatile platform; ASIC processor; Fast Fourier Transform; biomedical signal processor; design flexibility; embedded software based solution; hardware software codesign; power supply; scalable digital coprocessor; Algorithms; Biomedical Engineering; Computer Simulation; Computers; Equipment Design; Fourier Analysis; Humans; Neural Networks (Computer); Pattern Recognition, Automated; Programming Languages; Signal Processing, Computer-Assisted; Software;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Conference_Location :
Minneapolis, MN
ISSN :
1557-170X
Print_ISBN :
978-1-4244-3296-7
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/IEMBS.2009.5335295
Filename :
5335295
Link To Document :
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