Removal of respiratory influences from heart rate during emotional stress

Carolina Varon, Jesús Lázaro, Alberto Hernando, Alexander Caicedo, Sabine Van Huffel, Raquel Bailón

Resultado de la investigación: Contribución a una revistaArtículo de la conferenciarevisión exhaustiva

Resumen

Heart rate variability (HRV) has been proposed as an indicator of stress. However, respiratory changes affect the spectral content of the HRV, resulting in a misleading estimation of stress, especially when the respiratory rate falls into the classical low frequency band. To overcome this limitation of the classical HRV analysis, this study decomposes the HRV signal, recorded during different phases of acute emotional stress, into two components using orthogonal subspace projections (OSP). One component describes all linear respiratory influences, and the other one contains all residual HRV dynamics. Two subspace definitions are compared here, on the one hand, the original respiration signal, and on the other hand, its wavelet decomposition. After a multicomparison test, no difference was found between the respiratory components derived using both subspaces, hence, no added value is achieved by the wavelet decomposition. Furthermore, the HRV variations that are linearly related to respiration are significantly different (p < 0.008) between relax and emotional stress. This suggests that respiratory dynamics are enough to detect emotional stress, which might result in an improved assessment of stress.

Idioma originalInglés estadounidense
Páginas (desde-hasta)1-4
Número de páginas4
PublicaciónComputing in Cardiology
Volumen44
DOI
EstadoPublicada - 2017
Publicado de forma externa
Evento44th Computing in Cardiology Conference, CinC 2017 - Rennes, Francia
Duración: sept. 24 2017sept. 27 2017

Áreas temáticas de ASJC Scopus

  • Informática (todo)
  • Cardiología y medicina cardiovascular

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