Cells in our bodies sense and process information from their local tissue environment in order to adaptively respond to stimuli. We hypothesise that positive feedback between changes in cell shape (movement) and cell receptors (signalling) dynamically adapt the sensory interface of the cell, aiding information processing and cell decision-making. This idea, known as sensorimotor coupling, is the basis of active perception, a widely studied process in the fields of neuroscience, robotics and psychology that is known to enhance decision-making and other cognitive tasks in higher organisms. Currently, in cell biology, cell sensing (signalling) and motion (movement) are largely investigated independently, using different experimental assays and techniques, such that the level of coupling between these processes has been hard to measure. Here, we propose to investigate sensorimotor coupling in individual cells using a framework employing the information-based measure transfer entropy. Through agentbased computational modelling, we demonstrate its sensitivity to levels of coupling in a variety of simulated cell perturbations. To facilitate biological application, we use cellular readouts that we demonstrate are feasible to measure in real biological cells in vitro. Overall, this work highlights the potential of information theory to quantitatively investigate biological cell function, paving the way for translating theoretical developments to experimental biology.