Back

Test-retest reliability of electronic hand dynamometer in healthy adults- A cross-sectional study

Francis, A. K.; Hadya Ananda, K.; Joseph, J. K.

2025-08-16 rehabilitation medicine and physical therapy
10.1101/2025.08.14.25333572 medRxiv
Show abstract

IntroductionHand grip strength (HGS), is a crucial indicator of muscle function and general physical capacity of the elderly. Few tools are available to measure grip strength, including pneumatic instruments, spring devices, and hydraulic systems. However, among these, hydraulic dynamometers, such as the Jamar dynamometer, have been considered the gold standard due to their superior reliability and precision. Despite their advantages, these tools often come with limitations, such as high cost. Hence, the purpose of this study is to estimate the test-retest reliability of the electronic hand dynamometer for grip-strength measurement and also to compare the reliability of the electronic hand dynamometer in flexed and extended elbow. MethodsThe participants were recruited via convenience sampling and this ross sectional study followed the procedure as per the American Society of Hand Therapist (ASHT) recommended standardized position for grip strength. ResultsThe reliability of the electronic hand dynamometer for the right side with the elbow flexed was found to be 0.94 while for left side, it was found to be 0.91. Meanwhile, the reliability for the right side with the elbow extended was found to be 0.98, and for the left side, it was 0.97. ConclusionThe findings of this study demonstrate that the Camry electronic hand dynamometer has excellent reliability in testing grip strength. The grip strength was found to produce maximum strength when measured in an elbow extended position.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.