| dc.contributor |
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
|
| dc.contributor |
Pesterev, Aleksey |
|
| dc.contributor |
Pesterev, Aleksey |
|
| dc.creator |
Farshchi, Shahin |
|
| dc.creator |
Pesterev, Aleksey |
|
| dc.creator |
Nuyujukian, Paul |
|
| dc.creator |
Guenterberg, Eric |
|
| dc.creator |
Mody, Istvan |
|
| dc.creator |
Judy, Jack W. |
|
| dc.date |
2012-05-24T14:06:00Z |
|
| dc.date |
2012-05-24T14:06:00Z |
|
| dc.date |
2010-04 |
|
| dc.date |
2009-10 |
|
| dc.date.accessioned |
2023-03-01T18:04:30Z |
|
| dc.date.available |
2023-03-01T18:04:30Z |
|
| dc.identifier |
1534-4320 |
|
| dc.identifier |
INSPEC Accession Number: 11261001 |
|
| dc.identifier |
http://hdl.handle.net/1721.1/70916 |
|
| dc.identifier |
Farshchi, Shahin et al. “Embedded Neural Recording With TinyOS-Based Wireless-Enabled Processor Modules.” IEEE Transactions on Neural Systems and Rehabilitation Engineering 18.2 (2010): 134–141. Web. © 2010 IEEE. |
|
| dc.identifier |
20071270 |
|
| dc.identifier.uri |
http://localhost:8080/xmlui/handle/CUHPOERS/278647 |
|
| dc.description |
To create a wireless neural recording system that can benefit from the continuous advancements being made in embedded microcontroller and communications technologies, an embedded-system-based architecture for wireless neural recording has been designed, fabricated, and tested. The system consists of commercial-off-the-shelf wireless-enabled processor modules (motes) for communicating the neural signals, and a back-end database server and client application for archiving and browsing the neural signals. A neural-signal-acquisition application has been developed to enable the mote to either acquire neural signals at a rate of 4000 12-bit samples per second, or detect and transmit spike heights and widths sampled at a rate of 16670 12-bit samples per second on a single channel. The motes acquire neural signals via a custom low-noise neural-signal amplifier with adjustable gain and high-pass corner frequency that has been designed, and fabricated in a 1.5-μm CMOS process. In addition to browsing acquired neural data, the client application enables the user to remotely toggle modes of operation (real-time or spike-only), as well as amplifier gain and high-pass corner frequency. |
|
| dc.format |
application/pdf |
|
| dc.language |
en_US |
|
| dc.publisher |
Institute of Electrical and Electronics Engineers |
|
| dc.relation |
http://dx.doi.org/10.1109/tnsre.2009.2039606 |
|
| dc.relation |
IEEE Transactions on Neural Systems and Rehabilitation Engineering |
|
| dc.rights |
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. |
|
| dc.source |
IEEE |
|
| dc.title |
Embedded Neural Recording With TinyOS-Based Wireless-Enabled Processor Modules |
|
| dc.type |
Article |
|
| dc.type |
http://purl.org/eprint/type/JournalArticle |
|