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 Faculty Publications Conference Paper Faculty Publications- Conference Papers 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/. Creator An entity primarily responsible for making the resource Ajesh, F.; Philip, Felix M.; Jims, Anupama; Alapatt, Bosco Paul Title A name given to the resource IOT Wearable Medical Device for Heart Disease Recognition Based ML and DL: A Classification Approach Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems;Volume;1243 LNNS;pp.353-363 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-031-81080-0_32" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-81080-0_32</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105004252580?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105004252580?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Ajesh F., Department of Computer Science and Engineering, Sree Buddha College of Engineering, Kerala, Alappuzha, India; Philip F.M., Department of CS &amp; IT Jain (Deemed-to-be University), Bangalore, India; Jims A., Department of Computer Science and Engineering, CVV Institute of Science and Technology, Kerala, India; Alapatt B.P., CHRIST (Deemed to be University), Delhi-NCR, India Description An account of the resource In the past few years, heart disease has become the foremost worldwide contributor to mortality. This ailment, with a profound effect on the functioning of the heart, leads to issues such as infections in the coronary arteries and diminished blood vessel performance. These complications can culminate in severe unlikely events like heart attacks and strokes. In India alone, approximately one person succumbs to heart disease every minute. To curb the fatalities stemming from cardiac disorders, there is an urgent need for a swift and efficient detection strategy. IoT sensors are utilized in conjunction with Machine Learning (ML) and Deep Learning (DL) techniques to identify heart disease. In this research, we have successfully applied IoT devices and a sensor network to detect heart diseases. This study introduces a medical IoT device designed to gather heart data from patients both before and after the onset of heart disease. This continuously transmitted data is processed using RBF, MLP, and Bi-LSTM models for predicting heart disease. The deep learning approach utilizes past analyses to learn critical features related to heart disease, achieving efficiency in handling complex data. After conducting a series of experiments, we evaluate the systems performance using metrics such as f-measure, sensitivity, specificity, loss function, and Receiver Operating Characteristic (ROC) curves. The HDRBi-LSTM method, in combination with IoT-based analysis, achieves an impressive accuracy rate of 99.5% with minimal time complexity (5 s), effectively reducing heart disease mortality by simplifying the diagnosis of this condition. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. Subject The topic of the resource deep learning; Heart Disease prediction; IoT; long short-term memory; Supervised learning Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-303181079-4; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online