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Content Provider | IEEE Xplore Digital Library |
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Author | Gehring, T.V. Vasilaki, E. Giugliano, M. |
Copyright Year | 2015 |
Description | Author affiliation: Dept. of Comput. Sci., Univ. of Sheffield, Sheffield, UK (Gehring, T.V.; Vasilaki, E.; Giugliano, M.) |
Abstract | Technological advances of Multielectrode Arrays (MEAs) used for multisite, parallel electrophysiological recordings, lead to an ever increasing amount of raw data being generated. Arrays with hundreds up to a few thousands of electrodes are slowly seeing widespread use and the expectation is that more sophisticated arrays will become available in the near future. In order to process the large data volumes resulting from MEA recordings there is a pressing need for new software tools able to process many data channels in parallel. Here we present a new tool for processing MEA data recordings that makes use of new programming paradigms and recent technology developments to unleash the power of modern highly parallel hardware, such as multi-core CPUs with vector instruction sets or GPGPUs. Our tool builds on and complements existing MEA data analysis packages. It shows high scalability and can be used to speed up some performance critical pre-processing steps such as data filtering and spike detection, helping to make the analysis of larger data sets tractable. |
Starting Page | 4178 |
Ending Page | 4181 |
File Size | 587705 |
Page Count | 4 |
File Format | |
ISSN | 1557170X |
e-ISBN | 9781424492718 |
DOI | 10.1109/EMBC.2015.7319315 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2015-08-25 |
Publisher Place | Italy |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Hardware Runtime Programming Kernel Arrays Standards |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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