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

Bandpass Sampling

Bandpass Sampling

In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2. The spectrum...

Parallel Resonance

Parallel Resonance

The parallel RLC circuit is an arrangement where the resistor (R), inductor (L), and capacitor (C) are all connected to the same nodes and, as a result, share the same voltage across them. The parallel RLC circuit is analyzed in terms of admittance (Y), which reflects the ease with which current can flow. The admittance is given by:

Sampling Continuous Time Signal

Sampling Continuous Time Signal

In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...

Aliasing

Aliasing

Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original signal...

Passive Filters

Passive Filters

Passive filters are utilized to shape the frequency spectrum of signals across a diverse array of applications. These filters, using only passive elements like resistors (R), inductors (L), and capacitors (C), are capable of selectively allowing or blocking certain frequency ranges without the need for external power sources.
Low-Pass Filters
Low-pass filters are designed to transmit signals with frequencies lower than the cutoff frequency, ωc, and attenuate those above it. The cutoff frequency...

Active Filters

Active Filters

Active filters are electronic circuits that use operational amplifiers (op-amps), resistors, and capacitors to filter out unwanted frequency components from a signal. A first-order low-pass active filter is designed to pass signals with a frequency lower than a certain cutoff frequency and attenuate frequencies higher than that cutoff frequency. The transfer function for a first-order low-pass active filter is:

You might also read

Related Articles

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

Sort by

Same author

Closed-loop error damping in human BCI using pre-error motor cortex activity.

bioRxiv : the preprint server for biology·2026

Same author

Mapping the Causal Roles of Non-Primary Motor Areas in Human Reach Planning and Execution.

Human brain mapping·2026

Same author

Motor Cortex Coverage Predicts Signal Strength of a Stentrode Endovascular Brain-Computer Interface.

medRxiv : the preprint server for health sciences·2025

Same author

Signal properties and stability of a chronically implanted endovascular brain computer interface.

medRxiv : the preprint server for health sciences·2025

Same author

A posture subspace in the primary motor cortex.

Neuron·2025

Same author

Learning Frame-Level Classifiers for Video-Based Real-Time Assessment of Stroke Rehabilitation Exercises From Weakly Annotated Datasets.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2025

Same journal

Analysis of End-Tidal CO2 Variability During Plateau Waves Episodes: An Information Theoretic Approach<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025

Same journal

AI and Tomosynthesis for Breast Cancer Molecular Subtyping: A step toward precision medicine<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025

Same journal

Towards Sustainable Protein Recovery from Biological Waste: Assessing Polyethersulfone-based Microfiltration.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025

Same journal

Analysis of the cardiovascular response to standardized polymicrobial peritonitis experimental model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025

Same journal

Automated Wrist Ultrasound Image Bone Enhancement and Segmentation Using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025

Same journal

A Deep Learning approach for Depressive Symptoms assessment in Parkinson's disease patients using facial videos.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025

See all related articles

Search research articles

Related Experiment Video

Updated: May 25, 2026

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

Frequency tracking and variable bandwidth for line noise filtering without a reference.

John W Kelly¹, Jennifer L Collinger, Alan D Degenhart

¹Dept of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA. kelly@ece.cmu.edu

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

|January 19, 2012

Summary

This summary is machine-generated.

This study introduces an adaptive noise canceling (ANC) method to filter line noise from neural signals. The technique digitally generates a reference signal, offering narrower bandwidth and improved accuracy for electrocorticographic (ECoG) recordings.

More Related Videos

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Published on: March 13, 2017

Implementation of a Reference Interferometer for Nanodetection

Implementation of a Reference Interferometer for Nanodetection

Published on: April 26, 2014

Related Experiment Videos

Last Updated: May 25, 2026

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

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Published on: March 13, 2017

Implementation of a Reference Interferometer for Nanodetection

Implementation of a Reference Interferometer for Nanodetection

Published on: April 26, 2014

Area of Science:

Biomedical Engineering
Signal Processing
Neuroscience

Background:

Power line interference is a common artifact in electrophysiological recordings.
Existing notch filters can be too narrow or require a separate noise reference.
Adaptive Noise Canceling (ANC) typically needs an external noise reference signal.

Purpose of the Study:

To present a novel adaptive noise canceling (ANC) method for filtering line noise.
To eliminate sinusoidal contamination in neural signals without a reference noise source.
To achieve a narrower filter bandwidth compared to traditional notch filters.

Main Methods:

A digitally generated sinusoidal reference signal is used instead of an external one.
The filter automatically tracks drifting power line frequencies.
The learning rate is dynamically adjusted for optimal convergence and bandwidth control.

Main Results:

The proposed ANC method effectively removes sinusoidal line noise.
The filter achieves a narrower bandwidth than conventional notch filters.
The technique demonstrates faster and more accurate signal convergence.

Conclusions:

This ANC method provides an effective solution for line noise removal in neural recordings.
The technique is versatile and applicable beyond electrocorticographic (ECoG) signals.
Automatic adjustment of learning rate enhances filter performance and adaptability.