Evidence map›Paper›PMID 39275378›Full record

ArticleSensors (Basel, Switzerland)2024

Balance Assessment Using a Handheld Smartphone with Principal Component Analysis for Anatomical Calibration.

Evan C Anthony, Olivia K Kam, Stephen M Klisch, Scott J Hazelwood, Britta Berg-Johansen

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Evan C AnthonyMechanical Engineering Department, College of Engineering, California Polytechnic State University, San Luis Obispo, CA 93407, USA.
Olivia K KamBiomedical Engineering Department, College of Engineering, California Polytechnic State University, San Luis Obispo, CA 93407, USA.
Stephen M KlischMechanical Engineering Department, College of Engineering, California Polytechnic State University, San Luis Obispo, CA 93407, USA.ORCID 0000-0003-2459-2664
Scott J HazelwoodMechanical Engineering Department, College of Engineering, California Polytechnic State University, San Luis Obispo, CA 93407, USA.ORCID 0000-0003-0990-2839
Britta Berg-JohansenBiomedical Engineering Department, College of Engineering, California Polytechnic State University, San Luis Obispo, CA 93407, USA.ORCID 0009-0002-3595-6996

Funding

Donald E. Bentley Center for Engineering Innovation 2023-2024
6 · The paper itself

Abstract

Most balance assessment studies using inertial measurement units (IMUs) in smartphones use a body strap and assume the alignment of the smartphone with the anatomical axes. To replace the need for a body strap, we have used an anatomical alignment method that employs a calibration maneuver and Principal Component Analysis (PCA) so that the smartphone can be held by the user in a comfortable position. The objectives of this study were to determine if correlations existed between angular velocity scores derived from a handheld smartphone with PCA functional alignment vs. a smartphone placed in a strap with assumed alignment, and to analyze acceleration score differences across balance poses of increasing difficulty. The handheld and body strap smartphones exhibited moderately to strongly correlated angular velocity scores in the calibration maneuver (r = 0.487-0.983,

Indexed as

Postural BalancePrincipal Component AnalysisSmartphoneAccelerometryAdultCalibrationFemaleHumansMaleYoung Adultaccessibilityanatomical calibrationbalance assessmentinertial measurement unit (IMU)Principal Component Analysissmartphonewearables

Identifiers

PMID39275378
PMCPMC11397924

What OpenQuestion holds

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LicenceCC BY
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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.