EEG-Based Brain Computer Interface to Control FES: A Program Proposal

Abigail Roth, OTS and Dorothy Farrar Edwards, PhD Occupational Therapy Program, Department of Kinesiology ~ University of Wisconsin-Madison

BCI IN THE CLINIC

TERMINATION OF TREATMENT

ACKNOWLEDGEMENTS

Intended population  Individuals who have experienced a stroke  Ability to maintain high degree of concentration

Evaluation  Canadian Occupational Performance Measure (COPM)  Activity Card Sort (ACS)  Specific measures of motor function as necessary *Functional task(s) chosen to address in therapy

Examples include:  Sewing tasks  Cooking tasks  Feeding tasks

Session Preparation  EEG cap  FES electrode placement based on desired function

Session Client told via computer screen one of four commands:  Attempt to relax affected UE  Attempt to carryout functional task with affected UE  Imagine relaxing affected UE  Imagine engaging in functional task with affected UE

If EEG signal surpasses a pre-determined threshold, FES is activated, stimulating the selected muscle(s).

By requiring a high degree of active engagement, it is believed that motor learning will occur as a result of BCI use. Similarly, placing functional demands on the central nervous system (CNS) encourages lasting changes; cortical recovery should occur, ultimately improving occupational performance.

Special thanks to Léo Walton, Dorothy Edwards, Julia Wilbarger, and Veena Nair for their support. This project was funded by the Wallace H. Coulter Foundation.

REFERENCES

Duration of treatment will vary with each client Treatment should cease when Client:  Is satisfied  Spontaneously, consistently uses effective strategies during occupations  Reverts to inefficient movement patterns with removal of treatment  Lacks improvement in spite of personal and environmental modifications being made

OT TASK-ORIENTED APPROACH  Contemporary model of motor behavior and learning  Uses meaningful occupations as the means for change  Views Client as an active participant in the therapy process  Emphasizes the interdependence of person, environment, occupational performance, and role performance This approach will be used to frame this intervention.

Bach-y-Rita, P. (1993). Recovery from brain damage. Journal of Neurological Rehabilitation, 6, 191-199.

Baum, C.M., & Edwards, D. (2008). Activity Card Sort (2nd ed.). Bethesda, MD: AOTA Press.

Daly, J.J., Cheng, R., Rogers, J., Litinas, K., Hrovat, K. & Dohring, M. (2009). Feasibility of a new application of noninvasive brain computer interface (BCI): A case study of training for recovery of volitional motor control after stroke. Journal of Neurologic Physical Therapy, 33, 203-211.

Law, M., Baptiste, S., Carswell, A., McColl, M., Polatajko, H., Pollock, N. (1998). Canadian Occupational Performance Measure (3rd ed.) Toronto: CAOT Publications ACE.

Mathiowetz, V. & Bass Haugen, J. (1994). Motor behavior research: Implications for therapeutic approaches to central nervous system dysfunction. American Journal of Occupational Therapy, 48(8), 733-745.

It is expected that BCI use will lead to cortical recovery and improved upper extremity (UE) functional use as measured by task performance and functional neuroimaging.

EXPECTED RESULTS

INTRODUCTION

 Stroke is the leading cause of long-term disability in the US.

 Fifty percent of stroke survivors have some hemiparesis.

 The effectiveness of current treatment techniques has been questioned.

 A new intervention being considered is an electro-encephalogram (EEG) based brain computer interface (BCI).

 EEG-based BCI uses a person’s brain activity to control an electronic device- in this case, functional electrical stimulation (FES).

 Currently research is being done to test the effectiveness of an EEG-based BCI to control FES for treating hemiparesis after stroke.

Provided by a team of OT, Neurologist, and Engineer  OT: Scope of hemiparesis and its effect on ability to perform activities of daily living (ADLs).  Neurologist: Functional and stroke neuroanatomy  Engineer: Explanation of closed-loop system  Team: Discussion of functional neuroimaging

TRAINING