Extracting new information from old waveforms: Symmetric Projection Attractor Reconstruction - where maths meets medicine: Symmetric Projection Attractor Reconstruction

Manasi Nandi, Philip Aston

Research output: Contribution to journalArticlepeer-review

Abstract

Periodic physiological waveform data, such as blood pressure, pulse oximetry and ECG, are routinely sampled between 100 and 1000 Hz in preclinical research and in the clinical setting from a wide variety of implantable, bedside and wearable monitoring devices. Despite the underlying numerical waveform data being captured at such high fidelity, conventional analysis tends to reside in reporting only averages of minimum, maximum, amplitude and rate, as single point averages. Although these averages are undoubtedly of value, simplification of the data in this
way means that most of the available numerical data are discarded. In turn, this may lead to subtle physiological changes being missed when investigating the cardiovascular system over time. We have developed a mathematical method (symmetric projection attractor reconstruction) that
uses all the numerical data, replotting and revisualizing them in a manner that allows unique quantification of multiple changes in waveform morphology and variability. We propose that the additional quantification of these features will allow the complex behaviour of the cardiovascular
system to be mapped more sensitively in different physiological and pathophysiological settings
Original languageEnglish
Article numberTBC
Pages (from-to)TBC
JournalExperimental Physiology
VolumeTBC
Issue numberTBC
Publication statusAccepted/In press - 23 Apr 2020

Keywords

  • arterial pulse
  • waveform variability
  • attractor reconstruction,
  • Heart rate variability
  • Data Science
  • waveform morphology
  • decision support tools

Fingerprint

Dive into the research topics of 'Extracting new information from old waveforms: Symmetric Projection Attractor Reconstruction - where maths meets medicine: Symmetric Projection Attractor Reconstruction'. Together they form a unique fingerprint.

Cite this