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An adaptive brain actuated system for augmenting rehabilitation.

Roset SA, Gant K, Prasad A, Sanchez JC - Front Neurosci (2014)

Bottom Line: For people living with paralysis, restoration of hand function remains the top priority because it leads to independence and improvement in quality of life.In approaches to restore hand and arm function, a goal is to better engage voluntary control and counteract maladaptive brain reorganization that results from non-use.By continuously adapting to the user's brain activity, similar adaptive systems could be used to support clinical brain-computer interface neurorehabilitation over multiple days.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, University of Miami Coral Gables, FL, USA.

ABSTRACT
For people living with paralysis, restoration of hand function remains the top priority because it leads to independence and improvement in quality of life. In approaches to restore hand and arm function, a goal is to better engage voluntary control and counteract maladaptive brain reorganization that results from non-use. Standard rehabilitation augmented with developments from the study of brain-computer interfaces could provide a combined therapy approach for motor cortex rehabilitation and to alleviate motor impairments. In this paper, an adaptive brain-computer interface system intended for application to control a functional electrical stimulation (FES) device is developed as an experimental test bed for augmenting rehabilitation with a brain-computer interface. The system's performance is improved throughout rehabilitation by passive user feedback and reinforcement learning. By continuously adapting to the user's brain activity, similar adaptive systems could be used to support clinical brain-computer interface neurorehabilitation over multiple days.

No MeSH data available.


Related in: MedlinePlus

Flowchart of the steps of the experiment. Flowchart shows the preliminary steps of the experiment and how the final step can be repeated.
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Figure 2: Flowchart of the steps of the experiment. Flowchart shows the preliminary steps of the experiment and how the final step can be repeated.

Mentions: Adaptive BCI usage was broken down into several intermediate steps (Figure 2). Representative ErrPs were collected in the preliminary session and used to develop the critic through supervised learning (Prechelt, 1998). Once the critic was created, the weights of the actor were initialized to random initial values and trained through RL and feedback from the critic. After the first closed-loop session, in which the weights are initialized to random values, all subsequent closed-loop sessions used the weights from the previous session with no offline adjustments.


An adaptive brain actuated system for augmenting rehabilitation.

Roset SA, Gant K, Prasad A, Sanchez JC - Front Neurosci (2014)

Flowchart of the steps of the experiment. Flowchart shows the preliminary steps of the experiment and how the final step can be repeated.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4264503&req=5

Figure 2: Flowchart of the steps of the experiment. Flowchart shows the preliminary steps of the experiment and how the final step can be repeated.
Mentions: Adaptive BCI usage was broken down into several intermediate steps (Figure 2). Representative ErrPs were collected in the preliminary session and used to develop the critic through supervised learning (Prechelt, 1998). Once the critic was created, the weights of the actor were initialized to random initial values and trained through RL and feedback from the critic. After the first closed-loop session, in which the weights are initialized to random values, all subsequent closed-loop sessions used the weights from the previous session with no offline adjustments.

Bottom Line: For people living with paralysis, restoration of hand function remains the top priority because it leads to independence and improvement in quality of life.In approaches to restore hand and arm function, a goal is to better engage voluntary control and counteract maladaptive brain reorganization that results from non-use.By continuously adapting to the user's brain activity, similar adaptive systems could be used to support clinical brain-computer interface neurorehabilitation over multiple days.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, University of Miami Coral Gables, FL, USA.

ABSTRACT
For people living with paralysis, restoration of hand function remains the top priority because it leads to independence and improvement in quality of life. In approaches to restore hand and arm function, a goal is to better engage voluntary control and counteract maladaptive brain reorganization that results from non-use. Standard rehabilitation augmented with developments from the study of brain-computer interfaces could provide a combined therapy approach for motor cortex rehabilitation and to alleviate motor impairments. In this paper, an adaptive brain-computer interface system intended for application to control a functional electrical stimulation (FES) device is developed as an experimental test bed for augmenting rehabilitation with a brain-computer interface. The system's performance is improved throughout rehabilitation by passive user feedback and reinforcement learning. By continuously adapting to the user's brain activity, similar adaptive systems could be used to support clinical brain-computer interface neurorehabilitation over multiple days.

No MeSH data available.


Related in: MedlinePlus