title: A cardiorespiratory classifier of voluntary and involuntary electrodermal activity.
abstract: BACKGROUND
  Electrodermal reactions (EDRs) can be attributed to many origins, including spontaneous fluctuations of electrodermal activity (EDA) and stimuli such as deep inspirations, voluntary mental activity and startling events. In fields that use EDA as a measure of psychophysiological state, the fact that EDRs may be elicited from many different stimuli is often ignored. This study attempts to classify observed EDRs as voluntary (i.e., generated from intentional respiratory or mental activity) or involuntary (i.e., generated from startling events or spontaneous electrodermal fluctuations).
  
  
  METHODS
  Eight able-bodied participants were subjected to conditions that would cause a change in EDA: music imagery, startling noises, and deep inspirations. A user-centered cardiorespiratory classifier consisting of 1) an EDR detector, 2) a respiratory filter and 3) a cardiorespiratory filter was developed to automatically detect a participant's EDRs and to classify the origin of their stimulation as voluntary or involuntary.
  
  
  RESULTS
  Detected EDRs were classified with a positive predictive value of 78%, a negative predictive value of 81% and an overall accuracy of 78%. Without the classifier, EDRs could only be correctly attributed as voluntary or involuntary with an accuracy of 50%.
  
  
  CONCLUSIONS
  The proposed classifier may enable investigators to form more accurate interpretations of electrodermal activity as a measure of an individual's psychophysiological state.
authors.affiliation: Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada. stefanie.blain@utoronto.ca
authors.forename: Stefanie
authors.initials: S
authors.lastname: Blain
authors.forename: Sarah D
authors.initials: SD
authors.lastname: Power
authors.forename: Ervin
authors.initials: E
authors.lastname: Sejdic
authors.forename: Alex
authors.initials: A
authors.lastname: Mihailidis
authors.forename: Tom
authors.initials: T
authors.lastname: Chau
mesh_terms: D000328:Adult; D001794:Blood Pressure / Q000502:physiology*; D001810:Blood Volume / Q000502:physiology*; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D005712:Galvanic Skin Response / Q000502:physiology*; D006801:Humans; D008297:Male; D008954:Models, Biological; D012018:Reflex / Q000502:physiology*; D015203:Reproducibility of Results; D015656:Respiratory Mechanics / Q000502:physiology*; D012680:Sensitivity and Specificity; D014836:Volition / Q000502:physiology*