Detection of type-2 diabetes using characteristics of toe photoplethysmogram by applying support vector machine

• Published in: Biocybernetics and biomedical engineering Vol. 39; no. 1; pp. 38 - 51
• Main Authors: Nirala, Neelamshobha, Periyasamy, R., Singh, Bikesh Kumar, Kumar, Awanish
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.01.2019
• Subjects: Diabetes; Feature selection technique; Photoplethysmogram; Principal component analysis; Second derivative of photoplethysmogram; Support vector machine; Diabetes; Support vector machine; Second derivative of photoplethysmogram; Feature selection technique; Photoplethysmogram; Principal component analysis
• ISSN: 0208-5216
• DOI: 10.1016/j.bbe.2018.09.007

Diabetes mellitus (DM) is one of the most widespread and rapidly growing diseases. With its advancement, DM-related complications are also increasing. We used characteristic features of toe photoplethysmogram for the detection of type-2 DM using support vector machine (SVM). We collected toe PPG sig...