Despite progress in the field of assistive technologies for people who suffered an injury to the spinal cord (SCI), most of the current devices to control computers and wheelchairs are set in place to require as little physical effort as possible from the user, and little attention has been paid to maintaining and strengthening the neural and muscular resources that survived the injury. We recently developed a novel non-invasive body- machine interface (BMI) for the continuous control of a two-dimensional computer cursor using four inertial measurement units (IMUs) placed on the user's upper body. Results on healthy subjects indicate that taking advantage of the redundancy of the signals from the IMUs improved overall performance. In this study we propose to validate our results on people with SCI and determine the rehabilitative effects of practicing upper- body control of personalized interface in this population. A combination of diffusion tension magnetic resonance imaging (DTI), optical tracking, and force and functional clinical evaluations, will provide a framework fo inferring changes in brain structures and motor impairment from task measures provided by an assistive device. Moreover, we will demonstrate the ability of SCI patients to improve-or prevent the degradation of-the motor and neural resources that survived the injury through practice with a BMI.
The objective of this project to provide a framework for inferring changes in brain structures and motor impairment from task measures provided by an assistive device in people with spinal cord injury. Using a combination of task performance, clinical measures of function and impairment, and magnetic reasoning imaging, we will increase our understanding of the mechanisms of plasticity underlying functional recovery and the rehabilitative effects of practicing upper-body control of an assistive device. This knowledge is crucial to develop and enhance clinical treatment programs in physical rehabilitation that improve functional outcomes and facilitate the learning process related to assistive devices used by impaired individuals.
| Seanez-Gonzalez, Ismael; Pierella, Camilla; Farshchiansadegh, Ali et al. (2017) Static Versus Dynamic Decoding Algorithms in a Non-Invasive Body-Machine Interface. IEEE Trans Neural Syst Rehabil Eng 25:893-905 |
| Seáñez-González, Ismael; Pierella, Camilla; Farshchiansadegh, Ali et al. (2016) Body-Machine Interfaces after Spinal Cord Injury: Rehabilitation and Brain Plasticity. Brain Sci 6: |
