A miniature neural recording device

Edward, Epsy S, Kouzani, Abbas Z, Berk, Julian and Tye, Susannah J 2016, A miniature neural recording device, in ICIT 2016 : Proceedings of the IEEE International Conference on Industrial Technology, IEEE, Piscataway, N.J., pp. 1012-1015, doi: 10.1109/ICIT.2016.7474892.

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Title A miniature neural recording device
Author(s) Edward, Epsy S
Kouzani, Abbas ZORCID iD for Kouzani, Abbas Z orcid.org/0000-0002-6292-1214
Berk, Julian
Tye, Susannah J
Conference name International Conference on Industrial Technology (ICIT). Conference (2016 : Taipei, Taiwan)
Conference location Taipei, Taiwan
Conference dates 14- 17 March. 2016
Title of proceedings ICIT 2016 : Proceedings of the IEEE International Conference on Industrial Technology
Publication date 2016
Conference series International Conference on Industrial Technology
Start page 1012
End page 1015
Total pages 4
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) neural recording
Summary This paper presents a portable neural recording device for use with laboratory animals. It can detect and record neural signals from the cortical region of the brain during pre-clinical trials. The device utilizes simplified circuitry to perform signal detection, filtering, sampling, and storage. It includes analog and digital components each implemented on a separate small printed circuit board. The two printed circuit boards are then attached to one another to form the device. It is capable of uninterrupted operation for over 2 hours on a single coin battery. A bench-testing of the device was performed with pre-recorded neural signal which then injected to the input of the device to give validation of efficient operation of the device. Its amplification and filtration features have been analyzed. An overall 56 dB amplification and filtration in the frequency range of 300 Hz to 4 KHz was achieved. Sampling and storage at a reduced power and computational load is demonstrated with uninterrupted storage of the neural signal. A comparison of the input and reconstructed neural signals shows minimal variation error.
ISBN 9781467380751
Language eng
DOI 10.1109/ICIT.2016.7474892
Field of Research 090604 Microelectronics and Integrated Circuits
090304 Medical Devices
Socio Economic Objective 861603 Integrated Circuits and Devices
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2016, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30086134

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