Subthreshold Energy Harvesters Circuits for Biomedical Implants Applications
Journal Title: EAI Endorsed Transactions on Energy Web - Year 2016, Vol 3, Issue 9
Abstract
This paper reviews the state-of-art of the subthreshold level design energy harvesters for powering biomedical implants. Power consumption and lifespan are crucial requirements for the electronic circuitry of implantable systems. In order to meet these challenging requirements, a design for an energy harvester that operates in a subthreshold level offers a promising solution.
Authors and Affiliations
Meriam Gay Bautista, Eryk Dutkiewicz, Michael Heimlich
Keywords
Related Articles
- EP ID EP45152
- DOI http://dx.doi.org/10.4108/eai.28-9-2015.2261402
- Views 242
- Downloads 0
A Survey on Security Issues and Challenges in Mobile Ad-hoc Network
Rapid developments in the communication arena has tremendously improved the transmission procedures today. The amount of information transmission in the commercial and military applications has grown tremendously therefo...
Average Case Analysis of the MST-heuristic for the Power Assignment Problem: Special Cases
We present an average case analysis of the minimum spanning tree heuristic for the power assignment problem. The worst-case approximation ratio of this heuristic is 2. We have the following results: (a) In the one-dimens...
A comparative study based on the Genetic Algorithm (GA) method for the optimal sizing of the standalone photovoltaic system in the Ngoundiane site
We study a sizing method using Artificial Intelligence Techniques (AI) to find the optimal sizes of a standalone photovoltaic system in Ngoundiane, Senegal. The sizing of the PV system is considered here as a mono-object...
Price-based Energy Control for V2G Networks in the Industrial Smart Grid
The energy crisis and global warming call for a new industrial revolution in production and distribution of renewable energy. Distributed power generation will be well developed in the new smart electricity distribution...
Analysis of the Energy-Performance Tradeoff for Delayed Mobile Offloading
Mobile cloud offloading that migrates heavy computation from mobile devices to powerful cloud servers through communication networks can alleviate the hardware limitations of mobile devices for higher performance and ene...