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Content Provider | IEEE Xplore Digital Library |
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Author | Poustinchi, M. Musallam, S. |
Copyright Year | 2013 |
Description | Author affiliation: Dept. of Electr. & Comput. Eng., McGill Univ., Montreal, QC, Canada (Poustinchi, M.; Musallam, S.) |
Abstract | Millions of patients around the world suffer from neurological disorders. Many of these diseases such as Parkinson's are due to degeneration of Dopaminergic neurons. Our ultimate goal is to develop an intelligent implantable CMOS neurotrophic factor delivery microsystem which can maintain therapeutic levels of chemical concentrations in the brain by protecting the healthy neurons and restoring damaged ones. The hybrid microsystem is composed of neural probes fitted with novel sensors that can sense micromolar concentration of neurotransmitters (dopamine) and embedded negative feedback circuits that control the flow of pharmacological agents in micro fluidic channels. Additionally MEMS (Micro Electro Mechanical System) pumps connected to the probes to inject micromolar concentration of neurotrophic factors such as GDNF into the brain in order to protect and restore dopaminergic neurons in the nigrostriatal pathway. The focus of this manuscript is on sensing, control and decision making circuitry. It consists of a current conveyer, a low noise low power amplifier, an integrator and a comparator with offset cancelation. Circuit is fabricated in CMOS 0.18 um with low power consumption of 921 nW while maintaining a bandwidth of 2.75K Hertz. |
Starting Page | 863 |
Ending Page | 867 |
File Size | 4106899 |
Page Count | 5 |
File Format | |
ISBN | 9781467319690 |
ISSN | 19483554 |
DOI | 10.1109/NER.2013.6696071 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2013-11-06 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Electrodes Parkinson's disease Neurons Sensors CMOS integrated circuits Gain |
Content Type | Text |
Resource Type | Article |
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