Evidence map›Paper›PMID 32290639›Full record

ReviewSensors (Basel, Switzerland)2020

Physiological and Behavior Monitoring Systems for Smart Healthcare Environments: A Review.

Mariana Jacob Rodrigues, Octavian Postolache, Francisco Cercas

Open access · goldAbstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
5.6field-weighted citation impact, top 3% of its field
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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 113 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Wearables and their applications for the rehabilitation of elderly people.Medical & biological engineering & computing · 2022
    Review
  11. Article
  12. Article
  13. Article
  14. Article
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  17. Article
  18. Review
  19. Article
  20. Scenario-based dialogue system based on pause detection toward daily health monitoring.Journal of rehabilitation and assistive technologies engineering
    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

3 authors at 1 institution in 1 country.

Mariana Jacob RodriguesIscte-Instituto Universitário de Lisboa, Av. das Forças Armadas, 1649-026 Lisboa, Portugal.ORCID 0000-0002-9930-5028
Octavian PostolacheIscte-Instituto Universitário de Lisboa, Av. das Forças Armadas, 1649-026 Lisboa, Portugal.
Francisco CercasIscte-Instituto Universitário de Lisboa, Av. das Forças Armadas, 1649-026 Lisboa, Portugal.ORCID 0000-0002-0374-4078
Iscte – Instituto Universitário de Lisboa · PT

Funding

FCT/MCTES -Instituto de Telecomunicações -
6 · The paper itself

Abstract

Healthcare optimization has become increasingly important in the current era, where numerous challenges are posed by population ageing phenomena and the demand for higher quality of the healthcare services. The implementation of Internet of Things (IoT) in the healthcare ecosystem has been one of the best solutions to address these challenges and therefore to prevent and diagnose possible health impairments in people. The remote monitoring of environmental parameters and how they can cause or mediate any disease, and the monitoring of human daily activities and physiological parameters are among the vast applications of IoT in healthcare, which has brought extensive attention of academia and industry. Assisted and smart tailored environments are possible with the implementation of such technologies that bring personal healthcare to any individual, while living in their preferred environments. In this paper we address several requirements for the development of such environments, namely the deployment of physiological signs monitoring systems, daily activity recognition techniques, as well as indoor air quality monitoring solutions. The machine learning methods that are most used in the literature for activity recognition and body motion analysis are also referred. Furthermore, the importance of physical and cognitive training of the elderly population through the implementation of exergames and immersive environments is also addressed.

Indexed as

Delivery of Health CareActivities of Daily LivingAir Pollution, IndoorArtificial IntelligenceHealth StatusHumansInternet of ThingsMonitoring, PhysiologicWireless Technologyactivity recognitionhealthcareindoor air qualityinternet of thingsphysiological signs monitoringsmart environments

Identifiers

PMID32290639
PMCPMC7218909
OpenAlexW3015266960

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.