Evidence map›Paper›PMID 35432829›Full record

ArticleJournal of healthcare engineering2022

Augmented Reality-Centered Position Navigation for Wearable Devices with Machine Learning Techniques.

G K Kamalam, Shubham Joshi, Manish Maheshwari, K Senthamil Selvan, Sajjad Shaukat Jamal, S Vairaprakash, Musah Alhassan

Open access · hybridAbstract read
In one paragraph

Article in Journal of healthcare engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.6field-weighted citation impact, top 15% 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

0 citing papers in PubMed, 16 citations in OpenAlex.

No citing paper in PubMed yet.

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

7 authors at 5 institutions in 3 countries.

G K KamalamDepartment of Information Technology, Kongu Engineering College, Perundurai, Erode, Tamil Nadu, India.
Shubham JoshiComputer Engineering, SVKM'S NMIMS MPSTME, Shirpur Campus, Shirpur, India.ORCID 0000-0003-3815-1261
Manish MaheshwariDepartment of Computer Science and Applications, Makhanlal Chaturvedi National University of Journalism and Communication, Bhopal, Madhya Pradesh, India.
K Senthamil SelvanPrince Shri Venkateshwara Padmavathy Engineering College, Chennai, Tamil Nadu, India.
Sajjad Shaukat JamalDepartment of Mathematics, College of Science, King Khalid University, Abha, Saudi Arabia.ORCID 0000-0002-5852-1955
S VairaprakashDepartment of ECE, Ramco Institute of Technology, Rajapalayam, Tamil Nadu, India.
Musah AlhassanUniversity of Development Studies, Electrical Engineering Department, School of Engineering, Nyankpala Campus, Nyankpala, Ghana.ORCID 0000-0001-8640-8768
King Khalid University · SAMakhanlal Chaturvedi National University of Journalism and Communication · INNarsee Monjee Institute of Management Studies · INShri Venkateshwara University · INUniversity for Development Studies · GH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

People have always relied on some form of instrument to assist them to get to their destination, from hand-drawn maps and compasses to technology-based navigation systems. Many individuals these days have a smartphone with them at all times, making it a common part of their routine. Using GPS technology, these cellphones offer applications such as Google Maps that let people find their way around the outside world. Indoor navigation, on the other hand, does not offer the same level of precision. The development of indoor navigation systems is continuously ongoing. Bluetooth, Wi-Fi, RFID, and computer vision are some of the existing technologies used for interior navigation in current systems. In this article, we discuss the shortcomings of current indoor navigation solutions and offer an alternative approach based on augmented reality and ARCore. Navigating an indoor environment is made easier with ARCore, which brings augmented reality to your smartphone or tablet.

Indexed as

Augmented RealityWearable Electronic DevicesHumansMachine LearningSmartphone

Identifiers

PMID35432829
PMCPMC9010156
OpenAlexW4225619931

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.