title: Cardiac autonomic changes in middle-aged women: identification based on principal component analysis.
abstract: The purpose of this study was to investigate the application of the principal component analysis (PCA) technique on power spectral density function (PSD) of consecutive normal RR intervals (iRR) aiming at assessing its ability to discriminate healthy women according to age groups: young group (20-25 year-old) and middle-aged group (40-60 year-old). Thirty healthy and non-smoking female volunteers were investigated (13 young [mean ± SD (median): 22·8 ± 0·9 years (23·0)] and 17 Middle-aged [51·7 ± 5·3 years (50·0)]). The iRR sequence was collected during ten minutes, breathing spontaneously, in supine position and in the morning, using a heart rate monitor. After selecting an iRR segment (5 min) with the smallest variance, an auto regressive model was used to estimate the PSD. Five principal component coefficients, extracted from PSD signals, were retained for analysis according to the Mahalanobis distance classifier. A threshold established by logistic regression allowed the separation of the groups with 100% specificity, 83·2% sensitivity and 93·3% total accuracy. The PCA appropriately classified two groups of women in relation to age (young and Middle-aged) based on PSD analysis of consecutive normal RR intervals.
authors.affiliation: Biomedical Engineering Program, COPPE, Federal University of Rio de Janeiro.
authors.forename: Gabriela A
authors.initials: GA
authors.lastname: Trevizani
authors.affiliation: Biomedical Engineering Program, COPPE, Federal University of Rio de Janeiro.
authors.forename: Olivassé
authors.initials: O
authors.lastname: Nasario-Junior
authors.affiliation: Biomedical Engineering Program, COPPE, Federal University of Rio de Janeiro.|Hospital Universitário Pedro Ernesto, State University of Rio de Janeiro.
authors.forename: Paulo R
authors.initials: PR
authors.lastname: Benchimol-Barbosa
authors.affiliation: Faculty of Physioteraphy, Federal University of Juiz de Fora.
authors.forename: Lilian P
authors.initials: LP
authors.lastname: Silva
authors.affiliation: Biomedical Engineering Program, COPPE, Federal University of Rio de Janeiro.
authors.forename: Jurandir
authors.initials: J
authors.lastname: Nadal
mesh_terms: D000328:Adult; D000367:Age Factors; D000375:Aging; D001341:Autonomic Nervous System / Q000502:physiology*; D004562:Electrocardiography / Q000379:methods*; D005260:Female; D064368:Healthy Volunteers; D006321:Heart / Q000294:innervation*; D006339:Heart Rate; D006801:Humans; D008875:Middle Aged; D011237:Predictive Value of Tests; D025341:Principal Component Analysis; D012737:Sex Factors; D012815:Signal Processing, Computer-Assisted; D016683:Supine Position; D013997:Time Factors; D055815:Young Adult
keywords: ageing; heart rate variability; principal component analysis; spectral density function