ReviewSensors (Basel, Switzerland)2025
Understanding Acceleration-Based Load Metrics: From Concepts to Implementation.
Review 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 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Relationships Between Weekly Dynamic Stress Load Volume and Match-Play External and Internal Load: Half-Specific and Full-Competition Analyses in Professional Soccer Players.Sensors (Basel, Switzerland) · 2026Article
- Playerload™ and accelerometer-based metrics: scientific evaluation and implications for athlete monitoring.Frontiers in sports and active living · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accelerometer-based wearables offer a cost-effective solution for managing match and training loads in invasion team sports. However, a multitude of acceleration-derived metrics, each employing different algorithms, has led to inconsistent and incomparable outcomes across studies and devices. This article reviews the mathematical procedures underlying whole-body mechanical load metrics, clarifies their conceptual differences, and proposes refinements to enhance standardization. Synthetic data were employed to investigate conceptual differences, while experimental accelerometric data (463 time series) from a set of elite handball training sessions (involving 16 players) were used to implement the corrected equations and analyze statistical relationships. Analysis of synthetic data revealed that derivative-based metrics, such as Jerk Modulus (typically referred to as Player Load) and corrected Accel'Rate (cAccel'Rate), tend to amplify noise compared to acceleration-based metrics, such as universal Dynamic Stress Load (uDSL) and Body Load. Experimental results indicated that when metrics were summed, their values were nearly identical. In time-series comparisons, Jerk Modulus and cAccel'Rate were predictably found to be nearly identical, while Body Load was the most distinct. Acceleration-based metrics are preferable to derivative-based ones. Sports scientists should lead the design and validation of such metrics, ensuring methodological rigor, transparency, and innovation while preventing commercial interests from introducing rebranded variables with undisclosed scaling factors and unclear calculations.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.