International Journal of Engineering, Science and Mathematics
  • Year: 2018
  • Volume: 7
  • Issue: 5

Adaptive fuzzy rule based pulsewaveformsegmentation and artifact detection

  • Author:
  • L. Aleesha Livingston1, M. Kirubha2
  • Total Page Count: 7
  • Page Number: 113 to 119

1Assistant Professsor, Dept. of ECE, Bethlahem Institute of Engineering, Karungal, Kanyakumari Dist., Tamil Nadu

2II ME Applied Electronics, Dept. of ECE, Bethlahem Institute of Engineering, Karungal, Kanyakumari Dist., Tamil Nadu

Online published on 4 May, 2019.

Abstract

A photoplethysmogram (PPG) is an optically obtained plethysmogram, a volumetric measurement of an organ. A PPG is often obtained by using a pulse oximeter which illuminates the skin and measures changes in light absorption. It is a non-invasive, electro-optical method that provides information about the volume of blood flowing in a test region close to the skin of body. In the proposed method an adaptive fuzzy rule based pulse wave segmentation and artifact detection is used. The existing method had low detection accuracy so to overcomethese problem adaptive fuzzy rule is used. The definition of the fuzzy rule is the single most important and challenging aspect of fuzzy rule its effectiveness is vital to the overall performance. Fuzzy-rule-based modeling has become an active research field in recent years because of its uniquemerits in solving complex nonlinear system identification and control problems. When using a fuzzy model to approximate an unknown system, it is desired that the model include many rules so that it can cover the input-output state space of the system with sufficient patches, yet it is also desired that the model include as few rules as possible because the generalizing ability of the model decreases as the number of rules increases. When we speak here of generalization we are referring to the system's mean performance in terms of approximation accuracy evaluated over some independent test data set. Experimental result show high detection accuracy compared to existing method.

Keywords

Photoplethysmogram (PPG), Artifact, Pattern Recognition, Medical inference, Contour Analysis