Elucidating Sensorimotor Control Principles with Myoelectric Musculoskeletal Models

Abstract

While initially considered a tool for analyzing the mechanics of movement, myoelectric musculoskeletal models (MMMs) are now being used to expand the frontiers of knowledge in human sensorimotor control and learning. A MMM uses electromyography to sample human motor commands; these commands serve as inputs to mathematical models of muscular dynamics, which in turn act on a model of skeletal dynamics to produce a simulated motor action in real-time. When used to investigate human sensorimotor control principles, a MMM user performs goal-directed motor tasks while the actions of the MMM are displayed on a monitor. Depending on the application, the MMM can be personalized to reflect the musculoskeletal dynamics of an individual, artificial neural dynamics can be added such as noise or delays, sensory feedback can be altered using electrotactile, vibrotactile, or skin-stretch feedback, and an individual’s physical interaction with the MMM can be modified using a robotic apparatus to impose modeled dynamics. The power of an MMM for studying human sensorimotor control stems from its ability to (1) alter the functional interaction between human neural control processes and biomechanics, and (2) allow precise and controlled manipulations of neuromusculoskeletal dynamics that would normally be impossible to perform on living humans. This mini-review provides a brief overview of the design and operation of MMMs, discusses recent experiments that use MMMs to increase our understanding of the principles governing the control of human movement, and ends by highlighting current challenges and future possibilities.