Evidence map›Paper›PMID 40942989›Full record

ArticleSensors (Basel, Switzerland)2025

Limited Interchangeability of Smartwatches and Lace-Mounted IMUs for Running Gait Analysis.

Theodor Meingast, Bryson Carrier, Amanda Melvin, Kenneth M Kozloff, Alexandra F DeJong Lempke, Adam S Lepley

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. 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. 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

6 authors.

Theodor MeingastSchool of Kinesiology, University of Michigan, Ann Arbor, MI 48109, USA.
Bryson CarrierSchool of Kinesiology, University of Michigan, Ann Arbor, MI 48109, USA.
Amanda MelvinSchool of Kinesiology, University of Michigan, Ann Arbor, MI 48109, USA.
Kenneth M KozloffSchool of Kinesiology, University of Michigan, Ann Arbor, MI 48109, USA.
Alexandra F DeJong LempkeSchool of Medicine, Department of Physical Medicine and Rehabilitation, Virginia Commonwealth University, Richmond, VA 23284, USA.ORCID 0000-0002-5702-9184
Adam S LepleySchool of Kinesiology, University of Michigan, Ann Arbor, MI 48109, USA.ORCID 0000-0002-7710-3150

Funding

Samsung Electronics (South Korea) AWD: 022743
6 · The paper itself

Abstract

Spatiotemporal running metrics such as cadence, stride length (SL), and ground contact time (GCT) are important for assessing performance and injury risk. However, such metrics are traditionally assessed using laboratory-based tools that are often inaccessible in applied settings. Wearable devices including smartwatches and lace-mounted inertial measurement units (IMUs) offer promising alternatives, yet cross-device agreement in reporting spatiotemporal variables remains unclear. This study evaluated agreement between a commercial smartwatch and lace-mounted IMUs across varied distances and environments in 65 physically active adults (33 female/32 male, height: 171.0 ± 8.9 cm; weight: 70.9 ± 15.2 kg). Participants completed indoor and outdoor runs (2.5 km, 5 km, 10 km, 20 km) wearing both devices simultaneously. Average cadence demonstrated acceptable agreement (MAPE = 4.1%, CCC = 0.66) and supported equivalence, particularly among males, during outdoor conditions, and longer run distances. In contrast, peak cadence showed weak correlation (MAPE = 5.3%, CCC = 0.29), and SL and GCT demonstrated poor agreement (MAPE = 14.9-19.0%, CCC = 0.30-0.39) across all conditions. While average cadence may serve as a metric for cross-device comparisons, especially for males, and longer-distance outdoor runs, other spatiotemporal metrics demonstrated poor agreement, limiting interchangeability. Understanding device-specific capabilities is essential when interpreting wearable-derived gait data. Further validation using gold-standard tools is needed to support accurate and applied use of wearable technologies.

Indexed as

GaitGait AnalysisRunningWearable Electronic DevicesAdultBiomechanical PhenomenaFemaleHumansMaleYoung Adultactivity monitorbiomechanicsbiometric technologyfield-based assessmentfitness trackergaitwearable sensors

Identifiers

PMID40942989
PMCPMC12431447

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.