Evidence map›Paper›PMID 36065060›Full record

ArticleNPJ digital medicine2022

Validation of Amazon Halo Movement: a smartphone camera-based assessment of movement health.

Michael Fanton, Yaar Harari, Matthew Giffhorn, Allie Lynott, Eli Alshan, Jonathan Mendley, Madeline Czerwiec, Rebecca Macaluso, Ianir Ideses, Eduard Oks and 1 more

Open access · goldAbstract read
In one paragraph

Article in NPJ digital medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.2field-weighted citation impact, top 20% 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

5 citing papers in PubMed, 16 citations in OpenAlex.

  1. Observational
  2. Article
  3. Review
  4. Article
  5. 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

11 authors at 3 institutions in 2 countries.

Michael Fanton *Max Nader Lab for Rehabilitation Technologies and Outcomes Research, Shirley Ryan AbilityLab, Chicago, IL, USA.
Yaar Harari *Amazon Ltd, Seattle, WA, USA.
Matthew GiffhornMax Nader Lab for Rehabilitation Technologies and Outcomes Research, Shirley Ryan AbilityLab, Chicago, IL, USA.
Allie LynottMax Nader Lab for Rehabilitation Technologies and Outcomes Research, Shirley Ryan AbilityLab, Chicago, IL, USA.
Eli AlshanAmazon Ltd, Seattle, WA, USA.
Jonathan MendleyMax Nader Lab for Rehabilitation Technologies and Outcomes Research, Shirley Ryan AbilityLab, Chicago, IL, USA.
Madeline CzerwiecMax Nader Lab for Rehabilitation Technologies and Outcomes Research, Shirley Ryan AbilityLab, Chicago, IL, USA.
Rebecca MacalusoMax Nader Lab for Rehabilitation Technologies and Outcomes Research, Shirley Ryan AbilityLab, Chicago, IL, USA.
Ianir IdesesAmazon Ltd, Seattle, WA, USA.
Eduard OksAmazon Ltd, Seattle, WA, USA.
Arun JayaramanMax Nader Lab for Rehabilitation Technologies and Outcomes Research, Shirley Ryan AbilityLab, Chicago, IL, USA. a-jayaraman@northwestern.edu.ORCID http://orcid.org/0000-0002-9302-6693
Shirley Ryan AbilityLab · USAmazon (United States) · USNorthwestern University · US

Funding

PATHOPHYSIOLOGY AND REHABILITATION OF NEURAL DYSFUNCTIONT32HD007418 · NICHD · NORTHWESTERN UNIVERSITY AT CHICAGO · PI Levi John Hargrove · 1992 to 2026
$6.5M
NICHD NIH HHS T32 HD007418
6 · The paper itself

Abstract

Movement health is understanding our body's ability to perform movements during activities of daily living such as lifting, reaching, and bending. The benefits of improved movement health have long been recognized and are wide-ranging from improving athletic performance to helping ease of performing simple tasks, but only recently has this concept been put into practice by clinicians and quantitatively studied by researchers. With digital health and movement monitoring becoming more ubiquitous in society, smartphone applications represent a promising avenue for quantifying, monitoring, and improving the movement health of an individual. In this paper, we validate Halo Movement, a movement health assessment which utilizes the front-facing camera of a smartphone and applies computer vision and machine learning algorithms to quantify movement health and its sub-criteria of mobility, stability, and posture through a sequence of five exercises/activities. On a diverse cohort of 150 participants of various ages, body types, and ability levels, we find moderate to strong statistically significant correlations between the Halo Movement assessment overall score, metrics from sensor-based 3D motion capture, and scores from a sequence of 13 standardized functional movement tests. Further, the smartphone assessment is able to differentiate regular healthy individuals from professional movement athletes (e.g., dancers, cheerleaders) and from movement impaired participants, with higher resolution than that of existing functional movement screening tools and thus may be more appropriate than the existing tests for quantifying functional movement in able-bodied individuals. These results support using Halo Movement's overall score as a valid assessment of movement health.

Identifiers

PMID36065060
PMCPMC9445016
OpenAlexW4294916358

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.