ICA-based blind source separation (BSS) recovery of the pattern electroretinogram (PERG) from single channel records with poor SNR

IET Conference Publications

Volumn , Issue 520, 2006, Pages 42-

  Fisher, A C ^a   Hagan, R P ^a   Brown, M C ^a   El Deredy, W ^b   Lisboa, P J G ^c  

^a ROYAL LIVERPOOL UNIVERSITY HOSPITAL   (United Kingdom)

^b UNIVERSITY OF MANCHESTER   (United Kingdom)

^c LIVERPOOL JOHN MOORES UNIVERSITY   (United Kingdom)

Author keywords

BSS; Electroretinogram; ICA; Independent component analysis; PERG; Signalrecovery

Indexed keywords

ALGORITHMS; BLIND SOURCE SEPARATION; EYE MOVEMENTS; INDEPENDENT COMPONENT ANALYSIS; MEDICAL COMPUTING; SAMPLING;

PATTERN ELECTRORETINOGRAM (PERG); SIGNAL RECOVERY;

BIOELECTRIC POTENTIALS;

EID: 34047158254     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1049/cp:20060400     Document Type: Conference Paper

References (7)

1. Broomhead DS, King GP. Extracting qualitative data dynamics from experimental data. Physica D. 20 (2-3): 217-236 (1986)
2. Cardoso J-F. Infomax and maximum likelihood for source separation. IEEE Letters on Signal Proc. 4: 112-4 (1997)
3. Hyvärinen A, Karhunen J, and Oja E, Independent Component Analysis. Wiley, New York (2001)
4. James CJ, Hesse CW. Independent component analysis for biomedical signals. Physiol. Meas. 26: 15-39 (2005)
5. James CJ, Lowe D. Extracting multisource brain activity from a single electromagnetic channel. Artif. Intelligence Med. 28: 89-104 (2003)
6. Marmor MF, Holder GE, Porciatti V, et al. Guidelines for basic pattern electroretinography: recommendations by the ISCEV. Doc Ophthalmol 91: 291-298 (1996)
7. Takens F. Detecting strange attractors in turbulence. Lecture Notes in Mathematics. 898: 366-381 (1981)