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dc.contributor.authorKoçak, Hilal
dc.contributor.authorÇetin, Gürcan
dc.date.accessioned2021-07-30T10:25:52Z
dc.date.available2021-07-30T10:25:52Z
dc.date.issued2021en_US
dc.identifier.citationKoçak H., Çetin G. (2021) A Deep Learning-Based IoT Implementation for Detection of Patients’ Falls in Hospitals. In: Hemanth J., Yigit T., Patrut B., Angelopoulou A. (eds) Trends in Data Engineering Methods for Intelligent Systems. ICAIAME 2020. Lecture Notes on Data Engineering and Communications Technologies, vol 76. Springer, Cham. https://doi.org/10.1007/978-3-030-79357-9_46en_US
dc.identifier.isbn978-3-030-79357-9
dc.identifier.issn23674512
dc.identifier.urihttps://doi.org/10.1007/978-3-030-79357-9_46
dc.identifier.urihttps://hdl.handle.net/20.500.12809/9441
dc.description.abstractFalls in hospitalized patients are a major problem for patient safety. Accidental falls are one of the most common incidents reported in hospitals. Thanks to the advances in technology, smart solutions can be developed for hospital environments as well as in all areas of life. Wearable devices, context-aware or computer vision-based systems can be designed to detect patients who fall in hospital. Internet of Things (IoT) can also be placed on wearable health products, and gathered sensors data is processed and analyzed with Machine Learning (ML) and Deep Learning (DL) algorithms. Furthermore, some DL algorithms such as LSTM are also applied to the analysis of time-series data. In this study, to minimize damage caused by falls, we’ve proposed a model that can achieve real-time fall detection by applying LSTM based deep learning technique on IoT sensor data. In result of the study, falling detection has been realized with 98% F1-score. Moreover, a mobile application has been successfully developed to inform caregivers about patients’ fall.en_US
dc.item-language.isoengen_US
dc.publisherSpringeren_US
dc.relation.isversionof10.1007/978-3-030-79357-9_46en_US
dc.item-rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDeep learningen_US
dc.subjectLSTMen_US
dc.subjectPatients’ fallen_US
dc.subjectIoTen_US
dc.titleA Deep Learning-Based IoT Implementation for Detection of Patients’ Falls in Hospitalsen_US
dc.item-typebookParten_US
dc.contributor.departmentMÜ, Teknoloji Fakültesi, Bilişim Sistemleri Mühendisliği Bölümüen_US
dc.contributor.authorID0000-0003-2602-8557en_US
dc.contributor.institutionauthorKoçak, Hilal
dc.contributor.institutionauthorÇetin, Gürcan
dc.identifier.volume76en_US
dc.identifier.startpage465en_US
dc.identifier.endpage483en_US
dc.relation.journalLecture Notes on Data Engineering and Communications Technologiesen_US
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US


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