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

Search research articles

Related Experiment Video

Updated: Jun 12, 2026

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays

Published on: May 29, 2017

Energy-efficient waveform shapes for neural stimulation revealed with a genetic algorithm.

Amorn Wongsarnpigoon¹, Warren M Grill

¹Department of Biomedical Engineering, Duke University, Hudson Hall, Durham, NC 27708-0281, USA.

Journal of Neural Engineering

|June 24, 2010

Summary

Researchers optimized neural stimulation waveforms for energy efficiency using a genetic algorithm (GA). Optimized waveforms significantly improve energy and charge efficiency, potentially extending battery life in implantable devices.

Related Concept Videos

You might also read

Related Articles

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

Sort by

Same author

Model-based design and placement analysis for epidural cortical stimulation.

Journal of neural engineering·2026

Same author

Sacral Neuromodulation for Refractory Overactive Bladder: Closing the Gaps in Anatomy, Mechanisms, and Parameter Selection.

Advances in therapy·2026

Same author

Histologically Informed Multiscale Modeling of the Neuronal Elements Activated by TMS.

bioRxiv : the preprint server for biology·2026

Same author

Dual-frequency spinal cord stimulation increases responder rates for treatment of neuropathic pain.

Pain·2026

Same author

A Roadmap to Navigate the Future of Neural Engineering.

Journal of neural engineering·2026

Same author

Addendum: Modified cable equation incorporating transverse polarization of neuronal membranes for accurate coupling of electric fields (<i>J. Neural Eng</i>.<b>15</b>026003).

Journal of neural engineering·2026

Area of Science:

Biomedical Engineering
Computational Neuroscience
Neuroscience

Background:

Energy efficiency is critical for battery-powered implantable neural stimulators.
Optimizing waveform shape can enhance device longevity and reduce patient burden.

Purpose of the Study:

To determine the energy-optimal waveform shape for neural stimulation using a genetic algorithm (GA).
To compare the efficiency of GA-optimized waveforms against conventional shapes in computational models and in vivo.

Main Methods:

Coupling a genetic algorithm (GA) to a computational model of extracellular stimulation of mammalian myelinated axons.
Testing optimized waveforms in a population model of mammalian axons and in vivo experiments on cat sciatic nerve.

Related Experiment Videos

Last Updated: Jun 12, 2026

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays

Published on: May 29, 2017

Main Results:

The GA converged on energy-optimal waveforms, resembling truncated Gaussian curves.
GA-optimized waveforms demonstrated superior energy and charge efficiency compared to conventional shapes.
Waveform characteristics were influenced by the parameters of charge-balancing anodic pulses.

Conclusions:

GA-optimized waveforms offer significant improvements in energy and charge efficiency for neural stimulation.
These optimized waveforms can potentially extend battery life in implantable stimulators, reducing surgery frequency and associated risks.
The study highlights the potential of computational optimization for advancing implantable neurostimulation technology.