Anthropometric data for describing the kinematics of the human hand

Abstract

The major goal of this investigation was to collect statistically-based anthropometry describing the kinematics of the human hand and to model this anthropometry as a function of external hand measurements, so that it may be predicted noninvasively. Joint centres were anatomically estimated as the centre of curvature of the head of the bone proximal to the given joint. Joint centres determined using Reuleaux's method for PIP and DIP were within 1.4 mm of this anatomical estimate. Models using bone length as the independent variable explain more than 97% of the variability in the anatomically estimated joint centre position along the mid-line of the bone. Models for estimating the lengths of the kinematic segments using external hand length as the independent variable account for between 49 and 99% of the variability in segment length. Models for estimating the axial location of the finger MCP and thumb CMC joints with respect to the distal wrist crease using external hand length as the independent variable account for between 82 and 96% of the variability in these locations. Models for estimating the radio-ulnar location of the finger MCP and thumb CMC joints with respect to the long axis of the third metacarpal using external hand breadth as the independent variable account for between 30 and 74% of the variability in these locations.

A natural human hand model

“…As a statistical mean hand does not exist (is inherently unnatural), only personalized data can sustain general principles. Many data can be found [5,33] but always depersonalized.…”

“…We first measure adduction-abduction of the tmc JASS by taking radiographs and analyze them with a compass and ruler comparably to Buchholz et al [5] and other authors. We only derive the distance between tmc axes from this method (18.4 mm, after compensation for plate distance and radiation spread).…”

Scalability of the Muscular Action in a Parametric 3D Model of the Index Finger

“…Scalability of rotation axes location was achieved using the work of Buchholz,4 tendon action scalability by adapting the model proposed by An, 1 and ligament action scalability by adapting the geometric model presented by Pagowski. 9 In the absence of data from literature with regard to modelling differences in the muscular power of hands from different population groups, the authors considered a simple model for scalability in previous works, 11,12 using the same HL and HB parameters used for scaling the rest of the model components.…”

Towards a Realistic and Self-Contained Biomechanical Model of the Hand

“…Due to the important role that the shape of the palm plays in grasping, this model is considered more suitable for grasping simulation than others in the literature. The data for the location and orientation of the rotation axes comes from An et al (1979), Buchholz et al (1992) and Hollister et al (1995). Axes data and link lengths are fully scaled with respect to the hand length and hand breadth (Sancho-Bru, 2000).…”

“…The data for the location of the points defining the tendon paths comes from An et al (1979) and Buchholz et al (1992), and are also scaled with respect to the hand length and hand breadth (Sancho-Bru, 2000).…”