title: Electrically evoked compound action potentials artefact rejection by independent component analysis: procedure automation.
abstract: BACKGROUND
  Independent-components-analysis (ICA) successfully separated electrically-evoked compound action potentials (ECAPs) from the stimulation artefact and noise (ECAP-ICA, Akhoun et al., 2013).
  
  
  METHODS
  This paper shows how to automate the ECAP-ICA artefact cancellation process. Raw-ECAPs without artefact rejection were consecutively recorded for each stimulation condition from at least 8 intra-cochlear electrodes. Firstly, amplifier-saturated recordings were discarded, and the data from different stimulus conditions (different current-levels) were concatenated temporally. The key aspect of the automation procedure was the sequential deductive source categorisation after ICA was applied with a restriction to 4 sources. The stereotypical aspect of the 4 sources enables their automatic classification as two artefact components, a noise and the sought ECAP based on theoretical and empirical considerations.
  
  
  RESULTS
  The automatic procedure was tested using 8 cochlear implant (CI) users and one to four stimulus electrodes. The artefact and noise sources were successively identified and discarded, leaving the ECAP as the remaining source. The automated ECAP-ICA procedure successfully extracted the correct ECAPs compared to standard clinical forward masking paradigm in 22 out of 26 cases.
  
  
  CONCLUSIONS
  ECAP-ICA does not require extracting the ECAP from a combination of distinct buffers as it is the case with regular methods. It is an alternative that does not have the possible bias of traditional artefact rejections such as alternate-polarity or forward-masking paradigms.
  
  
  CONCLUSIONS
  The ECAP-ICA procedure bears clinical relevance, for example as the artefact rejection sub-module of automated ECAP-threshold detection techniques, which are common features of CI clinical fitting software.
authors.affiliation: School of Psychological Sciences, Faculty of Medical and Human Sciences, The University of Manchester, Manchester, UK; Advanced Bionics European Research Centre, Feodor-Lynen-Strasse, 35, Hanover, Germany. Electronic address: Idrick.akhoun@advancedbionics.com.
authors.forename: Idrick
authors.initials: I
authors.lastname: Akhoun
authors.affiliation: School of Psychological Sciences, Faculty of Medical and Human Sciences, The University of Manchester, Manchester, UK; The Bionics Institute of Australia, 384-388 Albert Street, East Melbourne, Australia.
authors.forename: Colette
authors.initials: C
authors.lastname: McKay
authors.affiliation: School of Psychological Sciences, Faculty of Medical and Human Sciences, The University of Manchester, Manchester, UK.
authors.forename: Wael
authors.initials: W
authors.lastname: El-Deredy
mesh_terms: D000368:Aged; D000669:Amplifiers, Electronic; D016477:Artifacts; D001331:Automation; D001703:Biophysics; D019929:Cochlear Implantation / Q000379:methods; D003638:Deafness / Q000175:diagnosis* / Q000503:physiopathology; D004558:Electric Stimulation; D005072:Evoked Potentials, Auditory / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D025341:Principal Component Analysis
keywords: Artefact; Automation; Cochlear implant; Electrically-evoked compound action potential (ECAP); Forward-masking; Independent component analysis (ICA)