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

Abstract

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.

A Soft Sensor-Based Three-Dimensional (3-D) Finger Motion Measurement System

“…The CMC joint was modeled to have two intersecting and perpendicular rotation axes with the flexion/extension and abduction/adduction, while keeping the orthogonality of the two axes [18]. As the amount of the axial rotation angle is relatively small (17 deg for the normal movement) and the limited space for the phalanges on thumb finger, axial rotation was neglected and the number of soft sensor was reduced [18,22,23]. The model for the CMC joint without the pronation rotation was suggested as shown in the Figure 9.…”

Mapping kinematic functional abilities of the hand to three dimensional shapes for inclusive design

“…The ROM for each angular rotation was determined using motion capture measurements. Detailed descriptions of the specific motions, hand measurements and targeting protocol can be found in previously published work on the development of the WFS model (Leitkam and Bush, 2015;Leitkam et al, 2013).…”

“…The framework for evaluating and modeling hand capabilities was the WFS model, previously developed by the authors (Leitkam et al, 2013). The WFS model was a 3D volume representing points that were reachable by each fingertip pad in space and weighted by three parameters that addressed levels of functionality for the fingertips.…”

“…The weighted fingertip space (WFS) model developed by the authors is one such model that Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/jbiomech www.JBiomech.com calculates the reachable spaces and weights the spaces according to kinematic functional abilities (Leitkam et al, 2013). The WFS model defines 3D reachable hand spaces using hand anthropometry and joint angles as input and then weights the reachable points to identify the (1) relative number of possible finger postures that allow a fingertip to reach each point, (2) range of possible orientations that the fingertip could assume at each point and (3) angular range of possible directions the fingertip could apply forces at each point.…”

Workspace Shape and Characteristics for Human Two- and Three-Fingered Precision Manipulation

“…More prior research has studied human grasping [1]- [4] and finger force modulation [5], while understanding the human hand's kinematic capabilities during dexterous, withinhand manipulation [6] has been largely ignored. Some studies have analyzed the kinematic capabilities of individual fingers in healthy participants [7], [8], as well as comparing the finger capabilities of participants with impaired hand functionality [9]- [11]. However, only a few studies (see Section II) directly consider the precision manipulation task of multiple fingertips interacting with an object, as in the present work.…”