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September 5, 2026Sports Medicine - OpenOpen Access

Commercial velocity sensors show good-to-excellent validity and agreement despite heterogeneity across technologies and exercise types.

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Why the study?

Are commercially available velocity sensors and velocity-based 1RM prediction models valid and reliable?

Population

101 studies evaluating load-velocity relationships

Design

Meta-analysis

Key result

Commercially available velocity sensors demonstrated good-to-excellent pooled validity and device agreement (ICC 0.91-0.92), though substantial heterogeneity exists depending on sensor technology and exercise type.

Authors

NCNina ClaassenSSStanislav D. SiegelMSMareike Sproll

Discussion

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Overview

Supports velocity-based training protocols; confirms pooled sensor validity while leaving technology- and exercise-specific heterogeneity unresolved.

Key Points

  • To comprehensively assess the validity and reliability of commercial velocity sensors and evaluate the accuracy of velocity-based one-repetition maximum (1RM) prediction models.
  • Conducted a systematic review across PubMed/MEDLINE, Web of Science, and Scopus registered in PROSPERO (CRD42025634595) using an adapted COSMIN framework to evaluate methodological quality.
  • Extracted and meta-analyzed intraclass correlation coefficients (ICC), Lin's concordance correlation coefficients, and Pearson's r across 63 sensor studies and 38 1RM prediction studies.
  • Commercial velocity sensors demonstrated good-to-excellent pooled validity (ICC = 0.91–0.92 [95% CI: 0.83–0.97], k = 55) and intra-/inter-day reliability (ICC = 0.90–0.91 [95% CI: 0.85–0.95], k = 228 and 608), with linear position transducers performing more consistently than inertial measurement units.
  • Velocity-based 1RM prediction showed high pooled reliability (ICC = 0.90 [95% CI: 0.83–0.94], k = 124) and validity (ICC = 0.91 [95% CI: 0.72–0.98], k = 9), but lower-body exercises exhibited substantial heterogeneity.

Study Design

Type

Meta-Analysis (n=101)

Structured PICO

Are commercially available velocity sensors and velocity-based 1RM prediction models valid and reliable?

P
Population
A systematic review and meta-analysis of 101 studies evaluating the validity, reliability, and device agreement of commercially available velocity sensors and velocity-based one-repetition maximum prediction models in healthy participants.
E
Exposure
Commercially available velocity sensors and velocity-based 1RM prediction models
O
Outcome
Validity, device agreement, and reliability (intra- and inter-day) measured via intraclass correlation coefficient (ICC), Lin’s concordance correlation coefficient (CCC), and Pearson’s correlation coefficient (r)

Main Result

Effect estimate: ICC 0.91-0.92 (95% CI 0.83-0.97)

Commercial velocity sensors and velocity-based 1RM prediction models demonstrate high average validity and reliability, but substantial heterogeneity and exercise-specific variability require cautious interpretation.

Limitations

  • Substantial heterogeneity and wide ranges of study-level estimates indicating considerable variability across moderators
  • Dearth of measurement error and agreement analyses prohibits final conclusions
  • Large heterogeneity in lower body exercises significantly biased the 1RM prediction results
  • Risk of publication bias and small-study effects in some analyses
  • Substantial heterogeneity
  • Wide ranges of study-level estimates
  • Dearth of measurement error and agreement analyses
  • Sensor- and exercise-specific evidence remains limited

Cite This Study

Claassen et al. (2026) conducted a meta-analysis in Healthy participants undergoing resistance training (n=101). Commercially available velocity sensors and velocity-based 1RM prediction models vs. Gold standard systems (e.g., 3D motion capture) or reference sensors was evaluated on Validity and device agreement of velocity sensors (ICC 0.91-0.92, 95% CI 0.83-0.97). Commercially available velocity sensors demonstrated good-to-excellent pooled validity and device agreement (ICC 0.91-0.92), though substantial heterogeneity exists depending on sensor technology and exercise type.

synapsesocial.com/papers/6a9bd4046b95aff0620eb504https://doi.org/10.1186/s40798-026-01102-0
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