Pani, Danilo and Usai, Francesco and Citi, Luca and Raffo, Luigi (2011) Real-time processing of tfLIFE neural signals on embedded DSP platforms: A case study. In: 5th International IEEE/EMBS Conference on Neural Engineering (NER 2011), 2011-04-27 - 2011-05-01.
Pani, Danilo and Usai, Francesco and Citi, Luca and Raffo, Luigi (2011) Real-time processing of tfLIFE neural signals on embedded DSP platforms: A case study. In: 5th International IEEE/EMBS Conference on Neural Engineering (NER 2011), 2011-04-27 - 2011-05-01.
Pani, Danilo and Usai, Francesco and Citi, Luca and Raffo, Luigi (2011) Real-time processing of tfLIFE neural signals on embedded DSP platforms: A case study. In: 5th International IEEE/EMBS Conference on Neural Engineering (NER 2011), 2011-04-27 - 2011-05-01.
Abstract
Spike sorting is a typical neural processing technique aimed at identifying the firing activity of individual neurons. It plays a different role in the processing of the signals coming either from a single electrode or an electrode array. In presence of highly noisy recordings, a preliminary denoising stage is required in order to improve the SNR. Despite the significant number of studies in the field, only a few of them deal with peripheral nervous system (PNS) recordings and often the possibility of a real-time implementation is only hinted without any real implementation study. In this paper, a real-time PNS signal processing and classification technique is presented end evaluated on real elec-troneurographic signals taken from the sciatic nerve of rats. A state-of-the-art algorithm, composed of a wavelet denoising preprocessing stage followed by a correlation-based spike sorting and a support vector machine, has been adapted to work on-line in order to improve the processing efficiency while preserving at the most its effectiveness. The algorithm provides some level of adaptiveness with respect to an off-line implementation. On average, the correct classification reach 92.24% with isolated errors that can be easily filtered out. Cycle-accurate profiling results on an off-the-shelf Digital Signal Processor demonstrate the real-time performance. © 2011 IEEE.
Item Type: | Conference or Workshop Item (Paper) |
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Additional Information: | Published proceedings: 2011 5th International IEEE/EMBS Conference on Neural Engineering, NER 2011 |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 04 Mar 2014 15:05 |
Last Modified: | 30 Oct 2024 17:08 |
URI: | http://repository.essex.ac.uk/id/eprint/8818 |