title: Nonlinear Heart Rate Variability features for real-life stress detection. Case study: students under stress due to university examination.
abstract: BACKGROUND
  This study investigates the variations of Heart Rate Variability (HRV) due to a real-life stressor and proposes a classifier based on nonlinear features of HRV for automatic stress detection.
  
  
  METHODS
  42 students volunteered to participate to the study about HRV and stress. For each student, two recordings were performed: one during an on-going university examination, assumed as a real-life stressor, and one after holidays. Nonlinear analysis of HRV was performed by using Poincaré Plot, Approximate Entropy, Correlation dimension, Detrended Fluctuation Analysis, Recurrence Plot. For statistical comparison, we adopted the Wilcoxon Signed Rank test and for development of a classifier we adopted the Linear Discriminant Analysis (LDA).
  
  
  RESULTS
  Almost all HRV features measuring heart rate complexity were significantly decreased in the stress session. LDA generated a simple classifier based on the two Poincaré Plot parameters and Approximate Entropy, which enables stress detection with a total classification accuracy, a sensitivity and a specificity rate of 90%, 86%, and 95% respectively.
  
  
  CONCLUSIONS
  The results of the current study suggest that nonlinear HRV analysis using short term ECG recording could be effective in automatically detecting real-life stress condition, such as a university examination.
authors: Department of Biomedical, Electronic and Telecommunication Engineering, University of Naples "Federico II", Via Claudio 21, Naples, Italy. paolo.melillo@unina.it
authors: Paolo
authors: P
authors: Melillo
authors: Marcello
authors: M
authors: Bracale
authors: Leandro
authors: L
authors: Pecchia
mesh_terms: D004521:Educational Measurement; D006339:Heart Rate; D006801:Humans; D017711:Nonlinear Dynamics; D013315:Stress, Psychological / Q000145:classification / Q000175:diagnosis* / Q000503:physiopathology*; D013334:Students / Q000523:psychology*; D014495:Universities