Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Upsampling

Upsampling

Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...

Reconstruction of Signal using Interpolation

Reconstruction of Signal using Interpolation

Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next sampling...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Signed-gradient adaptive step size LMS algorithm for biomedical applications.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2015

Same author

A novel gradient adaptive step size LMS algorithm with dual adaptive filters.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2013

See all related articles

Search research articles

Related Experiment Video

Updated: May 14, 2026

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

Modified Log-LMS adaptive filter with low signal distortion for biomedical applications.

Yuzhong Jiao¹, Rex Y P Cheung, Mark P C Mok

¹Hong Kong Applied Science and Technology Research Institute ASTRI, Hong Kong, China. yzjiao@astri.org

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|February 1, 2013

Summary

A modified Log-LMS algorithm enhances noise cancellation for biomedical signals like electrocardiography (ECG). This adaptive filtering method reduces distortion and improves signal processing in noisy environments.

More Related Videos

Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters

Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters

Published on: February 4, 2018

X-ray Beam Induced Current Measurements for Multi-Modal X-ray Microscopy of Solar Cells

X-ray Beam Induced Current Measurements for Multi-Modal X-ray Microscopy of Solar Cells

Published on: August 20, 2019

Related Experiment Videos

Last Updated: May 14, 2026

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters

Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters

Published on: February 4, 2018

X-ray Beam Induced Current Measurements for Multi-Modal X-ray Microscopy of Solar Cells

X-ray Beam Induced Current Measurements for Multi-Modal X-ray Microscopy of Solar Cells

Published on: August 20, 2019

Area of Science:

Biomedical Engineering
Signal Processing
Adaptive Filtering

Background:

Weak biological signals (e.g., ECG) are vulnerable to noise.
Adaptive filters, particularly the Least Mean Squares (LMS) algorithm, are used for noise cancellation.
The Log-LMS algorithm offers reduced complexity but can cause signal distortion.

Purpose of the Study:

To present a modified Log-LMS algorithm for improved biomedical signal processing.
To address the signal distortion issue inherent in standard LMS and Log-LMS algorithms.
To evaluate the modified algorithm's performance in realistic noisy biomedical scenarios.

Main Methods:

Development of a modified Log-LMS algorithm with a two-stage convergence process.
Application of distinct quantization methods in each stage of the algorithm.
Simulation analysis using two specific biomedical applications: helicopter stethoscope data and ECG with power line interference.

Main Results:

The modified Log-LMS algorithm demonstrates fast convergence.
The proposed method achieves significantly lower signal distortion compared to existing algorithms.
Effective noise reduction was observed in simulated periodic life signals.

Conclusions:

The modified Log-LMS algorithm offers a superior approach for adaptive filtering of biomedical signals.
This algorithm effectively balances computational efficiency with signal fidelity.
It shows promise for applications requiring robust noise cancellation in challenging environments.