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Single glucose biofuel cells implanted in rats power electronic devices.

ABSTRACT: We describe the first implanted glucose biofuel cell (GBFC) that is capable of generating sufficient power from a mammal's body fluids to act as the sole power source for electronic devices. This GBFC is based on carbon nanotube/enzyme electrodes, which utilize glucose oxidase for glucose oxidation and laccase for dioxygen reduction. The GBFC, implanted in the abdominal cavity of a rat, produces an average open-circuit voltage of 0.57 V. This implanted GBFC delivered a power output of 38.7??W, which corresponded to a power density of 193.5??W?cm(-2) and a volumetric power of 161??W?mL(-1). We demonstrate that one single implanted enzymatic GBFC can power a light-emitting diode (LED), or a digital thermometer. In addition, no signs of rejection or inflammation were observed after 110?days implantation in the rat.

SUBMITTER: Zebda A

PROVIDER: S-EPMC3605613 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Single glucose biofuel cells implanted in rats power electronic devices.

Zebda A A Cosnier S S Alcaraz J-P JP Holzinger M M Le Goff A A Gondran C C Boucher F F Giroud F F Gorgy K K Lamraoui H H Cinquin P P

Scientific reports 20130101

We describe the first implanted glucose biofuel cell (GBFC) that is capable of generating sufficient power from a mammal's body fluids to act as the sole power source for electronic devices. This GBFC is based on carbon nanotube/enzyme electrodes, which utilize glucose oxidase for glucose oxidation and laccase for dioxygen reduction. The GBFC, implanted in the abdominal cavity of a rat, produces an average open-circuit voltage of 0.57 V. This implanted GBFC delivered a power output of 38.7 μW, w ...[more]

PMID: 23519113

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Project description:OBJECTIVE:Closed-loop implantable neural stimulators are an exciting treatment option for patients with medically refractory epilepsy, with a number of new devices in or nearing clinical trials. These devices must accurately detect a variety of seizure types in order to reliably deliver therapeutic stimulation. While effective, broadly-applicable seizure detection algorithms have recently been published, these methods are too computationally intensive to be directly deployed in an implantable device. We demonstrate a strategy that couples devices to cloud computing resources in order to implement complex seizure detection methods on an implantable device platform. APPROACH:We use a sensitive gating algorithm capable of running on-board a device to identify potential seizure epochs and transmit these epochs to a cloud-based analysis platform. A precise seizure detection algorithm is then applied to the candidate epochs, leveraging cloud computing resources for accurate seizure event detection. This seizure detection strategy was developed and tested on eleven human implanted device recordings generated using the NeuroVista Seizure Advisory System. MAIN RESULTS:The gating algorithm achieved high-sensitivity detection using a small feature set as input to a linear classifier, compatible with the computational capability of next-generation implantable devices. The cloud-based precision algorithm successfully identified all seizures transmitted by the gating algorithm while significantly reducing the false positive rate. Across all subjects, this joint approach detected 99% of seizures with a false positive rate of 0.03?h-1. SIGNIFICANCE:We present a novel framework for implementing computationally intensive algorithms on human data recorded from an implanted device. By using telemetry to intelligently access cloud-based computational resources, the next generation of neuro-implantable devices will leverage sophisticated algorithms with potential to greatly improve device performance and patient outcomes.

Dataset Information

Single glucose biofuel cells implanted in rats power electronic devices.

Publications

Single glucose biofuel cells implanted in rats power electronic devices.

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