Evidence map›Paper›PMID 39209869›Full record

ArticleScientific reports2024

In-Clinic and Natural Gait Observations master protocol (I-CAN-GO) to validate gait using a lumbar accelerometer.

Miles Welbourn, Paul Sheriff, Pirinka Georgiev Tuttle, Lukas Adamowicz, Dimitrios Psaltos, Amey Kelekar, Jessica Selig, Andrew Messere, Winnie Mei, David Caouette and 6 more

Abstract read
In one paragraph

Article in Scientific reports, 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. Review
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

16 authors.

Miles Welbourn *Pfizer, Inc, Cambridge, MA, USA.
Paul Sheriff *Pfizer, Inc, Cambridge, MA, USA.
Pirinka Georgiev TuttlePfizer, Inc, Cambridge, MA, USA.
Lukas AdamowiczPfizer, Inc, Cambridge, MA, USA.
Dimitrios PsaltosPfizer, Inc, Cambridge, MA, USA.
Amey KelekarPfizer, Inc, Cambridge, MA, USA.
Jessica SeligPfizer, Inc, Cambridge, MA, USA.
Andrew MesserePfizer, Inc, Cambridge, MA, USA.
Winnie MeiPfizer, Inc, Cambridge, MA, USA.
David CaouettePfizer, Inc, Cambridge, MA, USA.
Sana GhafoorPfizer, Inc, Cambridge, MA, USA.
Mar SantamariaPfizer, Inc, Cambridge, MA, USA.
Hao ZhangPfizer, Inc, Cambridge, MA, USA.
Charmaine DemanuelePfizer, Inc, Cambridge, MA, USA.
F Isik KarahanogluPfizer, Inc, Cambridge, MA, USA.
Xuemei CaiPfizer, Inc, Cambridge, MA, USA. xuemei.cai@pfizer.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traditional measurements of gait are typically performed in clinical or laboratory settings where functional assessments are used to collect episodic data, which may not reflect naturalistic gait and activity patterns. The emergence of digital health technologies has enabled reliable and continuous representation of gait and activity in free-living environments. To provide further evidence for naturalistic gait characterization, we designed a master protocol to validate and evaluate the performance of a method for measuring gait derived from a single lumbar-worn accelerometer with respect to reference methods. This evaluation included distinguishing between participants' self-perceived different gait speed levels, and effects of different floor surfaces such as carpet and tile on walking performance, and performance under different bouts, speed, and duration of walking during a wide range of simulated daily activities. Using data from 20 healthy adult participants, we found different self-paced walking speeds and floor surface effects can be accurately characterized. Furthermore, we showed accurate representation of gait and activity during simulated daily living activities and longer bouts of outside walking. Participants in general found that the devices were comfortable. These results extend our previous validation of the method to more naturalistic setting and increases confidence of implementation at-home.

Indexed as

AccelerometryGaitGait AnalysisActivities of Daily LivingAdultFemaleHealthy VolunteersHumansLumbosacral RegionMaleMiddle AgedWalkingWalking Speed

Identifiers

PMID39209869
PMCPMC11362325

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.