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

Wave Parameters

Wave Parameters

The simplest mechanical waves are associated with simple harmonic motion and repeat themselves for several cycles. These simple harmonic waves can be modeled using a combination of sine and cosine functions. Consider a simplified surface water wave that moves across the water's surface. Unlike complex ocean waves, in surface water waves, water moves vertically, oscillating up and down, whereas the disturbance of the wave moves horizontally through the medium. If a seagull is floating on the...

You might also read

Related Articles

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

Sort by

Same author

Neural spike compression through salient sample extraction and curve fitting dedicated to high-density brain implants.

Communications engineering·2025

Same author

Real-time, neural signal processing for high-density brain-implantable devices.

Bioelectronic medicine·2025

Same author

Intertwined-pulse modulation for compressive data telemetry.

Scientific reports·2022

Same author

Data Transformation in the Processing of Neuronal Signals: A Powerful Tool to Illuminate Informative Contents.

IEEE reviews in biomedical engineering·2022

Same author

Wireless, miniaturized, semi-implantable electrocorticography microsystem validated in vivo.

Scientific reports·2020

Same author

Spike Detection Technique Based on Spike Augmentation with Low Computational and Hardware Complexity.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2020

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

Electroencephalographic Signal Acquisition Framework for Neurodiverse: A Case Study of Dolphin-Assisted Therapy

Electroencephalographic Signal Acquisition Framework for Neurodiverse: A Case Study of Dolphin-Assisted Therapy

Published on: June 27, 2025

A 64-channel neural signal processor/ compressor based on Haar wavelet transform.

Mohammad Ali Shaeri¹, Amir M Sodagar, Hamid Abrishami-Moghaddam

¹Research Laboratory for Integrated Circuits and Systems, Department of Electrical and Computer Engineering, KNToosi University of Technology, Tehran, Iran.

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 a Haar wavelet-based signal processor for implantable neural recorders. It achieves high-quality neural signal compression with reduced circuit complexity and silicon area, ideal for microsystems.

More Related Videos

A Procedure for Implanting Organized Arrays of Microwires for Single-unit Recordings in Awake, Behaving Animals

A Procedure for Implanting Organized Arrays of Microwires for Single-unit Recordings in Awake, Behaving Animals

Published on: February 14, 2014

Related Experiment Videos

Last Updated: May 25, 2026

Electroencephalographic Signal Acquisition Framework for Neurodiverse: A Case Study of Dolphin-Assisted Therapy

Electroencephalographic Signal Acquisition Framework for Neurodiverse: A Case Study of Dolphin-Assisted Therapy

Published on: June 27, 2025

A Procedure for Implanting Organized Arrays of Microwires for Single-unit Recordings in Awake, Behaving Animals

A Procedure for Implanting Organized Arrays of Microwires for Single-unit Recordings in Awake, Behaving Animals

Published on: February 14, 2014

Area of Science:

Biomedical Engineering
Signal Processing
Integrated Circuits

Background:

Implantable neural recording microsystems require efficient signal processing.
Existing compression methods may lack efficiency or require significant hardware resources.

Purpose of the Study:

To present a novel signal processor/compressor for implantable neural recording microsystems.
To evaluate the performance of Haar wavelet transform for neural signal compression.

Main Methods:

A 64-channel, 8-bit signal processor was designed using a 0.13-μm standard CMOS process.
Haar wavelet transform was employed for neural signal compression.
Performance was compared against other mathematical transforms.

Main Results:

Haar wavelet transform offers neural signal compression of comparable quality to existing methods.
The proposed method significantly reduces circuit complexity and silicon area.
The designed processor occupies 113 μm x 110 μm and operates at 3.2 MHz with a 1.8-V supply.

Conclusions:

Haar wavelet transform is a suitable and efficient method for neural signal compression in implantable devices.
The developed signal processor offers a compact and low-power solution for neural recording microsystems.