title: Acoustical detection of venous stenosis in hemodialysis patients using principal component analysis.
abstract: In this paper, a feature extraction method based on principal component analysis was developed for classification of the vascular access's condition in hemodialysis patients. The assessment of the method was carried out by discriminating between before and after angioplasty sound recordings as well as before angioplasty and reference recordings. The results showed that when before and after angioplasty recordings were compared by patient, the classification agreed with the result of angioplasty procedure. When all the available before and after angioplasty recordings were compared, it was still possible to discriminate them at a good rate. On the other hand, when the reference recordings substituted the after angioplasty recordings, almost a perfect discrimination was achieved.
authors.affiliation: UNI-Asdi-FEC Group, Faculty of Electrical Engineering and Computer Science, National University of Engineering, UNI, Managua, Nicaragua. mmm@eit.lth.se
authors.forename: Marco
authors.initials: M
authors.lastname: Munguia M
authors.forename: Pablo
authors.initials: P
authors.lastname: Vasquez
authors.forename: Elisabeth
authors.initials: E
authors.lastname: Mattsson
authors.forename: Bengt
authors.initials: B
authors.lastname: Mandersson
mesh_terms: D000465:Algorithms; D001166:Arteriovenous Shunt, Surgical / Q000009:adverse effects*; D001314:Auscultation / Q000379:methods*; D003627:Data Interpretation, Statistical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006801:Humans; D025341:Principal Component Analysis; D006435:Renal Dialysis / Q000009:adverse effects*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013018:Sound Spectrography / Q000379:methods*; D020246:Venous Thrombosis / Q000175:diagnosis* / Q000209:etiology*