Fall detection in older adults with mobile IoT devices and machine learning in the cloud and on the edge-Reference-Cited by-同舟云学术

Fall detection in older adults with mobile IoT devices and machine learning in the cloud and on the edge

Published:2020-10 Issue: Volume:537 Page:132-147
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Mrozek Dariusz^ORCID,Koczur Anna,Małysiak-Mrozek Bożena

Funder

Politechnika Śląska

Microsoft Research

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference50 articles.

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2. Aguiar, B., Rocha, T., Silva, J., Sousa, I., Accelerometer-based fall detection for smartphones, in: 2014 IEEE International Symposium on Medical Measurements and Applications (MeMeA), 2014, pp. 1–6.https://doi.org/10.1109/MeMeA.2014.6860110.

3. Fall classification by machine learning using mobile phones;Albert;PLOS ONE,2012

4. Qos-aware health monitoring system using cloud-based wbans;Almashaqbeh;J. Med. Syst.,2014

5. Design and implementation of a fall monitor system by using a 3-axis accelerometer in a smart phone;Bai;IEEE Trans. Consum. Electron.,2012

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