title: An automatic method for arterial pulse waveform recognition using KNN and SVM classifiers.
abstract: The measurement and analysis of the arterial pulse waveform (APW) are the means for cardiovascular risk assessment. Optical sensors represent an attractive instrumental solution to APW assessment due to their truly non-contact nature that makes the measurement of the skin surface displacement possible, especially at the carotid artery site. In this work, an automatic method to extract and classify the acquired data of APW signals and noise segments was proposed. Two classifiers were implemented: k-nearest neighbours and support vector machine (SVM), and a comparative study was made, considering widely used performance metrics. This work represents a wide study in feature creation for APW. A pool of 37 features was extracted and split in different subsets: amplitude features, time domain statistics, wavelet features, cross-correlation features and frequency domain statistics. The support vector machine recursive feature elimination was implemented for feature selection in order to identify the most relevant feature. The best result (0.952 accuracy) in discrimination between signals and noise was obtained for the SVM classifier with an optimal feature subset .
authors.affiliation: Physics Department, Instrumentation Center, University of Coimbra, Rua Larga, 3004-516, Coimbra, Portugal. taniapereira@lei.fis.uc.pt.
authors.forename: Tânia
authors.identifier: http://orcid.org/0000-0003-1681-2436
authors.initials: T
authors.lastname: Pereira
authors.affiliation: Physics Department, University of Coimbra, Coimbra, Portugal.
authors.forename: Joana S
authors.initials: JS
authors.lastname: Paiva
authors.affiliation: Physics Department, Instrumentation Center, University of Coimbra, Rua Larga, 3004-516, Coimbra, Portugal.
authors.forename: Carlos
authors.initials: C
authors.lastname: Correia
authors.affiliation: Physics Department, Instrumentation Center, University of Coimbra, Rua Larga, 3004-516, Coimbra, Portugal.
authors.forename: João
authors.initials: J
authors.lastname: Cardoso
mesh_terms: D001158:Arteries; D004867:Equipment Design / Q000295:instrumentation; D006801:Humans; D055095:Optics and Photonics / Q000295:instrumentation* / Q000379:methods; D011674:Pulse / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D060388:Support Vector Machine; D058067:Wavelet Analysis
keywords: Arterial pulse waveform; Feature creation; K-nearest neighbour algorithm; Optical system; Recursive feature elimination; Support vector machine