Acceleration plethysmography to evaluate aging effect in cardiovascular system. Using new criteria of four wave patterns

Med Prog Technol. 1996;21(4):205-10.

Abstract

Acceleration plethysmography (APG) uses the second derivative of the waveform of the digital photoplethysmography to stabilize the baseline and to separate components of the waveform more clearly than the first derivative. The purposes of this study were 1) to investigate the association between APG and aging, using our new criteria of four patterns and 2) to test the clinical usefulness of APG for the prediction of the level of atherosclerosis. The examined subjects were 82 males and 308 females aged 30-69 years. Plethysmograms were recorded in the sitting position. We compared the distribution of four patterns of APG by age group and analyzed the predictor of changing waveforms. We also analyzed the association between wave patterns and the risk factors, i.e. total cholesterol (TC), high density lipoprotein cholesterol, systolic blood pressure, diastolic blood pressure, body mass index, and current smoking status.

The results: -categorized four wave patterns were significantly associated with aging; -pulse pressure (PP), body height and sex influenced waveforms of APG independently of age; and -categorized wave patterns were associated with high serum TC among risk factors for atherosclerosis. Those results suggest that APG reflects the arterial wall properties which change with age and might predict the level of atherosclerosis. To provide further guidance for determining appropriate clinical interpretations of APG, it is required to consider the effects of PP, body height and sex. We conclude that simply categorized wave patterns of APG could be a useful noninvasive tool to evaluate aging in cardiovascular system.

Publication types

  • Clinical Trial
  • Comparative Study
  • Randomized Controlled Trial

MeSH terms

  • Adult
  • Aged
  • Aging / physiology*
  • Arteriosclerosis / diagnosis
  • Body Height
  • Cardiovascular Physiological Phenomena*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Plethysmography / methods*
  • Predictive Value of Tests
  • Regression Analysis
  • Sex Factors
  • Smoking