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Collection and analysis of physiological data in smart environments: a systematic mapping.

Authors :
Aranda, Jorge Arthur Schneider
Dias, Lucas Pfeiffer Salomão
Barbosa, Jorge Luis Victória
de Carvalho, Juliano Varella
Tavares, João Elison da Rosa
Tavares, Mauricio Campelo
Source :
Journal of Ambient Intelligence & Humanized Computing; Jul2020, Vol. 11 Issue 7, p2883-2897, 15p
Publication Year :
2020

Abstract

In a world with an increasing population, an alternative for aiding healthcare systems is the use of sensors and wearable devices for monitoring patient physiological data. The analysis of collected data can help guide health services or the self-care of patients. This paper explores literature related to the collection and analysis of physiological data in smart environments by means of a systematic mapping study, organized in three steps: (1) identification of research questions; (2) elaboration of the search process; (3) definition of the criteria for filtering results. Papers were added using the snowball sampling method. This work encompassed 5870 papers published in the past 11 years, up to April 2019. The final selection resulted in 32 papers. Among these, 25 works collected cardiac data, 23 used Wi-Fi, Bluetooth, GSM, or ZigBee technologies, and 14 used techniques for the analysis of physiological data. Mapping verified the more prevalent trends and technologies in the collected and analyzed physiological data from smart environments. The filtering process allowed for a focus on communication technologies and vital sign data types. Three general questions (GQ), two specific questions (SQ), and two statistical questions (STQ) were answered. Similar reviews have already been conducted focusing on sensors, rather than collecting techniques and physiological data analysis. This denotes an opportunity for further studies in the vital sign analysis area. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18685137
Volume :
11
Issue :
7
Database :
Complementary Index
Journal :
Journal of Ambient Intelligence & Humanized Computing
Publication Type :
Academic Journal
Accession number :
143875058
Full Text :
https://doi.org/10.1007/s12652-019-01409-9