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Published on: November 19, 2017
Thermal impact of an active 3-D microelectrode array implanted in the brain.
Sohee Kim1, Prashant Tathireddy, Richard A Normann
1Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT 84112, USA. soheek@eng.utah.edu
This study investigated the heat generated by implantable neural devices. Researchers found that temperature increases predictably with device power, ensuring safe brain tissue temperatures for wireless neural interfaces.
Area of Science:
- Biomedical Engineering
- Neuroscience
- Thermal Analysis
Background:
- Chronically implantable wireless neural interfaces require integrated circuits (ICs) to eliminate wired connections.
- Integrated circuits dissipate power, potentially increasing temperature in surrounding brain tissues.
- Understanding thermal effects is crucial for the safety and efficacy of neural implantable devices.
Purpose of the Study:
- To investigate the thermal influence of an integrated 3-D Utah Electrode Array (UEA) device implanted in the brain.
- To validate numerical models with experimental measurements for accurate thermal prediction.
- To analyze factors affecting tissue heating, including power dissipation, blood perfusion, and device geometry.
Main Methods:
- Numerical simulation using finite element analysis (FEA).
- Experimental temperature measurements in vitro and in vivo.
- Validation of numerical models against experimental data.
Main Results:
- Numerically calculated and experimentally measured temperature increases showed good agreement.
- The validated model predicted a linear relationship between temperature increase and power dissipation (0.029 °C/mW).
- Investigated the impact of blood perfusion, brain metabolism, and UEA geometry on tissue heating.
Conclusions:
- The thermal influence of the 3-D Utah Electrode Array (UEA) is predictable and can be accurately modeled.
- The study provides a validated model for assessing temperature increases in brain tissue due to neural implantable devices.
- Findings support the development of safe and effective chronically implantable wireless neural interfaces.
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