Feasibility of Tracking Human Kinematics with Simultaneous Localization and Mapping (SLAM).

Sepehr Laal, Paul Vasilyev, Sean Pearson, Mateo Aboy, James McNames

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 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

–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

0 citing papers in PubMed.

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

5 authors.

Sepehr LaalDepartment of Electrical and Computer Engineering, Portland State University, Portland, OR 97201, USA.

Paul VasilyevDepartment of Electrical and Computer Engineering, Portland State University, Portland, OR 97201, USA.

Sean PearsonAPDM Wearable Technologies, Portland, OR 97201, USA.

Mateo AboyCentre for Law, Medicine and Life Sciences, University of Cambridge, Cambridge CB2 1TN, UK.ORCID 0000-0002-5168-4321

James McNamesDepartment of Electrical and Computer Engineering, Portland State University, Portland, OR 97201, USA.ORCID 0000-0001-8091-3560

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We evaluated a new wearable technology that fuses inertial sensors and cameras for tracking human kinematics. These devices use on-board simultaneous localization and mapping (SLAM) algorithms to localize the camera within the environment. Significance of this technology is in its potential to overcome many of the limitations of the other dominant technologies. Our results demonstrate this system often attains an estimated orientation error of less than 1° and a position error of less than 4 cm as compared to a robotic arm. This demonstrates that SLAM's accuracy is adequate for many practical applications for tracking human kinematics.

Indexed as

AlgorithmsBiomechanical PhenomenaHumanscomputer visionkinematicsmotion capturesimultaneous localization and mappingwearable cameras

Identifiers

PMID36502075

DOI10.3390/s22239378

PMCPMC9739070

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.