Evidence map›Paper›PMID 37514552›Full record

ArticleSensors (Basel, Switzerland)2023

Exploring Teslasuit's Potential in Detecting Sequential Slip-Induced Kinematic Changes among Healthy Young Adults.

Jacob Hepp, Michael Shiraishi, Michelle Tran, Emmy Henson, Mira Ananthanarayanan, Rahul Soangra

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Jacob HeppCrean College of Health and Behavioral Sciences, Chapman University, Orange, CA 92866, USA.
Michael ShiraishiCrean College of Health and Behavioral Sciences, Chapman University, Orange, CA 92866, USA.
Michelle TranCrean College of Health and Behavioral Sciences, Chapman University, Orange, CA 92866, USA.
Emmy HensonCrean College of Health and Behavioral Sciences, Chapman University, Orange, CA 92866, USA.
Mira AnanthanarayananCrean College of Health and Behavioral Sciences, Chapman University, Orange, CA 92866, USA.
Rahul SoangraCrean College of Health and Behavioral Sciences, Chapman University, Orange, CA 92866, USA.ORCID 0000-0001-9836-1549

Funding

AI-based Fall-Risk Assessment during Daily Activities in Post Stroke Survivors using SmartphonesR15HD110941 · NICHD · CHAPMAN UNIVERSITY · PI SOANGRA, RAHUL · 2023 to 2023
$391k
Eunice Kennedy Shriver National Institute of Child Health and Human Development 1R15HD110941-01NICHD NIH HHS R15 HD110941
6 · The paper itself

Abstract

This study aimed to assess whether the Teslasuit, a wearable motion-sensing technology, could detect subtle changes in gait following slip perturbations comparable to an infrared motion capture system. A total of 12 participants wore Teslasuits equipped with inertial measurement units (IMUs) and reflective markers. The experiments were conducted using the Motek GRAIL system, which allowed for accurate timing of slip perturbations during heel strikes. The data from Teslasuit and camera systems were analyzed using statistical parameter mapping (SPM) to compare gait patterns from the two systems and before and after slip. We found significant changes in ankle angles and moments before and after slip perturbations. We also found that step width significantly increased after slip perturbations (

Indexed as

GaitWalkingAnkle JointBiomechanical PhenomenaHumansLower ExtremityYoung Adultfall riskgait kinematicsperturbation trainingwearable technologies

Identifiers

PMID37514552
PMCPMC10383312

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.