Abstract
Local field potentials (LFPs) are popularly used in wireless neural interface due to its chronic stability and robustness against noise and radio interferences. On-chip data compression is advantageous that allows for integration with the recent low-power, low-data-rate wireless technologies to ensure reliable operations. In this paper, we propose a streaming principal component analysis (PCA) based algorithm and its microchip implementation to compress multichannel LFP data. The chip has been designed in a 65nm CMOS technology and occupies a silicon area of 0.06mm2. It has been tested with Guinea pig auditory cortex data recorded with a multi-shank Neuro Nexus probe, where the chip can achieve an 8× compression ratio with ∼3% average reconstruction error, consuming 144nW per channel at a 0.5V power supply.
Original language | English (US) |
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Title of host publication | Proceedings - 2016 IEEE Biomedical Circuits and Systems Conference, BioCAS 2016 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 192-195 |
Number of pages | 4 |
ISBN (Electronic) | 9781509029594 |
DOIs | |
State | Published - 2016 |
Event | 12th IEEE Biomedical Circuits and Systems Conference, BioCAS 2016 - Shanghai, China Duration: Oct 17 2016 → Oct 19 2016 |
Publication series
Name | Proceedings - 2016 IEEE Biomedical Circuits and Systems Conference, BioCAS 2016 |
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Other
Other | 12th IEEE Biomedical Circuits and Systems Conference, BioCAS 2016 |
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Country/Territory | China |
City | Shanghai |
Period | 10/17/16 → 10/19/16 |
Bibliographical note
Publisher Copyright:© 2016 IEEE.