Random measurement and prediction errors limit the practical relevance of two velocity sensors to estimate the 1RM back squat

Research output: Journal contributionsJournal articlesResearchpeer-review

Authors

  • Konstantin Warneke
  • Josua Skratek
  • Carl Maximilian Wagner
  • Klaus Wirth
  • Michael Keiner

Introduction: While maximum strength diagnostics are applied in several sports and rehabilitative settings, dynamic strength capacity has been determined via the one-repetition maximum (1RM) testing for decades. Because the literature concerned several limitations, such as injury risk and limited practical applicability in large populations (e.g., athletic training groups), the strength prediction via the velocity profile has received increasing attention recently. Referring to relative reliability coefficients and inappropriate interpretation of agreement statistics, several previous recommendations neglected systematic and random measurement bias. Methods: This article explored the random measurement error arising from repeated testing (repeatability) and the agreement between two common sensors (vMaxPro and TENDO) within one repetition, using minimal velocity thresholds as well as the velocity = 0 m/s method. Furthermore, agreement analyses were applied to the estimated and measured 1RM in 25 young elite male soccer athletes. Results: The results reported repeatability values with an intraclass correlation coefficient (ICC) = 0.66–0.80, which was accompanied by mean absolute (percentage) errors (MAE and MAPE) of up to 0.04–0.22 m/s and ≤7.5%. Agreement between the two sensors within one repetition showed a systematic lower velocity for the vMaxPro device than the Tendo, with ICCs ranging from 0.28 to 0.88, which were accompanied by an MAE/MAPE of ≤0.13 m/s (11%). Almost all estimations systematically over/ underestimated the measured 1RM, with a random scattering between 4.12% and 71.6%, depending on the velocity threshold used. Discussion: In agreement with most actual reviews, the presented results call for caution when using velocity profiles to estimate strength. Further approaches must be explored to minimize especially the random scattering.

Original languageEnglish
Article number1435103
JournalFrontiers in Physiology
Volume15
Number of pages11
ISSN1664-042X
DOIs
Publication statusPublished - 10.09.2024

Bibliographical note

Publisher Copyright:
Copyright © 2024 Warneke, Skratek, Wagner, Wirth and Keiner.

Recently viewed

Publications

  1. Towards a Dynamic Interpretation of Subjective and Objective Values
  2. Substructure, subgraph, and walk counts as measures of the complexity of graphs and molecules.
  3. Using Decision Trees and Reinforcement Learning for the Dynamic Adjustment of Composite Sequencing Rules in a Flexible Manufacturing System
  4. Building Assistance Systems using Distributed Knowledge Representations
  5. DialogueMaps: Supporting interactive transdisciplinary dialogues with a web-based tool for multi-layer knowledge maps
  6. The learning net - an interactive representation of shared knowledge
  7. Set-oriented numerical computation of rotation sets
  8. Isocodal and isospectral points, edges, and pairs in graphs and how to cope with them in computerized symmetry recognition
  9. Making an Impression Through Openness
  10. A model predictive control for an aggregate actuator with a self-tuning initial condition procedure in combustion engines
  11. A discrete approximate solution for the asymptotic tracking problem in affine nonlinear systems
  12. Multi-Parallel Sending Coils for Movable Receivers in Inductive Charging Systems
  13. Control of a Sun Tracking Robot Based on Adaptive Sliding Mode Control with Kalman Filtering and Model Predictive Control
  14. Anomaly detection in formed sheet metals using convolutional autoencoders
  15. Framework for setting up and operating biobanks
  16. Perfect anti-windup in output tracking scheme with preaction
  17. Introducing a multivariate model for predicting driving performance
  18. Semantic Parsing for Knowledge Graph Question Answering with Large Language Models
  19. Reading and Calculating in Word Problem Solving
  20. Selection and Recognition of Statistically Defined Signals in Learning Systems
  21. Inversion of fuzzy neural networks for the reduction of noise in the control loop
  22. Age-related differences in processing visual device and task characteristics when using technical devices
  23. Evaluating the construct validity of Objective Personality Tests using a multitrait-multimethod-Multioccasion-(MTMM-MO)-approach
  24. A denoising procedure using wavelet packets for instantaneous detection of pantograph oscillations
  25. Managing Business Process in Distributed Systems: Requirements, Models, and Implementation
  26. Evaluating OWL 2 reasoners in the context of checking entity-relationship diagrams during software development
  27. The elicitation process in developing of case library for Case-Based Reasoner system whilst consideration for validating electronic communication technologies
  28. A multi input sliding mode control for Peltier Cells using a cold-hot sliding surface
  29. Design and Control of an Inductive Power Transmission System with AC-AC Converter for a Constant Output Current
  30. On robustness properties in permanent magnet machine control by using decoupling controller
  31. Construct Objectification and De-Objectification in Organization Theory
  32. Vision-Based Deep Learning Algorithm for Detecting Potholes
  33. Methodologies for Noise and Gross Error Detection using Univariate Signal-Based Approaches in Industrial Application
  34. A model predictive control in Robotino and its implementation using ROS system
  35. Analysis and comparison of two finite element algorithms for dislocation density based crystal plasticity