Literature DB >> 24638879

Denoising and compression of intracortical signals with a modified MDL criterion.

Elias S G Carotti1, Vahid Shalchyan, Winnie Jensen, Dario Farina.   

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.

Mesh:

Year:  2014        PMID: 24638879     DOI: 10.1007/s11517-014-1146-x

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  18 in total

1.  Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering.

Authors:  R Quian Quiroga; Z Nadasdy; Y Ben-Shaul
Journal:  Neural Comput       Date:  2004-08       Impact factor: 2.026

2.  Wireless transmission of neural signals using entropy and mutual information compression.

Authors:  Stefan Craciun; David Cheney; Karl Gugel; Justin C Sanchez; Jose C Principe
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2010-09-02       Impact factor: 3.802

3.  An integrated system for multichannel neuronal recording with spike/LFP separation, integrated A/D conversion and threshold detection.

Authors:  Yevgeny Perelman; Ran Ginosar
Journal:  IEEE Trans Biomed Eng       Date:  2007-01       Impact factor: 4.538

4.  Optimal wavelets for biomedical signal compression.

Authors:  Mogens Nielsen; Ernest Nlandu Kamavuako; Michael Midtgaard Andersen; Marie-Françoise Lucas; Dario Farina
Journal:  Med Biol Eng Comput       Date:  2006-06-13       Impact factor: 2.602

5.  A systems approach for data compression and latency reduction in cortically controlled brain machine interfaces.

Authors:  Karim G Oweiss
Journal:  IEEE Trans Biomed Eng       Date:  2006-07       Impact factor: 4.538

6.  A 128-channel 6 mW wireless neural recording IC with spike feature extraction and UWB transmitter.

Authors:  Moo Sung Chae; Zhi Yang; Mehmet R Yuce; Linh Hoang; Wentai Liu
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2009-05-08       Impact factor: 3.802

7.  Compression of biomedical signals with mother wavelet optimization and best-basis wavelet packet selection.

Authors:  Laurent Brechet; Marie-Françoise Lucas; Christian Doncarli; Dario Farina
Journal:  IEEE Trans Biomed Eng       Date:  2007-12       Impact factor: 4.538

8.  Low power and high accuracy spike sorting microprocessor with on-line interpolation and re-alignment in 90 nm CMOS process.

Authors:  Tung-Chien Chen; Tsung-Chuan Ma; Yun-Yu Chen; Liang-Gee Chen
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2012

9.  Bridging the brain to the world: a perspective on neural interface systems.

Authors:  John P Donoghue
Journal:  Neuron       Date:  2008-11-06       Impact factor: 17.173

10.  A fully implantable 96-channel neural data acquisition system.

Authors:  Michael Rizk; Chad A Bossetti; Thomas A Jochum; Stephen H Callender; Miguel A L Nicolelis; Dennis A Turner; Patrick D Wolf
Journal:  J Neural Eng       Date:  2009-03-02       Impact factor: 5.379

View more
  1 in total

1.  Capturing spike train temporal pattern with wavelet average coefficient for brain machine interface.

Authors:  Shixian Wen; Allen Yin; Po-He Tseng; Laurent Itti; Mikhail A Lebedev; Miguel Nicolelis
Journal:  Sci Rep       Date:  2021-09-24       Impact factor: 4.379

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.