Track My Health: An IoT Approach for Data Acquisition and Activity Recognition...pHealth 2020, Proceedings of the 17th International Conference on Wearable Micro and Nano Technologies for Personalized Health, September 14-16, 2020.
Human Activity Recognition (HAR) is an arisen research topic because of its usage of self-care and prevention issues. In our days, the advances of technology (smart-phones, smart-watches, tablets, wristbands) and achievements of Machine Learning provide great opportunities for in-depth research on H...
| Publicado en: | Studies in Health Technology & Informatics Vol. 273; pp. 266 - 272 |
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| Autores principales: | , , , |
| Formato: | pictorial proceedings tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=145735358&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 145735358 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09269630 U1V jtl: Studies in Health Technology & Informatics issn: 09269630 maglogo: N pubinfo: dt: 2020 vid: 273 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 145735358 145735358 145735358 10.3233/SHTI200654 145735358 ppf: 266 ppct: 6 formats: tig: atl: Track My Health: An IoT Approach for Data Acquisition and Activity Recognition...pHealth 2020, Proceedings of the 17th International Conference on Wearable Micro and Nano Technologies for Personalized Health, September 14-16, 2020. aug: au: BOTILIAS, Giannis PAPOUTSIS, Angelos KARVELIS, Petros STYLIOS, Chrysostomos affil: Laboratory of Knowledge and Intelligent Computing, Department of Informatics and Telecommunications, University of Ioannina, Kostakioi, 47150 Arta, Greece sug: subj: Physical Activity Data Collection Monitoring, Physiologic Machine Learning Health Status Internet of Things Self Care Wearable Sensors Mobile Applications Home Environment Congresses and Conferences ab: Human Activity Recognition (HAR) is an arisen research topic because of its usage of self-care and prevention issues. In our days, the advances of technology (smart-phones, smart-watches, tablets, wristbands) and achievements of Machine Learning provide great opportunities for in-depth research on HAR. Technological gadgets include many sensors that gather various, which in turn are input to machine learning techniques to derive useful information and results about human activities and health conditions. Activity Recognition is mainly based physical sensors attached to the human body, with wearable devices coming with built-in sensors such as the accelerometer, gyroscope. This work presents a system based on the Internet of Things (IoT), that monitoring essential vital signals. A mobile application has designed and developed to collect data from a wearable device with built-in sensors (accelerometer and gyroscope) for different human activities and store them for use in a database. The purpose of this work is to present the module of the system that is responsible for the data acquisition, processing and storage of signals that will feed then the Machine Learning module to identify the human health status. pubtype: Academic Journal doctype: pictorial proceedings tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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