Evidence map›Paper›PMID 33261064›Full record

ReviewSensors (Basel, Switzerland)2020

On the Challenges and Potential of Using Barometric Sensors to Track Human Activity.

Ajaykumar Manivannan, Wei Chien Benny Chin, Alain Barrat, Roland Bouffanais

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 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.2field-weighted citation impact, top 10% 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

9 citing papers in PubMed, 44 citations in OpenAlex.

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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 at 2 institutions in 3 countries.

Ajaykumar ManivannanEngineering Product Development, Singapore University of Technology and Design, 8 Somapah Road, Singapore 487372, Singapore.ORCID 0000-0002-2860-8195
Wei Chien Benny ChinEngineering Product Development, Singapore University of Technology and Design, 8 Somapah Road, Singapore 487372, Singapore.ORCID 0000-0001-7215-3303
Alain BarratCNRS, CPT, Aix Marseille University, Université de Toulon, 13009 Marseille, France.ORCID 0000-0001-8683-269X
Roland BouffanaisEngineering Product Development, Singapore University of Technology and Design, 8 Somapah Road, Singapore 487372, Singapore.ORCID 0000-0002-2507-4642
Singapore University of Technology and Design · SGTokyo Institute of Technology · JP

Funding

Singapore University of Technology and Design Cities Sector: PIE-SGP-CTRS-1803
6 · The paper itself

Abstract

Barometers are among the oldest engineered sensors. Historically, they have been primarily used either as environmental sensors to measure the atmospheric pressure for weather forecasts or as altimeters for aircrafts. With the advent of microelectromechanical system (MEMS)-based barometers and their systematic embedding in smartphones and wearable devices, a vast breadth of new applications for the use of barometers has emerged. For instance, it is now possible to use barometers in conjunction with other sensors to track and identify a wide range of human activity classes. However, the effectiveness of barometers in the growing field of human activity recognition critically hinges on our understanding of the numerous factors affecting the atmospheric pressure, as well as on the properties of the sensor itself-sensitivity, accuracy, variability, etc. This review article thoroughly details all these factors and presents a comprehensive report of the numerous studies dealing with one or more of these factors in the particular framework of human activity tracking and recognition. In addition, we specifically collected some experimental data to illustrate the effects of these factors, which we observed to be in good agreement with the findings in the literature. We conclude this review with some suggestions on some possible future uses of barometric sensors for the specific purpose of tracking human activities.

Indexed as

Micro-Electrical-Mechanical SystemsMonitoring, PhysiologicWearable Electronic DevicesHuman ActivitiesHumansSmartphonebarometerbarometric pressurehuman activity recognition (HAR)vertical displacement activity (VDA)

Identifiers

PMID33261064
PMCPMC7731380
OpenAlexW3110129313

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.