A pattern assessment of attractors structured by acceleration plethysmogram time series data

Abstract

Our study has specifically addressed scientifically classifying information from a pulse wave. In addition, we have tried classification assessment of disease state so far by applying nonlinear chaotic analysis to acceleration plethysmogram time series data. The present study examines a new analytical method to supplement information that is missed by the recurrence plot method. We report on this new method as we have used it in conventional research.