Kinematic signature of high risk labored breathing revealed by novel signal analysis

Sci Rep. 2024 Nov 13;14(1):27794. doi: 10.1038/s41598-024-77778-9.

Abstract

Breathing patterns (respiratory kinematics) contain vital prognostic information. This dimension of physiology is not captured by conventional vital signs. We sought to determine the feasibility and utility of quantifying respiratory kinematics. Using inertial sensors, we analyzed upper rib, lower rib, and abdominal motion of 108 patients with respiratory symptoms during a hospital encounter (582 two-minute recordings). We extracted 34 features based on an explainable correspondence with well-established breathing patterns. K-means clustering revealed that respiratory kinematics had three dimensions apart from the respiratory rate. We represented these dimensions using respiratory rate variability, respiratory alternans (rib-predominant breaths alternating with abdomen-predominant ones), and recruitment of accessory muscles (increased upper rib excursion). Latent profile analysis of the kinematic measures revealed two profiles consistent with the established clinical constructs of labored and unlabored breathing. In logistic regression, the labored breathing profile improved model discrimination for critical illness beyond the Sequential Organ Failure Assessment (SOFA) score (AUROC 0.77 v/s 0.72; p = 0.02). These findings quantitatively confirm the prior understanding that the respiratory rate alone does not adequately represent the complexity of respiratory kinematics; they demonstrate that high-dimensional signatures of labored breathing can be quantified in routine practice settings, and they can improve predictions of clinical deterioration.

Keywords: Biomedical Engineering; Early Warning Scores; Physiological Monitoring; Respiratory Failure; Work of Breathing.

MeSH terms

  • Adult
  • Aged
  • Biomechanical Phenomena
  • Female
  • Humans
  • Male
  • Middle Aged
  • Respiration*
  • Respiratory Mechanics / physiology
  • Respiratory Rate / physiology
  • Signal Processing, Computer-Assisted