Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

A Simultaneous ECG-PCG Acquisition System with Real-Time Burst-Adaptive Noise Cancellation

Avishka Herath, Malith Jayalath, Kumudu Kaushalya, Sanjana Kapukotuwa, Chathuni Wijegunawardena, Pahan Mendis, Kithmin Wickremasinghe, Duminda Samarasinghe, Wageesha N. Manamperi, Chamira U. S. Edussooriya

TL;DR

The paper addresses reliable cardiac screening in noisy clinical environments by integrating simultaneous ECG and PCG acquisition with a real-time adaptive noise cancellation pipeline. It introduces a burst-adaptive NLMS (BA-NLMS) algorithm for PCG denoising and an elliptic IIR denoising chain for ECG, all implemented in a portable device with wireless streaming. Validation on hospital-noise datasets and real-device recordings shows BA-NLMS achieving PCG and ECG improvements of $37.01$ dB and $30.32$ dB, respectively, demonstrating robust performance in real-world settings. The work demonstrates a practical path toward embedded, dual-modality cardiac screening capable of operating in resource-constrained environments and during routine clinical use.

Abstract

Cardiac auscultation is an essential clinical skill, requiring excellent hearing to distinguish subtle differences in timing and pitch of heart sounds. However, diagnosing solely from these sounds is often challenging due to interference from surrounding noise, and the information may be limited. Existing solutions that adaptively cancel external noise are either not real-time or are computationally intensive, making them unsuitable for implementation in a portable system. This work proposes an end-to-end system with a real-time adaptive noise cancellation pipeline integrated into a device that simultaneously acquires electrocardiogram (ECG) and phonocardiogram (PCG) signals. The performance of the system is validated using real-world hospital noise datasets and recordings captured with the dual-modality device. For PCG and ECG signals recorded from the device in noisy hospital settings, the proposed algorithms achieved signal-to-noise ratio improvements of 37.01 dB and 30.32 dB, respectively. These results demonstrate the systems effectiveness in enabling reliable and accessible cardiac screening, including noisy hospital environments typical of resource-constrained settings.

A Simultaneous ECG-PCG Acquisition System with Real-Time Burst-Adaptive Noise Cancellation

TL;DR

The paper addresses reliable cardiac screening in noisy clinical environments by integrating simultaneous ECG and PCG acquisition with a real-time adaptive noise cancellation pipeline. It introduces a burst-adaptive NLMS (BA-NLMS) algorithm for PCG denoising and an elliptic IIR denoising chain for ECG, all implemented in a portable device with wireless streaming. Validation on hospital-noise datasets and real-device recordings shows BA-NLMS achieving PCG and ECG improvements of dB and dB, respectively, demonstrating robust performance in real-world settings. The work demonstrates a practical path toward embedded, dual-modality cardiac screening capable of operating in resource-constrained environments and during routine clinical use.

Abstract

Cardiac auscultation is an essential clinical skill, requiring excellent hearing to distinguish subtle differences in timing and pitch of heart sounds. However, diagnosing solely from these sounds is often challenging due to interference from surrounding noise, and the information may be limited. Existing solutions that adaptively cancel external noise are either not real-time or are computationally intensive, making them unsuitable for implementation in a portable system. This work proposes an end-to-end system with a real-time adaptive noise cancellation pipeline integrated into a device that simultaneously acquires electrocardiogram (ECG) and phonocardiogram (PCG) signals. The performance of the system is validated using real-world hospital noise datasets and recordings captured with the dual-modality device. For PCG and ECG signals recorded from the device in noisy hospital settings, the proposed algorithms achieved signal-to-noise ratio improvements of 37.01 dB and 30.32 dB, respectively. These results demonstrate the systems effectiveness in enabling reliable and accessible cardiac screening, including noisy hospital environments typical of resource-constrained settings.

Paper Structure

This paper contains 10 sections, 6 equations, 4 figures, 2 tables.

Table of Contents

  1. Introduction
  2. System Overview
  3. Simultaneous Acquisition of ECG and PCG Signals
  4. Real-Time Adaptive Noise Cancellation for PCG Signals
  5. Real-time Denoising Pipeline for ECG Signals
  6. Results and Discussion
  7. Performance Evaluation with Artificially Induced Noise
  8. Prototype Performance Validation with Recorded Data
  9. Conclusion
  10. Acknowledgements

Figures (4)

  • Figure 1: Block diagram of the overall system architecture. Signals from dry Ag/AgCl electrodes (acquiring ECG) and digital microelectromechanical system (MEMS) microphones (acquiring PCG) are captured, processed by a microcontroller unit (MCU), and transmitted wirelessly to a computer for real-time ANC and signal visualization.
  • Figure 2: Photographs of the prototype with the design features annotated.
  • Figure 3: Denoising performance of the Burst-Adaptive NLMS filter on a PCG signal. A clean signal was corrupted by burst noise to an input SNR of $-3$ dB. The filtered output shows an $\Delta$SNR of $+19.31$ dB and a CC of 0.9889.
  • Figure 4: Denoising performance of the proposed real-time filter algorithms on recorded noisy ECG and PCG signals. Spectrograms (left) and time-domain plots (right) show the improvement in the noisy ECG (input SNR of $-9.08$ dB) and noisy PCG (input SNR of $-2.08$ dB) signals, respectively.