1. Complexity and Variability in Manual Wheelchair Propulsion Jacob J. Sosnoff 1,3, Zahid M. Rampurawala 1, Scott C. Daigle 2, Louis A. DiBerardino 2, Kiwon Park 2, Elizabeth T. Hsiao-Wecksler 2 Departments of Kinesiology and Community Health 1 and Mechanical Science and Engineering 2, Center for Advanced Study 3 University of Illinois at Urbana-Champaign 1. Introduction  There is growing evidence that variation in movement output provides unique information concerning underlying control and dysfunction [1].  It has been suggested that as individuals develop proficiency in a motor skill their output becomes less variable and more complex [2].  There has been a lack of research examining variability in wheelchair propulsion and how it changes with expertise. 2. Objective  The purpose of this research was to quantify the dynamic variability and complexity of upper arm motion during manual wheelchair propulsion as a function of speed in expert and novice wheelchair users. 3. Theory  Phase-portrait representations of upper limb segment were used to quantify complexity and variability of manual wheelchair propulsion [3]. Phase portraits are cyclic, dynamic representations of motion obtained by plotting a position value against its velocity.  Complexity was quantified by assessing the frequency content of phase portraits. Elliptical Fourier Analysis (EFA) performed on 20 propulsion cycles of the upper arm using MATLAB. Number of harmonics required to characterize 99.9% of phase-portrait data were calculated for each trial. Greater the number of harmonics, more complex the propulsion pattern.  Variability measures were based on the movement of phase portrait centroid over consecutive propulsion cycles. Centroid area  bivariate 95% confidence ellipse area swept by the centroids over 20 propulsion cycles. Centroid drift  path length or total point-wise Cartesian distance that the centroid travelled on the phase plane over 20 propulsion cycles. 6. Discussion  Table 1 indicates a pattern of decreasing number of harmonics with increase in propulsion speeds for both the expert and novice wheelchair users. More harmonics (higher frequencies) are required to accurately describe more complex shapes, hence, propulsion patterns at slow speeds are more complex than those at fast speeds.  The difference in centroid drift area values between the two user groups increases with increase in propulsion speeds. This indicates that the novice user group has a much smaller range as compared to the expert user. Slower speeds resulted in more complex and less variable motion patterns. Moreover, the experienced wheelchair user demonstrated significantly greater adaptability as a function of task constraints. 5. Results Phase portraits of the upper arm as a function of propulsion speed (left: slow, right: fast) over 20 cycles of novice wheelchair user. Table 1. Number of harmonic frequencies required for fitting phase portraits of 20 cycles each at 3 speeds of propulsion. SD=Standard Deviation Table 2. Values of centroid drift areas for phase portraits of 20 cycles each at 3 speeds of propulsion. SD=Standard Deviation 4. Methods  Expert and novice wheelchair users were tested using a 10-camera Motion Analysis system  Manual wheelchair propulsion on exercise rollers  3 speeds of propulsion: slow (0.7m/s), moderate (1.1m/s) and fast (1.8m/s)  2 minute trial at each speed Retro-reflective markers captured by the Cortex software Side view of subject being tested. Front view of subject being tested 7. References & Acknowledgements [1] Davids K, Bennett S and Newell K. Variability in the movement system: A multidisciplinary perspective. Human Kinetics, Champaign IL, 2006. [2] Newell K and Vaillancourt D. Dimensional change in motor learning. Human Movement Science 20(4-5): 695-715, 2001. [3] DiBerardino L, Polk J, Rosengren K, Spencer-Smith J and Hsiao-Wecksler E, Quantifying complexity and variability in phase portraits of gait, Clinical Biomechanics, accepted pending revision, 2009. Acknowledgements: Funding was provided in part by grants from the NSF (grant #0727083), Mary J. Neer Disability Fund and a seed grant from the Beckman Institute. JJS was supported in part by a Center for Advanced Studies Research Fellowship and ZMR was supported by the Chittenden Fellowship. Angular Velocity (radians/s) Angular Position (radians) SlowModerateFastMeanSD Expert19016311815736 Novice16815314415512 SlowModerateFastMeanSD Expert0.030.050.190.09 Novice0.03 0.060.040.02 Right upper arm Left upper arm Right shoulderLeft shoulder Left wrist Right wrist