Using Electronic Handgrip Dynamometry and Accelerometry to Examine Multiple Aspects of Handgrip Function in Master Endurance Athletes: A Pilot Study

Abstract

Abstract Klawitter, LA, Hackney, KJ, Christensen, BK, Hamm, JM, Hanson, M, and McGrath, R. Using electronic handgrip dynamometry and accelerometry to examine multiple aspects of handgrip function in master endurance athletes: A Pilot Study. J Strength Cond Res 37(9): 1777–1782, 2023—Electronic handgrip dynamometry and accelerometry may provide novel opportunities to comprehensively measure muscle function for human performance, especially for master athletes. This investigation sought to determine the multivariate relationships between maximal strength, asymmetry, rate of force development, fatigability, submaximal force control, bimanual coordination, and neuromuscular steadiness to derive one or more handgrip principal components in master-aged endurance athletes. We included n = 31 cyclists and triathletes aged 35–70 years. Maximal strength, asymmetry, rate of force development, fatigability, submaximal force control, bimanual coordination, and neuromuscular steadiness were measured twice on each hand using electronic handgrip dynamometry and accelerometry. The highest performing measures were included in the analyses. A principal component analysis was conducted to derive a new collection of uncorrelated variables from the collected handgrip measurements. Principal components with eigenvalues >1.0 were kept, and individual measures with a factor loading of |>0.40| were retained in each principal component. There were 3 principal components retained with eigenvalues of 2.46, 1.31, and 1.17. The first principal component, “robust strength,” contained maximal strength, rate of force development, submaximal force control, and neuromuscular steadiness. The second principal component, “bilateral synergy,” contained asymmetry and bimanual coordination, whereas the third principal component, “muscle conditioning,” contained fatigability. Principal components 1, 2, and 3 explained 44.0, 31.6, and 24.4% of the variance, respectively. Different dimensions of muscle function emerged from our findings, suggesting the potential of a muscle function battery. Further research examining how these measures are associated with appropriate human performance metrics and lower extremity correlates is warranted.