Journal of Electronics and Informatics
IRO Journals
Volume 7 — Issue 4 — December 2025

An Area Efficient Lifting Wavelet for ECG R-peak Detection Applications

https://doi.org/10.36548/jei.2025.4.002
Ravi Teja C.
Assistant Professor, Department of Electronics and Communication Engineering, Srinivasa Ramanujan Institute of Technology, Anantapur, Andhra Pradesh
Dharani M.
Department of Electronics and Communication Engineering, Srinivasa Ramanujan Institute of Technology, Anantapur, Andhra Pradesh
Kavitha Y.
Department of Electronics and Communication Engineering, Srinivasa Ramanujan Institute of Technology, Anantapur, Andhra Pradesh
Bhoomika V.
Department of Electronics and Communication Engineering, Srinivasa Ramanujan Institute of Technology, Anantapur, Andhra Pradesh
Imran S.
Department of Electronics and Communication Engineering, Srinivasa Ramanujan Institute of Technology, Anantapur, Andhra Pradesh
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How to Cite

C., Ravi Teja, Dharani M., Kavitha Y., Bhoomika V., and Imran S. 2026. “An Area Efficient Lifting Wavelet for ECG R-Peak Detection Applications”. Journal of Electronics and Informatics 7 (4): 267-80. https://doi.org/10.36548/jei.2025.4.002.
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Keywords

— FPGA
— Biomedical ECG Wearables
— Noise Reduction in ECG Signals
— Lifting-based DWT
— Adaptive Soft Thresholding
Published: 06-01-2026

Abstract

Noise removal is a vital pre-processing step in wearable ECG devices for accurate arrhythmia detection. This paper proposes a hardware-efficient, multiplier-less FPGA architecture for ECG denoising using a lifting-based wavelet transform. A universal thresholding function with soft thresholding enhances signal quality, while a modified lifting-based DWT eliminates multipliers and simplifies computation. An optimized median calculation and thresholding method remove the need for comparators in VLSI design. ECG data from the MIT-BIH databases validate the approach, achieving an SNR improvement of 7.4 dB and an MSE of 0.0206. FPGA implementation on the Nexys 4 DDR board demonstrates low hardware usage and a high operating frequency of 166 MHz, outperforming existing designs.

References

  1. Gon, Anusaka, and Atin Mukherjee. "FPGA-based low-cost architecture for R-peak detection and heart-rate calculation using lifting-based discrete wavelet transform." Circuits, Systems, and Signal Processing 42, no. 1 (2023): 580-600.
  2. BAHRI Mounira, BEDDIAF Seif Eddine. "Analysis ECG signals by adaptive wavelets."
  3. Gon, Anusaka, and Atin Mukherjee. "Design and FPGA implementation of an efficient architecture for noise removal in ECG signals using lifting-based wavelet denoising." (2023).
  4. Guénégo, Béatrice, Caroline Lelandais-Perrault, Emilie Avignon-Meseldzija, Gérard Sou, and Philippe Bénabès. "Impact of Mother Wavelet Choice on Fast Wavelet Transform Performances for Integrated ST Segment Monitoring." Journal of Low Power Electronics and Applications 15, no. 2 (2025): 31.
  5. Seidel, Henrique Bestani, Morgana Macedo Azevedo da Rosa, Guilherme Paim, Eduardo Antonio Cesar Da Costa, Sérgio JM Almeida, and Sergio Bampi. "Approximate pruned and truncated Haar discrete wavelet transform VLSI hardware for energy-efficient ECG signal processing." IEEE Transactions on Circuits and Systems I: Regular Papers 68, no. 5 (2021): 1814-1826.
  6. Kumar, Mahendra, and Satyarth Tiwari. "2-D Discrete Wavelet Decomposition using Low Pass and High Pass Sub-band: A Review." International Journal of Research & Technology 12, no. 3 (2024): 27-31.
  7. Saxena, Shivani, Prasadini Mahapatra, and Ahsan Z. Rizvi. "Construction of wavelet using M-estimation and its Application in R-peak detection." In 2023 International Conference on Recent Advances in Electrical, Electronics & Digital Healthcare Technologies (REEDCON), IEEE, 2023, 211-215.
  8. Dwivedi, Ranjana, Divyanshu Awasthi, and Vinay Kumar Srivastava. "An optimized ECG copyright protection technique and its feature authentication." Computers and Electrical Engineering 126 (2025): 110546.
  9. Singh, Shivam, and Satyarth Tiwari. "Study of 1-D and 2-D Discrete Wavelet Transform for Image Compression Application." International Journal of Research & Technology 12, no. 1 (2024): 6-10.
  10. Waleed, Rasha, Noor Talal Gadawe, and Sahar Lazim Qaddoori. "REAL-TIME PROCESSING STAGES OF ELECTROCARDIOGRAM SIGNAL: A REVIEW." Journal of Modern Technology & Engineering 9, no. 1 (2024).