ArticleInternational Conference on Indoor Positioning and Indoor Navigation : [proceedings]. International Conference on Indoor Positioning and Indoor Navigation2024
Robust Indoor Pedestrian Backtracking Using Magnetic Signatures and Inertial Data.
Article in International Conference on Indoor Positioning and Indoor Navigation : [proceedings]. International Conference on Indoor Positioning and Indoor Navigation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Navigating unfamiliar environments can be challenging for visually impaired individuals due to difficulties in recognizing distant landmarks or visual cues. This work focuses on a particular form of wayfinding, specifically backtracking a previously taken path, which can be useful for blind pedestrians. We propose a hands-free indoor navigation solution using a smartphone without relying on pre-existing maps or external infrastructure. Our hybrid matching method integrates machine learning to enhance positioning accuracy, addressing real-life challenges such as odometry errors or deviations from the correct path. Testing with datasets from visually impaired individuals demonstrates the potential of our approach in providing reliable backtracking assistance.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.