A digit-resolved grip dynamometer for quantifying multi-finger force coordination: development and validation against reference hand dynamometer

The multi-finger force deficit (MFFD) is the reduction in force expressed during simultaneous multi-finger exertion relative to the summed force capacity of the individual digits. The MFFD has been linked to neural control mechanisms, but previous research generally has measured it using apparatuses and tasks that do not biomechanically match traditional handgrip strength (HGS) testing. The purpose of this study was to develop and validate a custom-built, digit-resolved grip dynamometer (DRGD) engineered to approximate standard Jamar testing conditions while providing the finger-specific force signals required to quantify MFFD. A custom DRGD was designed and manufactured to measure HGS and digit-resolved force in 22 volunteers. Known-mass dead-weight testing was used to assess static load-measurement accuracy independently of the clinical reference dynamometer (Jamar dynamometer; JD). For each device, peak HGS was defined as the highest force across maximal whole-hand trials, whereas mean HGS was calculated from the final two maximal trials. Device association and agreement were evaluated using Pearson correlation, intraclass correlation coefficients (ICC), and Bland–Altman analysis. Known-mass testing showed highly linear load measurement across the tested range (R² > 0.999), with mean relative errors of + 5.0% for the DRGD and − 2.7% for the JD. Pooled correlations were strong for both peak and mean HGS ( r = 0.99). Peak HGS showed good agreement for the dominant (ICC = 0.872) and non-dominant hand (ICC = 0.890), with biases of − 0.56% and − 9.19% respectively. Mean HGS agreement was also good (dominant ICC = 0.805; non-dominant ICC = 0.861), with a dominant hand mean bias of − 3.74% and a non-dominant hand median bias of -9.83%. The larger non-dominant differences are consistent with potential order, fatigue, and/or attentional effects from the fixed testing sequence. The DRGD reproduced conventional HGS outcomes with good agreement relative to the JD while providing digit-level force resolution not available from standard single-output dynamometry. The observed differences were generally modest and are compatible with protocol order effects, although device and protocol related sources cannot be fully separated in the present design. These results support the DRGD as a viable platform for conventional HGS measurement and for quantifying multi-digit coordination features.

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Publication Details

Journal
Journal of NeuroEngineering and Rehabilitation
Published
2026-10-30
DOI
https://doi.org/10.1186/s12984-026-02204-2
Primary Topic
Motor Control and Adaptation
Type
article
Field-Weighted Citation Impact
0.00

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article

A digit-resolved grip dynamometer for quantifying multi-finger force coordination: development and validation against reference hand dynamometer

Brian C. Clark, Thomas J. Boyle, Andrew B. Dick, Gregory M. Shaw et al.
1 links
Journal of NeuroEngineering and Rehabilitation
Motor Control and Adaptation
article

A digit-resolved grip dynamometer for quantifying multi-finger force coordination: development and validation against reference hand dynamometer

Brian C. Clark, Thomas J. Boyle, Andrew B. Dick, Gregory M. Shaw, Robert Williams
article en

Abstract

The multi-finger force deficit (MFFD) is the reduction in force expressed during simultaneous multi-finger exertion relative to the summed force capacity of the individual digits. The MFFD has been linked to neural control mechanisms, but previous research generally has measured it using apparatuses and tasks that do not biomechanically match traditional handgrip strength (HGS) testing. The purpose of this study was to develop and validate a custom-built, digit-resolved grip dynamometer (DRGD) engineered to approximate standard Jamar testing conditions while providing the finger-specific force signals required to quantify MFFD. A custom DRGD was designed and manufactured to measure HGS and digit-resolved force in 22 volunteers. Known-mass dead-weight testing was used to assess static load-measurement accuracy independently of the clinical reference dynamometer (Jamar dynamometer; JD). For each device, peak HGS was defined as the highest force across maximal whole-hand trials, whereas mean HGS was calculated from the final two maximal trials. Device association and agreement were evaluated using Pearson correlation, intraclass correlation coefficients (ICC), and Bland–Altman analysis. Known-mass testing showed highly linear load measurement across the tested range (R² > 0.999), with mean relative errors of + 5.0% for the DRGD and − 2.7% for the JD. Pooled correlations were strong for both peak and mean HGS ( r = 0.99). Peak HGS showed good agreement for the dominant (ICC = 0.872) and non-dominant hand (ICC = 0.890), with biases of − 0.56% and − 9.19% respectively. Mean HGS agreement was also good (dominant ICC = 0.805; non-dominant ICC = 0.861), with a dominant hand mean bias of − 3.74% and a non-dominant hand median bias of -9.83%. The larger non-dominant differences are consistent with potential order, fatigue, and/or attentional effects from the fixed testing sequence. The DRGD reproduced conventional HGS outcomes with good agreement relative to the JD while providing digit-level force resolution not available from standard single-output dynamometry. The observed differences were generally modest and are compatible with protocol order effects, although device and protocol related sources cannot be fully separated in the present design. These results support the DRGD as a viable platform for conventional HGS measurement and for quantifying multi-digit coordination features.

Journal of NeuroEngineering and Rehabilitation
Ohio University (US)
National Institutes of Health
Good health and well-being
Openalex Percentile: Top 14%
Motor Control and Adaptation
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