EMBEDDED ARTS FOR
MOVEMENT RETRAINING
Lise Worthen-Chaudhari
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.
Therapy and Neurorehab
“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
http://www.youtube.com/watch?v=MABD7sYplkk
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.
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
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.
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 experiences Worthen-Chaudhari (2011), Modugno (2011)
Implicit & Immersive
• Acknowledged for importance in cognitive
knowledge construction but underused for
physical knowledge construction
• Participation and Engagement
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.
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
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
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.
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 NeuroRecovery
Network and Dodd Inpatient clinics at OSUWMC, my children and my
husband, Dr. Ajit Chaudhari.
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
Future Directions
• Phase II Effectiveness Study
• Implement programs found to be feasible and
effective (Dodd Hospital - all floors)
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.
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.