"Assistive devices are revolutionizing the way people with severe motor impairments are able to interact with their environments and perform activities of daily living. Brain-machine interfaces are not well-suited for the changing body and brain of a growing child and therefore we focused our efforts on further developing body-motion interfaces (BoMIs). Current BoMIs are based on principal-component analysis (PCA) and are well-suited for 2D tasks. We extended the PCA position control mode to velocity control mode to enable children to control the positions of the end-effector of a robotic arm. Testing showed that this method was not well-suited for younger children, nor was it easily expandable to higher degrees of freedom. We also developed a novel BoMI technique utilizing a finite element model to produce a virtual representation of the user's body, referred to as the virtual body model. This enables us to project the movements of the subject to a set of distinct anatomical motion patterns. Using natural body motions of the torso and head, the distinct motion patterns are intuitive and easily learned, even when considering numerous degree-of-freedom (DOF) control. The proposed method can take small, inexpensive, wireless sensors and reliably produce accurate pose estimates of the user. The estimates can be interpreted by the software to generate commands for the assistive device. In testing, a user with limited training was able to utilize the interface to control five DOFs of a robotic arm in order to conduct a pick-and-place task as well as to drink from a water bottle."--Page ii.
Read
