Entropy change of biological dynamics in COPD

Int J Chron Obstruct Pulmon Dis. 2017 Oct 12:12:2997-3005. doi: 10.2147/COPD.S140636. eCollection 2017.

Abstract

In this century, the rapid development of large data storage technologies, mobile network technology, and portable medical devices makes it possible to measure, record, store, and track analysis of large amount of data in human physiological signals. Entropy is a key metric for quantifying the irregularity contained in physiological signals. In this review, we focus on how entropy changes in various physiological signals in COPD. Our review concludes that the entropy change relies on the types of physiological signals under investigation. For major physiological signals related to respiratory diseases, such as airflow, heart rate variability, and gait variability, the entropy of a patient with COPD is lower than that of a healthy person. However, in case of hormone secretion and respiratory sound, the entropy of a patient is higher than that of a healthy person. For mechanomyogram signal, the entropy increases with the increased severity of COPD. This result should give valuable guidance for the use of entropy for physiological signals measured by wearable medical device as well as for further research on entropy in COPD.

Keywords: COPD; entropy; heart rate variability; irregularity; physiological signal; respiratory pattern.

Publication types

  • Review

MeSH terms

  • Entropy
  • Gait*
  • Heart Rate*
  • Hormones / blood
  • Hormones / metabolism*
  • Humans
  • Lung / physiopathology*
  • Pattern Recognition, Automated / methods*
  • Predictive Value of Tests
  • Pressure
  • Prognosis
  • Pulmonary Disease, Chronic Obstructive / blood
  • Pulmonary Disease, Chronic Obstructive / diagnosis*
  • Pulmonary Disease, Chronic Obstructive / physiopathology
  • Respiration
  • Respiratory Muscles / physiopathology
  • Respiratory Sounds
  • Severity of Illness Index
  • Signal Processing, Computer-Assisted*
  • Telemetry / methods*
  • Time Factors

Substances

  • Hormones