
Research Article
Enhancing Strength Assessment: A Comprehensive Analysis of Velocity-Based and Isometric Methods for 1RM Estimation
@INPROCEEDINGS{10.4108/eai.16-9-2025.2361061, author={Asep Prima and Putra Arima and Melly Br Bangun}, title={ Enhancing Strength Assessment: A Comprehensive Analysis of Velocity-Based and Isometric Methods for 1RM Estimation}, proceedings={Proceedings of the 7th International Conference on Innovation in Education, Science, and Culture, ICIESC 2025, 16 September 2025, Medan, Indonesia}, publisher={EAI}, proceedings_a={ICIESC}, year={2026}, month={3}, keywords={one-repetition maximum (1rm) load-velocity relationship (l-v) isometric midthigh pull (imtp) strength estimation methods bibliometric analysis}, doi={10.4108/eai.16-9-2025.2361061} }- Asep Prima
Putra Arima
Melly Br Bangun
Year: 2026
Enhancing Strength Assessment: A Comprehensive Analysis of Velocity-Based and Isometric Methods for 1RM Estimation
ICIESC
EAI
DOI: 10.4108/eai.16-9-2025.2361061
Abstract
This study explores safer and more efficient alternatives to traditional one-repetition maximum (1RM) testing, particularly for the elderly or individuals with medical conditions. It focuses on velocity-based methods, specifically the load-velocity (L-V) relationship, and isometric approaches, like the isometric midthigh pull (IMTP), which correlate strongly with maximal strength while reducing fatigue and injury risk. A bibliometric analysis using VOSviewer software was conducted on articles from 2015 to 2025 to map trends, identify key researchers, and highlight gaps. The results show a growing interest in 1RM estimation since 2017. L-V methods relate lifting velocity to maximal strength, while isometric tests offer fatigue-free alternatives. However, variability in technique and individual response remains a challenge. The study underscores the need to standardize these methods for broader applicability. Future research should enhance accuracy, especially for untrained and clinical populations. Overall, alternative 1RM estimation methods show promise but require refinement and validation.


