Evidence map›Paper›PMID 39507657›Full record

ArticleFrontiers in public health2024

Wireless sensor network-based health monitoring and smart home assistance for the older adults in sports and wellness towns.

Dapeng Yang, Junqi Wang, Li Huang, Tongling Wang

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Dapeng YangCollege of Physical Education, Huainan Normal University, Huainan, China.
Junqi WangSchool of Physical Education and Sport, Henan University, Kaifeng, China.
Li HuangConservatory of Music, Huainan Normal University, Huainan, China.
Tongling WangInstitute of Physical Education, Huzhou University, Huzhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Integrating technology with rural development is essential for addressing the unique challenges faced by aging populations in rural areas. China's national rural revitalization strategy emphasizes the importance of developing characteristic towns that focus on health and wellness demands, particularly for the older adults. However, there is a gap in the literature regarding the systematic use of technology to support the health and daily living needs of this demographic. Objective: This study aims to bridge this gap by proposing a wireless sensor network (WSN)-based system that integrates health monitoring and smart home assistance, specifically tailored for older adults residents in sports and wellness towns. Methods: The system's design involves collecting and analyzing historical activity data and basic physiological parameters from older adults residents' homes. The data are cleaned, combined and stored to prepare it for behavior analysis, which is vital for controlling smart home equipment. Preliminary health assessments are conducted using the collected physiological data. A hybrid network leveraging Sub-G and Wi-Fi technologies is optimized for the purposes of collecting and uploading data, based on a comparative analysis of wireless communication options. Significance: This study significantly contributes to the advancement of sports and wellness towns by promoting healthy aging through cutting-edge technological solutions.

Indexed as

SportsWireless TechnologyAgedAged, 80 and overChinaFemaleHealth PromotionHome Care ServicesHumansMaleMiddle AgedMonitoring, PhysiologicRural Populationartificial intelligencehealthy aging throughk-means algorithmrural revitalizationsports and wellness town

Identifiers

PMID39507657
PMCPMC11537851

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.