<p>Physiological systems are inherently complex, driven by non-linear interactions among various subsystems that govern their function across diverse spatiotemporal scales. Understanding this interconnectedness is crucial; in this sense, the structure function enables us to dissect the dynamic intricacies of biological responses. By examining amplitude fluctuations across different timescales, we can gain valuable insights into the variability and adaptability of these vital systems. A structure function serves as an essential tool for uncovering long-term correlations that highlight self-organizing behavior. Additionally, it effectively examines the fractal characteristics of short-term signals influenced by the measurement noise often present in biological data. This paper presents a novel investigation into how various parameters of the structure function of the PhotoPlethysmoGraphic (PPG) signal can serve as reliable physiological biomarkers indicative of an individual’s cardiorespiratory activity level. Preliminary tests on 40 students from the Universidad Politécnica de Madrid (UPM), all young and healthy individuals aged between 19 and 30, yielded promising results. These findings enhance our understanding of PPG signal dynamics from a physiological standpoint and provide a procedural framework for real-time patient monitoring and health assessment in clinical environments.</p>

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Structure function in photoplethysmographic signal dynamics for physiological assessment

  • Javier de Pedro-Carracedo,
  • David Fuentes-Jimenez,
  • María Fernanda Cabrera-Umpiérrez,
  • Ana Pilar González-Marcos

摘要

Physiological systems are inherently complex, driven by non-linear interactions among various subsystems that govern their function across diverse spatiotemporal scales. Understanding this interconnectedness is crucial; in this sense, the structure function enables us to dissect the dynamic intricacies of biological responses. By examining amplitude fluctuations across different timescales, we can gain valuable insights into the variability and adaptability of these vital systems. A structure function serves as an essential tool for uncovering long-term correlations that highlight self-organizing behavior. Additionally, it effectively examines the fractal characteristics of short-term signals influenced by the measurement noise often present in biological data. This paper presents a novel investigation into how various parameters of the structure function of the PhotoPlethysmoGraphic (PPG) signal can serve as reliable physiological biomarkers indicative of an individual’s cardiorespiratory activity level. Preliminary tests on 40 students from the Universidad Politécnica de Madrid (UPM), all young and healthy individuals aged between 19 and 30, yielded promising results. These findings enhance our understanding of PPG signal dynamics from a physiological standpoint and provide a procedural framework for real-time patient monitoring and health assessment in clinical environments.