Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource IoT and wearables for detection of COVID-19 diagnosis using fusion-based feature extraction with multikernel extreme learning machine Subject The topic of the resource COVID-19; Deep Learning; Feature Extraction; Fusion model; Radiological Images Description An account of the resource Presently, wearables act as a vital part of healthcare sector and they are able to offer exclusive perceptions about the person's health conditions. In contrast to traditional diagnosis in a hospital environment, wearables can give unrestricted access to real-time physiological data. COVID-19 epidemic is increasing at a faster rate with limited test kits. Hence, it becomes essential to develop a novel COVID-19 diagnostic model. Numerous studies were based on the utilization of artificial intelligence techniques on radiological images to precisely identify the disease. This chapter presents an efficient fusion-based feature extraction with multikernel extreme learning machine (FFE-MKELM) for COVID-19 diagnosis using internet of things (IoT) and wearables. Primarily, the wearables and IoT are used to capture the radiological images of the patient. The presented FFE-MKELM model incorporates Gaussian filtering based preprocessing for removing the noise that exists in the radiological image. Besides, directional local extreme patterns with deep features based on Inception v4 model are applied for the FFE process. In addition, MKELM model is utilized as a classification model to determine the appropriate class label of the input radiological images. Moreover, monarch butterfly optimization algorithm is applied to fine tune the parameters involved in the MKELM model. Experimental validation of the FFE-MKELM model is performed against benchmark dataset and the outcomes are inspected under different measures. The resultant simulation outcome ensured the betterment of the FFE-MKELM method by demonstrating an increased sensitivity of 97.34%, specificity of 97.26%, accuracy of 97.14%, and F-measure of 97.01%. 2022 Elsevier Inc. All rights reserved. Creator An entity primarily responsible for making the resource Ganesh Kumar R.; Toomula S.; Paulraj D.; Jebin Bose S.; Bikku T.; Sivabalaselvamani D. Source A related resource from which the described resource is derived Wearable Telemedicine Technology for the Healthcare Industry: Product Design and Development, pp. 137-152. Publisher An entity responsible for making the resource available Elsevier Date A point or period of time associated with an event in the lifecycle of the resource 2021-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/B978-0-323-85854-0.00008-3" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/B978-0-323-85854-0.00008-3</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127957821&amp;doi=10.1016%2FB978-0-323-85854-0.00008-3&amp;partnerID=40&amp;md5=ff173f59d33519a0fc67527e8e08a462" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127957821&amp;doi=10.1016%2fB978-0-323-85854-0.00008-3&amp;partnerID=40&amp;md5=ff173f59d33519a0fc67527e8e08a462</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-032385810-6; 978-032385854-0 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Ganesh Kumar R., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST, Bangalore, Karnataka, India; Toomula S., Department of Computer Science, RBVRR Women's College, Hyderabad, TELANGANA, India; Paulraj D., Department of CSE, RMK College of Engineering and Technology (RMKCET), Thiruvallur, Tamil Nadu, India; Jebin Bose S., Noorul Islam Centre for Higher Education, Kumaracoil, Tamil Nadu, India; Bikku T., Computer Science and Engineering, Vignan's Nirula Institute of Technology and Science for Women, Guntur, Andhra Pradesh, India; Sivabalaselvamani D., Department of Computer Applications, Kongu Engineering College, Erode, Tamil Nadu, India