Dealing with target uncertainty in a reaching control interface.
Prosthetic devices need to be controlled by their users, typically using physiological signals. People tend to look at objects before reaching for them and we have shown that combining eye movements with other continuous physiological signal sources enhances control. This approach suffers when subjects also look at non-targets, a problem we addressed with a probabilistic mixture over targets where subject gaze information is used to identify target candidates. However, this approach would be ineffective if a user wanted to move towards targets that have not been foveated. Here we evaluated how the accuracy of prior target information influenced decoding accuracy, as the availability of neural control signals was varied. We also considered a mixture model where we assumed that the target may be foveated or, alternatively, that the target may not be foveated. We tested the accuracy of the models at decoding natural reaching data, and also in a closed-loop robot-assisted reaching task. The mixture model worked well in the face of high target uncertainty. Furthermore, errors due to inaccurate target information were reduced by including a generic model that relied on neural signals only.
Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, Illinois, United States of America ; Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, Illinois, United States of America.
Elaine A
EA
Corbett
Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, Illinois, United States of America ; Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, Illinois, United States of America ; Department of Physiology, Northwestern University, Chicago, Illinois, United States of America.
Konrad P
KP
Körding
Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, Illinois, United States of America ; Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, Illinois, United States of America ; Department of Biomedical Engineering, Northwestern University, Chicago, Illinois, United States of America.
Eric J
EJ
Perreault
D000465:Algorithms; D003198:Computer Simulation; D004576:Electromyography; D006801:Humans; D008962:Models, Theoretical; D009132:Muscles / Q000502:physiology; D019736:Prostheses and Implants; D035501:Uncertainty