Assessing Human Feedback Parameters for Disturbance-Rejection

Electromyography (EMG) interfaces are a promising alternative to traditional manual interfaces such as joysticks, mice, and touchscreens for applications such as prosthetics, rehabilitation, and human-computer interaction. McRuer's crossover model has been extensively studied to determine the impacts of dynamical systems on humans using manual interfaces; however, the same analysis has not been conducted with EMG interfaces or more complex dynamical systems. In this paper, we establish and assess changes in human parameters (gain and delay) and bandwidth for manual (joystick) and EMG interfaces when humans are tasked with controlling a first- and second-order dynamical system. We performed a secondary data analysis to estimate the human parameters for 11 participants by performing least-squares fitting on the error between empirical estimates (calculated from measured signals and system dynamics at specific frequencies) and parameterized models (developed from the McRuer's gain-margin crossover model). EMG delay was smaller than the manual delay for the first-order system and EMG delay was smaller with the first-order system than the second-order system. EMG bandwidth was also larger than the manual bandwidth for both first- and second-order systems. These results suggest that using an EMG interface improves the user's reaction time in a first-order system, and the EMG interface increases the bandwidth that the user can control for both first- and second-order systems compared to a manual interface. Understanding the differences in delays and bandwidth based on interfaces and system dynamics is useful for designing multimodal interfaces or for complex systems where the human delay or bandwidth is important. Copyright (c) 2022 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)