WheelCon: A wheel control-based gaming platform for studying human sensorimotor control

TL;DR

WheelCon is an open-source, flexible gaming platform that simulates sensorimotor tasks, allowing manipulation of feedback components for neuroscience research and control engineering education.

Contribution

It introduces a customizable, cost-effective platform for studying human sensorimotor control with adjustable feedback loop parameters.

Findings

Demo results align with theoretical model predictions.

Platform effectively simulates complex sensorimotor tasks.

Flexible manipulation of feedback components demonstrated.

Abstract

Feedback control theory has been extensively implemented to theoretically model human sensorimotor control. However, experimental platforms capable of manipulating important components of multiple feedback loops lack development. This paper describes the WheelCon, which is an open source platform aimed at resolving such insufficiencies. WheelCon enables safely simulation of the canonical sensorimotor task such as riding a mountain bike down a steep, twisting, bumpy trail etc., with provided only a computer, standard display, and an inexpensive gaming steering wheel with a force feedback motor. The platform provides flexibility, as will be demonstrated in the demos provided, so that researchers may manipulate the disturbances, delay, and quantization (data rate) in the layered feedback loops, including a high-level advanced plan layer and a low-level delayed reflex layer. In this paper, we illustrate WheelCon's graphical user interface (GUI), the input and output of existing demos, and how to design new games. In addition, we present the basic feedback model, and we show the testing results from our demo games which align well with prediction from the model. In short, the platform is featured as cheap, simple to use, and flexible to program for effective sensorimotor neuroscience research and control engineering education.