Embedded Arts for Movement Retraining

1. Lise Worthen-Chaudhari Embedded Arts for Movement Retraining

2. Description Embedded Arts is an interactive computer program designed as a rehabilitation biofeedback tool. The purpose of the system is to tap into artistic and creative neural pathways during performance of standard rehabilitation exercises. Using real-time data from biophysical sensors, the program integrates creative process within rehabilitation protocols by translating movement into art.

3. Therapy and Neurorehab http://www.youtube.com/watch?v=MABD7sYplkk “This ability of our neural wiring to reroute when given the right stimuli can be a powerful agent for recovery and has, since the 1980s, emerged as the most promising phenomenon for facilitating neurorehabilitation.” Nudo & Dancause (2007) in Brain Injury Medicine: Principles and Practices

4. Purpose enable patients to create fun, individualized images that would be  aesthetically and kinesthetically satisfying, but that would also represent a patient's personal healing through the process of activity-based medicine.

5. Hypothesis • Embedding interactive arts processes within rehabilitation exercises may improve outcomes • Increasing gains in physical tacit knowledge construction • Improving patient attention and compliance • Enhancing clinician tracking

6. Leveraged Phenomenon • Implicit Learning Gentile (1998 ) • Can’t be imparted explicitly from outside. • Immersive Learning Mirelman (2010), Keshner • Multi-sensory (aka multi-modal) • Both Deeply felt on embodied level during performance.

7. Implicit & Immersive • Research • Stroke Patton et al. (2004, 2005); Pohl et al. (2006); Boyd et al. (2010) , Mirelman (2010) • Parkinson’s Witt et al. (2006), Keshner, Thaut • Examples • Robotics & video gaming • Arts generative experiencesWorthen-Chaudhari(2011), Modugno (2011)

8. Implicit & Immersive Acknowledged for importance in cognitive knowledge construction but underused for physical knowledge construction Participation and Engagement

9. Design Research • Asked the experts • Patients, artists, and clinicians • Feedback was iterative process of using the program, getting feedback, implementing improvements (exploration within the exploration) • Results • Practical issues addressed • Dancers suggested explicit use instructions while patients tended to figure out for themselves. • Artists were logical/pragmatic while clinicians were artistic.

10. Feasibility Study • 8 patients single session • 6 patients longitudinal study • Results • No AE • Feasible to incorporate the technology in clinical practice • Accepted and desired by patients & clinicians • Limiting factors: • Time for computer to boot • IT support for secure data storage • Access to EA “concierge” help as needed

11. Summary • Interactive arts technologies enhance standard rehabilitation • Embedding creative process within rehabilitation may improve outcomes • Outputting artistic work from rehabilitation exercises adds economic element to rehabilitation endeavors • Motion capture data transformed for feedback and recorded for quantitative outcomes analysis in the clinic and home health settings • Artistic nature of personal movement in a rehabilitation setting is explored

12. Conclusion In the rehabilitation paradigm, movement is medicine. In the dance paradigm, movement is art. Often, a single movement can be both. Perhaps, through the phenomemon of movement, the arts and medicine are more interdependent than we previously imagined. Worthen-Chaudhari(2011) New Partnerships Between Dance and Neuroscience: Embedding the Arts for Neurorecovery, Dance Research Journal, 29.2, p 469.

13. Acknowledgements This project has been partially funded by the College of Arts & Sciences, Department of Dance, Department of Physical Medicine and Rehabilitation, and the Medical Center Alumni Association at The Ohio State University. Special thanks to: Helen Alkire, Brad Burns, Chuck Crosby, John Griffith, Ashley Hahn, Joseph F. Kuspan, Jill Sarina, Aaron Wolfe (artists), Michael Kelly Bruce, David Covey, Susan Petry (Dance), D. Michele Basso (Health & Rehab Sciences), W. Jerry Mysiw (PM&R), staff of the NeuroRecoveryNetwork and Dodd Inpatient clinics at OSUWMC, my children and my husband, Dr. AjitChaudhari.

14. Design constraints • Action painting aesthetic “…shifted the emphasis from the object [of art] to the struggle itself, with the finished painting being only the physical manifestation, a kind of residue, of the actual work of art, which was in the act or process of the painting’s creation.” http://en.wikipedia.org/wiki/Action_painting • Random aesthetic elements

15. Future Directions • Phase II Effectiveness Study • Implement programs found to be feasible and effective (Dodd Hospital - all floors)

16. References Boyd LA, Quaney BM, Pohl PS, Winstein CJ. Learning implicitly: effects of task and severity after stroke. Neurorehabil Neural Repair 21: pp.444–454, 2007. Brewer B, McDowell SK, Worthen-Chaudhari LC. Post-stroke upper extremity rehabilitation: a review of robotic systems and clinical results. Topics in Stroke Rehab 14(6): pp. 22-44, 2007. Cleeremans A. Implicit learning. In: Nadel L, ed. Encyclopedia of Cognitive Science. London: Nature Publishing Group, 2003. Foerde K. Implicit Learning and Memory: Psychological and Neural Aspects. Encyclopedia of Behavioral Neuroscience, pp. 84-93, 2010. Job Accommodation Network by the Office of Disability Employment Policy, “Network Fact Sheet Series: Self employment for artists with disabilities”, viewed February 11, 2010 <www.jan.wvu.edu/entre/pubs/Entre_Artists.doc>. Meulemans T, Van der Linden M. Implicit learning of complex information in amnesia. Brain and Cognition 52(2), pp. 250-257, 2003. Patton JL, Mussa-Ivaldi FA. Robot-assisted adaptive training: custom force fields for teaching movement patterns. IEEE Trans Biomed Eng. 51: pp. 636–646, 2004. Patton JL, Stoykov ME, Kovic M, Mussa-Ivaldi FA. Evaluation of robotic training forces that either enhance or reduce error in chronic hemiparetic stroke survivors. Exp Br Res 168 (3): pp.363-383, 2005.

17. References Pohl PS, McDowd JM, Filion D, Richards LG, Stiers W. Implicit learning of a motor skill after mild and moderate stroke. Clin Rehabil.20: pp.246–253, 2006. Thaut MH, McIntosh GC, Rice RR, Miller RA. Rhythmic auditory stimulation in gait training for parkinson’s disease patients. Movement Disorders 11(2): pp.193-200, 2004. The New York Times, “Learning his body; learning to dance”, viewed February 11, 2010 <http://www.nytimes.com/2009/11/25/arts/dance/25palsy.html>. Whitall J, Waller SM, Silver KHC, Macko RF. Repetitive bilateral arm training with rhythmic auditory cueing improves motor function in chronic hemiparetic stroke. Stroke 31: pp. 2390-2395, 2000. Witt K, Daniels C, Daniel V, Schmitt-Eliassen J, Volkmann J, Deuschle G. Patients with Prkinson’s disease learn to control complex systems – an indication for intact implicit cognitive skill learning. Neuropsychologia 44(12), pp. 2445-2451, 2006. Yadev V, Schmiedeler J, McDowell SK, Worthen-Chaudhari LC. Quantifying age-related differences in human reaching while interacting with a rehabilitation robotic device, Journal of Applied Biomechanics and Bionics accepted 2010.