Millions of people have reduced hand function; this loss of function can be due to injury, disease, or aging. Loss of hand function is identified as reduced motion abilities in the fingers or a decrease in the ability of the fingers to generate force. Unfortunately, there are limited data available regarding each finger's ability to produce force and how those force characteristics vary with changes in finger posture. To relate motion and force abilities of the fingers, first an approach to measure and map them together is needed. The goal of this work was to develop and demonstrate a method to quantify the force abilities of the fingers and map these forces to the kinematic space associated with each finger. Using motion capture and multi-axis load cells finger forces were quantified at different positions over their ranges of motion. These two sets of data were then converted to the same coordinate space and mapped together. Further, the data were normalized for the index finger and mapped as a population space model. The ability to quantify motion and force data for each finger and map them together will provide an improved understanding the effects of treatments and rehabilitation, identifying functional loss due to injury or disease, and device design.

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