Literature DB >> 29866962

Human Activity Recognition Supported on Indoor Localization: A Systematic Review.

Jesús Cerón1, Diego M López1.   

Abstract

PROBLEM: The number of older adults is growing worldwide. This has a social and economic impact in all countries because of the increased number of older adults affected by chronic diseases, health emergencies, and disabilities, representing at the end high cost for the health system. To face this problem, the Ambient Assisted Living (AAL) domain has emerged. Its main objective is to extend the time that older adults can live independently in their homes. AAL is supported by different fields and technologies, being Human Activity Recognition (HAR), control of vital signs and location tracking the three of most interest during the last years.
OBJECTIVE: To perform a systematic review about Human Activity Recognition (HAR) approaches supported on Indoor Localization (IL) and vice versa, describing the methods they have used, the accuracy they have obtained and whether they have been directed towards the AAL domain or not.
METHODS: A systematic review of six databases was carried out (ACM, IEEE Xplore, PubMed, Science Direct and Springer).
RESULTS: 27 papers were found. They were categorised into three groups according their approach: paper focus on 1. HAR, 2. IL, 3. HAR and IL. A detailed analysis of the following factors was performed: type of methods and technologies used for HAR, IL and data fusion, as well as the precision obtained for them.
CONCLUSIONS: This systematic review shows that the relationship between HAR and IL has been very little studied, therefore providing insights of its potential mutual support to provide AAL solutions.

Entities:  

Keywords:  Human Activity Recognition; Indoor Localization; Simultaneous Human Activity Recognition and Indoor Localization

Mesh:

Year:  2018        PMID: 29866962

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  3 in total

1.  Framework for Simultaneous Indoor Localization, Mapping, and Human Activity Recognition in Ambient Assisted Living Scenarios.

Authors:  Jesus D Ceron; Diego M López; Felix Kluge; Bjoern M Eskofier
Journal:  Sensors (Basel)       Date:  2022-04-28       Impact factor: 3.847

2.  Deep Learning-Based Human Activity Real-Time Recognition for Pedestrian Navigation.

Authors:  Junhua Ye; Xin Li; Xiangdong Zhang; Qin Zhang; Wu Chen
Journal:  Sensors (Basel)       Date:  2020-04-30       Impact factor: 3.576

3.  Human Activities and Postures Recognition: From Inertial Measurements to Quaternion-Based Approaches.

Authors:  Makia Zmitri; Hassen Fourati; And Nicolas Vuillerme
Journal:  Sensors (Basel)       Date:  2019-09-20       Impact factor: 3.576

  3 in total

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