HARMONIE: A multimodal control framework for human assistive robotics

Abstract

Effective user control of highly dexterous and robotic assistive devices requires intuitive and natural modalities. Although surgically implanted brain-computer interfaces (BCIs) strive to achieve this, a number of non-invasive engineering solutions may provide a quicker path to patient use by eliminating surgical implantation. We present the development of a semi-autonomous control system that utilizes computer vision, prosthesis feedback, effector centric device control, smooth movement trajectories, and appropriate hand conformations to interact with objects of interest. Users can direct a prosthetic limb through an intuitive graphical user interface to complete multi-stage tasks using patient appropriate combinations of control inputs such as eye tracking, conventional prosthetic controls/joysticks, surface electromyography (sEMG) signals, and neural interfaces (ECoG, EEG). Aligned with activities of daily living (ADL), these tasks include directing the prosthetic to specific locations or objects, grasping of objects by modulating hand conformation, and action upon grasped objects such as self-feeding. This Hybrid Augmented Reality Multimodal Operation Neural Integration Environment (HARMONIE) semi-autonomous control system lowers the user's cognitive load, leaving the bulk of command and control of the device to the computer. This flexible and intuitive control system could serve patient populations ranging from wheelchair-bound quadriplegics to upper-limb amputees.