Heart rate variability and respiratory sinus arrhythmia assessment of affective states by bivariate autoregressive spectral analysis

V. Magagnin, M. Mauri, P. Cipresso, L. Mainardi, E. N. Brown, S. Cerutti, M. Villamira, R. Barbieri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The study of emotions elicited by human-computer interactions is a promising field that could lead to the identification of specific patterns of affective states. We present a heart rate variability (HRV) assessment of the autonomic nervous system (ANS) response and respiratory sinus arrhythmia during PC-mediated stimuli by means of standard and multivariate autoregressive spectral methods. 35 healthy volunteers were exposed to computer-mediated tasks during data collection. The stimuli were designed to elicit: relaxation (R), engagement (E) and stress (S); half of the subjects were exposed to E before S (RES) while the other to S before E (RSE). HRV measures clearly separate the ANS response among R, S and E. Less significant differences are found between E and S in RSE, suggesting that S stimuli may cause a lasting response affecting the E period. Results from the bivariate analysis indicate a disruption of the cardio-respiratory coupling during non-relax conditions.

Original languageEnglish
Title of host publicationComputing in Cardiology
Pages145-148
Number of pages4
Volume37
Publication statusPublished - 2010
EventComputing in Cardiology 2010, CinC 2010 - Belfast, United Kingdom
Duration: Sep 26 2010Sep 29 2010

Other

OtherComputing in Cardiology 2010, CinC 2010
CountryUnited Kingdom
CityBelfast
Period9/26/109/29/10

ASJC Scopus subject areas

  • Computer Science Applications
  • Cardiology and Cardiovascular Medicine

Fingerprint Dive into the research topics of 'Heart rate variability and respiratory sinus arrhythmia assessment of affective states by bivariate autoregressive spectral analysis'. Together they form a unique fingerprint.

Cite this