Evidence map›Paper›PMID 37896635›Full record

ArticleSensors (Basel, Switzerland)2023

Can Gait Characteristics Be Represented by Physical Activity Measured with Wrist-Worn Accelerometers?

Wenyi Lin, Fikret Isik Karahanoglu, Dimitrios Psaltos, Lukas Adamowicz, Mar Santamaria, Xuemei Cai, Charmaine Demanuele, Junrui Di

Open access · goldAbstract read
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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

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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

8 authors at 1 institution in 1 country.

Wenyi LinPfizer Inc., Cambridge, MA 02139, USA.ORCID 0000-0001-8767-1795
Fikret Isik KarahanogluPfizer Inc., Cambridge, MA 02139, USA.ORCID 0000-0002-9162-8367
Dimitrios PsaltosPfizer Inc., Cambridge, MA 02139, USA.ORCID 0000-0002-3347-307X
Lukas AdamowiczPfizer Inc., Cambridge, MA 02139, USA.ORCID 0000-0001-6992-9545
Mar SantamariaPfizer Inc., Cambridge, MA 02139, USA.
Xuemei CaiPfizer Inc., Cambridge, MA 02139, USA.ORCID 0000-0001-9822-9935
Charmaine DemanuelePfizer Inc., Cambridge, MA 02139, USA.ORCID 0000-0002-7715-9920
Junrui DiPfizer Inc., Cambridge, MA 02139, USA.ORCID 0000-0001-6325-8090
Pfizer (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wearable accelerometers allow for continuous monitoring of function and behaviors in the participant's naturalistic environment. Devices are typically worn in different body locations depending on the concept of interest and endpoint under investigation. The lumbar and wrist are commonly used locations: devices placed at the lumbar region enable the derivation of spatio-temporal characteristics of gait, while wrist-worn devices provide measurements of overall physical activity (PA). Deploying multiple devices in clinical trial settings leads to higher patient burden negatively impacting compliance and data quality and increases the operational complexity of the trial. In this work, we evaluated the joint information shared by features derived from the lumbar and wrist devices to assess whether gait characteristics can be adequately represented by PA measured with wrist-worn devices. Data collected at the Pfizer Innovation Research (PfIRe) Lab were used as a real data example, which had around 7 days of continuous at-home data from wrist- and lumbar-worn devices (GENEActiv) obtained from a group of healthy participants. The relationship between wrist- and lumbar-derived features was estimated using multiple statistical methods, including penalized regression, principal component regression, partial least square regression, and joint and individual variation explained (JIVE). By considering multilevel models, both between- and within-subject effects were taken into account. This work demonstrated that selected gait features, which are typically measured with lumbar-worn devices, can be represented by PA features measured with wrist-worn devices, which provides preliminary evidence to reduce the number of devices needed in clinical trials and to increase patients' comfort. Moreover, the statistical methods used in this work provided an analytic framework to compare repeated measures collected from multiple data modalities.

Indexed as

AccelerometryWristExerciseGaitHumansWrist Jointaccelerometrydevice placementgaitjoint and individual variation explainedmultilevel modelpartial least squarepenalized regressionsphysical activitywearable devices

Identifiers

PMID37896635
PMCPMC10611403
OpenAlexW4387744176

What OpenQuestion holds

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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.