Investigating the effects of flexor tendon shortening on active range of motion after finger tendon repair.

Evaluation of surgical effects is often done using simple cadaver experimentation. This study uses a robotic testbed to estimate the best-case clinical outcomes of flexor tendon shortening during repair surgery on cadaver hands. Nine fresh-frozen cadaver subjects were connected to an extrinsic index finger robotic muscle testbed and measurement system. The flexor digitorum profundus tendons were severed and surgically repaired at different shortening levels. The index finger's extrinsic tendons were robotically actuated using Hill-type muscle models to emulate the muscle force-length relationships. Extensor muscles were then activated to estimate the active range of motion (ROM) of the all-finger joints after surgery. The effects of metacarpophalangeal (MCP) joint extension limits and extensor muscle activation were also investigated. The resulting interphalangeal joint ROM was clinically graded. Active ROM of the finger decreases as tendon shortening increases ( ηp2=0.92 ), like passive ROM. This results in a clinical reduction of functionality grade from excellent to good at 10 mm of shortening. Blocking MCP joint ROM and extensor activation also showed significant effects on recovered ROM ( ηp2=0.72 and 0.86). Significant two-way interactions were also observed between shortening and MCP joint blocking ( ηp2=0.80 ) and between shortening and extensor activation ( ηp2=0.78 ). Results support clinical recommendations of limiting shortening to 10 mm. While this article provides additional experimental evidence for current surgical recommendations, it also validates a new robotic-cadaver methodology for predicting active hand recovery in terms of clinical measurements.

Simultaneous Kinematic and Contact Force Modeling of a Human Finger Tendon System Using Bond Graphs and Robotic Validation.

This paper aims to use bond graph modeling to create the most comprehensive finger tendon model and simulation to date. Current models are limited to either free motion without external contact or fixed finger force transmission between tendons and fingertip. The forward dynamics model, presented in this work, simultaneously simulates the kinematics of tendon-finger motion and contact forces of a central finger given finger tendon inputs. The model equations derived from bond graphs are accompanied by nonlinear relationships modeling the anatomical complexities of moment arms, tendon slacking, and joint range of motion (ROM). The structure of the model is validated using a robotic testbed, Utah's Anatomically correct Robotic Testbed (UART) finger. Experimental motion of the UART finger during free motion (no external contact) and surface contact are simulated using the bond graph model. The contact forces during the surface contact experiments are also simulated. On average, the model was able to predict the steady-state pose of the finger with joint angle errors less than 6 deg across both free motion and surface contact experiments. The static contact forces were accurately predicted with an average of 11.5% force magnitude error and average direction error of 12 deg.

Design and optimization of PARTNER: a parallel actuated robotic trainer for NEuroRehabilitation.

Robotic devices are a promising and dynamic tool in the realm of post-stroke rehabilitation. Researchers are still investigating how the use of robots affects motor learning and what design characteristics best encourage recovery. We present a parallel-actuated, end-effector robot designed to provide spatial assistance for upper-limb therapy while exhibiting low impedance and high backdrivability. A gradient based optimization was performed to find an optimal design that accounted for force isotropy, mechanical advantage, workspace size, and counter-balancing. A beta prototype has been built to these specifications (low impedance and high backdrivability) and has undergone initial controller performance as well as fit and function testing. By fitting a nonlinear model to experimental frequency response data, the apparent mass, viscous friction coefficient, and dynamic dry friction coefficient were determined to be 0.242 kg, 0.114 Ns/m, and 0.894 N respectively. The robot will serve as a testing platform to investigate motor learning and evaluate the efficacy of control schemes for post-stroke movement therapy.