Approximate Pruned and Truncated Haar Discrete Wavelet Transform VLSI Hardware for Energy-Efficient ECG Signal Processing
Also Available Domains DSP Core|Xilinx ISE
Abstract
Approximate or inexact computing is a computing paradigm that can trade energy and computing time with accuracy of output. Error-tolerant applications, such as multimedia and signal processing, can process the information with lower-than-standard accuracy at the circuit level while still fulfilling a good and acceptable service quality at the application level. The automatic detection of R-peaks in an electrocardiogram (ECG) signal is the essential step preceding ECG processing and analysis. The Haar discrete wavelet transform (HDWT) is a low-complexity pre-processing filter suitable to detect ECG R-peaks in embedded systems like wearable devices, which are incredibly energy constrained. This work presents an approximate HDWT hardware architecture for ECG processing at very high energy efficiency. Our best-proposal employing pruning within the approximate HDWT hardware architecture requires just seven additions. The use of a truncation technique to improve energy efficiency is also investigated herein by observing the evolution of the signal-to-noise ratio and the ultimate impact in the ECG peak-detection application. This research finds that our HDWT approximate hardware architecture proposal accepts higher truncation levels than the original HDWT. In summary: Our results shows energy reduction when combining our HDWT matrix approximation proposal with the pruning and the highest acceptable level of truncation while still maintaining the R-peak detection performance accuracy average.
Index Terms— Approximate computing, Haar discrete wavelet transform, VLSI design, energy efficiency, ECG processing.
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Block Diagram
Specifications
Software Requirements:
- Xilinx Vivado
- HDL: Verilog
Hardware Requirements:
- Microsoft® Windows XP,
- Intel® Pentium® 4 processor or Pentium 4 equivalent with SSE support
- 512 MB RAM
- 100 MB of available disk space
Learning Outcomes
- Basics of Digital Electronics
- FPGA design Flow
- Introduction to Verilog Coding
- Different modeling styles in Verilog
- Data Flow modeling
- Structural modeling
- Behavioral modeling
- Mixed level modeling
- Concept of Approximation
- Importance of Approximate computing
- Drawbacks of Exact Computing in error tolerant applications
- Introduction to Discrete Wavelet
- Knowledge on various types of wavelets
- Study on ECG signal processing
- Knowledge on Haar Discrete Wavelet
- Applications of HDW in real time applications
- Scope of approximation concept in today’s world
- Applications in real time
- Xilinx Vivado for design and simulation
- Generation of Netlist
- Solution providing for real time problems
- Project Development Skills:
- Problem Analysis Skills
- Problem Solving Skills
- Logical Skills
- Designing Skills
- Testing Skills
- Debugging Skills
- Presentation Skills
- Thesis Writing Skills
Paper Publishing
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