Complexity and Variability in Manual Wheelchair Propulsion
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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 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 Velocity (radians/s) Angular Position (radians) Angular Position (radians) Slow Moderat e Fast Mean SD Expert 190 163 118 157 36 Novice 168 153 144 155 12 Slow Moderat e Fast Mean SD Expert 0.03 0.05 0.19 0.09 0.09 Novice 0.03 0.03 0.06 0.04 0.02 Right upper arm Left upper arm Right shoulder Left shoulder Left wrist Right wrist
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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 - PowerPoint PPT Presentation
Transcript of Complexity and Variability in Manual Wheelchair Propulsion
Complexity and Variability in Manual Wheelchair PropulsionJacob J. Sosnoff1,3, Zahid M. Rampurawala1, Scott C. Daigle2, Louis A. DiBerardino2, Kiwon Park2, Elizabeth T. Hsiao-Wecksler2
Departments of Kinesiology and Community Health1 and Mechanical Science and Engineering2 , Center for Advanced Study3
University of Illinois at Urbana-Champaign
1. IntroductionThere 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 toquantify 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. DiscussionTable 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 systemManual wheelchair propulsion on exercise rollers3 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.
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Angular Position (radians) Angular Position (radians)
Slow Moderate Fast Mean SD
Expert 190 163 118 157 36
Novice 168 153 144 155 12
Slow Moderate Fast Mean SD
Expert 0.03 0.05 0.19 0.09 0.09
Novice 0.03 0.03 0.06 0.04 0.02Right upper armLeft upper arm
Right shoulder Left shoulder
Left wristRight wrist
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