Millions of people have reduced hand function;​ this loss of function can be due to injury, disease, or aging. Osteoarthritis is the leading cause of hand dysfunction in America, affecting over 60% of Americans over the age of 55. However, the current methods to quantify changes to hand function—such as questionnaires, goniometers, and dynamometry— are limited. In order to move towards personalized medicine and to design better devices for individuals with reduced hand function, it is critical to have an objective understanding of how hand function changes.

Therefore, the goals of this work were to 1) develop a method to quantify and visualize hand function in terms of kinematics (where the digits can reach) and kinetics (how the digits can apply force);​ 2) experimentally quantify the function of healthy fingers and develop a generalized linear mixed model (GLMM) to represent the finger function;​ and 3) track how hand function changes due to osteoarthritis and due to surgery.

First, a functional testing protocol was developed to calculate and visualize hand function. Motion capture was used to track finger and thumb postures over their ranges of motion and a multi-axis load cell with custom attachments was used to compute finger forces different at positions over their ranges of motion. The motion data were used to calculate the kinematic space of the digits, or everywhere each digit could reach. Then, the force data were transformed to the same coordinate space and mapped onto the kinematic spaces of each finger of each participant. Further, the functional data were normalized by the participants’ hand sizes and mapped to create population models.

Next, the functional testing protocol was used to quantify finger function of forty-one healthy individuals. Maximum finger forces were affected by the fingers’ joint angles (GLMM p<0.001), and direction of the force (GLMM p<0.001). Those differences were used to develop a generalized linear mixed model to estimate heathy finger strength across the ranges of motion for all four fingers.

Then, the healthy participants’ index finger function was compared to a population of participants with hand OA. The ranges of motion were smaller in participants with OA leading to an average 23% decrease in the kinematic space of the index finger. The OA group applied less force (Analysis of Variance p<0.001), using a smaller range of joint angles (ANOVA p=0.01) in a smaller range of directions (ANOVA p<0.001). The forces applied by the participants with OA also had reduced variation due to finger posture or force direction, as compared to healthy participants.

Finally, five patients were tested determine the effects of thumb suspensionplasty (removal of the trapezium followed by insertion of a suture wire between the first and second metacarpals). Participants were tested at three time points:​ before surgery, six weeks postsurgery, and again twelve weeks post-surgery. As expected, the suspensionplasty led to reduced pain in all patients;​ however, function was not consistently improved. Carpometacarpal joint ranges of motion were decreased due to the surgery, and the kinematic space of the thumb was similar after surgery to before surgery. The ability to apply forces, in terms of force magnitude, range of directions, and volume of space used to apply force, was not improved due to the surgery, but also did not lessen.

The ability to quantify motion and force data for each finger and map them together provides an improved understanding of the effects of treatments and rehabilitation and can lead to better informed device design. The models presented in this work can be used to compare an individual’s function to normative function so clinicians can determine what function was lost and develop a treatment plan. Going forward, this process can be used to compare other populations, such as stroke or juvenile arthritis, to determine how function has changed, or compare to other surgeries to understand how different procedures lead to different outcomes for patients with severe OA.