Hand Grip Force–Time Curve Indicators Evaluated by Dynamometer: A Systematic Review

Author:

Silva-Santos Tânia1ORCID,Guerra Rita S.12ORCID,Valdiviesso Rui34ORCID,Amaral Teresa F.13ORCID

Affiliation:

1. LAETA-INEGI/FEUP, Associated Laboratory of Energy, Transports and Aerospace, Institute of Science and Innovation in Mechanical and Industrial Engineering, Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal

2. FP-I3ID, FP-BHS, Faculty of Health Sciences, University Fernando Pessoa, 4200-150 Porto, Portugal

3. FCNAUP, Faculty of Nutrition and Food Sciences, University of Porto, 4150-180 Porto, Portugal

4. CINTESIS@RISE, MEDCIDS, Faculty of Medicine, University of Porto, 4200-450 Porto, Portugal

Abstract

Background: Handgrip strength (HGS) is an indicator of muscular strength, used in the diagnosis of sarcopenia, undernutrition, and physical frailty as well as recovery. Typically, the maximum HGS value is used; however, recent evidence suggests the exploration of new indicators provided based on the force–time curve to achieve a more comprehensive assessment of muscle function. Therefore, the objective was to identify indicators of the HGS profile beyond maximum HGS, based on force–time curves, and to systematize knowledge about their applications to various types of samples, health issues, and physical performance. Methods: A systematic review was performed including studies whose participants’ HGS was assessed with a digital or adapted dynamometer. The outcome measures were HGS profile indicators calculated from the force–time curve. Results: a total of 15 studies were included, and the following indicators were identified: grip fatigue, fatigability index, fatigue rate, fatigue resistance, time to 80% maximal voluntary contraction, plateau coefficient of variability, time to maximum value, T-90%, release rate, power factor, grip work, average integrated area, endurance, cycle duration, time between cycles, maximum and minimum force–velocity, rate of grip force, final force, inflection point, integrated area, submaximal control, and response time. Conclusions: Various indicators based on the force–time curve can be assessed through digital or adapted dynamometers. Future research should analyze these indicators to understand their implications for muscle function assessment, to standardize evaluation procedures, to identify clinically relevant measures, and to clarify their implications in clinical practice.

Funder

FCT/MCTES

Publisher

MDPI AG

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