title: Utilization of second derivative photoplethysmographic features for myocardial infarction classification.
abstract: Myocardial infarction (MI) is a common disease that causes morbidity and mortality. The current tools for diagnosing this disease are improving, but still have some limitations. This study utilised the second derivative of photoplethysmography (SDPPG) features to distinguish MI patients from healthy control subjects. The features include amplitude-derived SDPPG features (pulse height, ratio, jerk) and interval-derived SDPPG features (intervals and relative crest time (RCT)). We evaluated 32 MI patients at Pusat Perubatan Universiti Kebangsaan Malaysia and 32 control subjects (all ages 37-87 years). Statistical analysis revealed that the mean amplitude-derived SDPPG features were higher in MI patients than in control subjects. In contrast, the mean interval-derived SDPPG features were lower in MI patients than in the controls. The classifier model of binary logistic regression (Model 7), showed that the combination of SDPPG features that include the pulse height (d-wave), the intervals of "ab", "ad", "bc", "bd", and "be", and the RCT of "ad/aa" could be used to classify MI patients with 90.6% accuracy, 93.9% sensitivity and 87.5% specificity at a cut-off value of 0.5 compared with the single features model.
authors.affiliation: a Jabatan Kejuruteraan Elektrik, Elektronik dan Sistem, Fakulti Kejuruteraan dan Alam Bina , Universiti Kebangsaan Malaysia , Bangi , Malaysia.
authors.forename: Nurhafizah
authors.initials: N
authors.lastname: Mahri
authors.affiliation: a Jabatan Kejuruteraan Elektrik, Elektronik dan Sistem, Fakulti Kejuruteraan dan Alam Bina , Universiti Kebangsaan Malaysia , Bangi , Malaysia.
authors.forename: Kok Beng
authors.initials: KB
authors.lastname: Gan
authors.affiliation: b Jabatan Kesihatan Masyarakat , Pusat Perubatan Universiti Kebangsaan Malaysia , Cheras , Malaysia.
authors.forename: Rusna
authors.initials: R
authors.lastname: Meswari
authors.affiliation: b Jabatan Kesihatan Masyarakat , Pusat Perubatan Universiti Kebangsaan Malaysia , Cheras , Malaysia.
authors.forename: Mohd Hasni
authors.initials: MH
authors.lastname: Jaafar
authors.affiliation: a Jabatan Kejuruteraan Elektrik, Elektronik dan Sistem, Fakulti Kejuruteraan dan Alam Bina , Universiti Kebangsaan Malaysia , Bangi , Malaysia.
authors.forename: Mohd Alauddin
authors.initials: MA
authors.lastname: Mohd Ali
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D004562:Electrocardiography; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009203:Myocardial Infarction / Q000175:diagnosis*; D017156:Photoplethysmography / Q000379:methods*; D012680:Sensitivity and Specificity
keywords: Photoplethysmography; classification; feature extraction; myocardial infarction; second derivative