Abstract
Force trajectories during isometric force-matching tasks involving isometric contractions vary substantially across individuals. In this study, we investigated if this variability can be explained by discrete time proportional, integral, derivative (PID) control algorithms with varying model parameters. To this end, we analyzed the pinch force trajectories of 24 subjects performing two rapid force-matching tasks with visual feedback. Both tasks involved isometric contractions to a target force of 10% maximal voluntary contraction. One task involved a single action (pinch) and the other required a double action (concurrent pinch and wrist extension). 50,000 force trajectories were simulated with a computational neuromuscular model whose input was determined by a PID controller with different PID gains and frequencies at which the controller adjusted muscle commands. The goal was to find the best match between each experimental force trajectory and all simulated trajectories. It was possible to identify one realization of the PID controller that matched the experimental force produced during each task for most subjects (average index of similarity: 0.87 +/- A 0.12; 1 = perfect similarity). The similarities for both tasks were significantly greater than that would be expected by chance (single action: p = 0.01; double action: p = 0.04). Furthermore, the identified control frequencies in the simulated PID controller with the greatest similarities decreased as task difficulty increased (single action: 4.0 +/- A 1.8 Hz; double action: 3.1 +/- A 1.3 Hz). Overall, the results indicate that discrete time PID controllers are realistic models for the neural control of force in rapid force-matching tasks involving isometric contractions.