Determining Functional Finger Capabilities of Healthy Adults: Comparing Experimental Data to a Biomechanical Model

The human hand has a wide range of possible functional abilities that can change with age, disease, and injury, and can vary from individual to individual and subsequently can affect a person's quality of life. The objective of this work was to develop a theoretical model of the space that is reachable by the hand, weighted to represent three types of functionality, and to compare this model to an experimental data set obtained from a healthy hand population. A theoretical model, termed the Weighted Fingertip Space, was developed using 50th percentile published hand data and ranges of finger motion. The functional abilities calculated in the model were the abilities to position the fingertip pad, orient the fingertip pad, and apply directional forces through the fingertip pad at all the reachable points in space with respect to the palm. Following the development of this theoretical model, experimental data sets from nine individuals with healthy hands were obtained through motion capture techniques. The experimental data were then compared to the theoretical model. Comparisons between a 50th percentile theoretical model and a subject with a similar sized hand showed good agreement in weighting parameters and overall size and shape of the model spaces. The experimental data set from the entire sample, which ranged from the 2nd to 95th percentile hand sizes, showed resultant models that, on average, reached smaller volumes of space, but yielded higher values of the functional measures within those volumes. Additionally, in comparison to the theoretical model, the variability of the experimental models showed that small changes in hand dimensions and ranges of motion of the finger joints had a large influence in the functional measures of the model. Combined, these results suggest that the modeling technique can calculate functional ability of the hand, but should be used on an individualized basis for evaluating changes in function (e.g., rehabilitation). Further, scaling to hand size has the potential to yield “average” models for larger population samples.