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Denoising and compression of intracortical signals with a modified MDL criterion |
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| Authors: | Elias S. G. Carotti Vahid Shalchyan Winnie Jensen Dario Farina |
| Affiliation: | 1. Dipartimento di Automatica ed Informatica, Politecnico di Torino, Turin, Italy 2. Department of Biomedical Engineering, Faculty of Electrical Engineering, Iran University of Science and Technology (IUST), Tehran, Iran 4. Department of Neurorehabilitation Engineering, Bernstein Focus Neurotechnology G?ttingen, Bernstein Center for Computational Neuroscience, University Medical Center G?ttingen, Georg-August University, Von-Siebold-Str. 4, 37075, G?ttingen, Germany 3. Center for Sensory-Motor Interaction, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark |
| Abstract: | Intracortical signals are usually affected by high levels of noise [0 dB signal-to-noise ratio (SNR) is not uncommon] often due to magnetic or electrical coupling between surrounding sources and the recording system. Apart from hindering effective exploitation of the information content in the signals, noise also influences the bandwidth needed to transmit them, which is a problem especially when a large number of channels are to be recorded. In this paper, we propose a novel technique for joint denoising and compression of intracortical signals based on the minimum description length principle. This method was tested on both simulated and experimental signals, and the results showed that the proposed technique achieves improvements in SNR and compression ratios greater than alternative denoising/compression methods. |
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