Real‐time brain stroke detection through a learning‐by‐examples technique—An experimental assessment. Issue 11 (November 2017)

• Record Type: Journal Article
• Authors: Salucci, Marco; Vrba, Jan; Merunka, Ilja; Massa, Andrea
• Is Part Of: Microwave and optical technology letters. Volume 59:Issue 11(2017:Nov.)
• Page Start: 2796
• Page End: 2799
• Publication Date: 2017-11
• Subjects: brain stroke detection -- experimental validation -- learning‐by‐examples -- support vector machines; Microwaves -- Periodicals; Optics -- Periodicals; 621
• DOI: 10.1002/mop.30821
• Languages: English
• ISSNs: 0895-2477

Abstract

Abstract: The real‐time detection of brain strokes is addressed within the Learning‐by‐Examples (LBE) framework. Starting from scattering measurements at microwave regime, a support vector machine ( SVM ) is exploited to build a robust decision function able to infer in real‐time whether a stroke is present or not in the patient head. The proposed approach is validated in a laboratory‐controlled environment by considering experimental measurements for both training and testing SVM phases. The obtained results prove that a very high detection accuracy can be yielded even though using a limited amount of training data.