1. Gait Symmetry in Subjects with Multiple Sclerosis Stephanie Crenshaw, James Richards, Caralynne Miller Department of Health, Nutrition, and Exercise Sciences University of Delaware American College of Medicine 53 rd Annual Meeting May 31-June 3, 2006 Denver, Colorado

2. Purposes  To explain newly developed Symmetry Analysis Method  To apply Symmetry Analysis Method to Clinical Population of Subjects with Multiple Sclerosis

3. MULTIPLE SCLEROSIS Disease of the CNS Characterized by demyelinated areas/axon damage in brain and spinal cord Damage interferes with nerve signals that control muscle coordination, strength, sensation, and vision

4. Signs and Symptoms Vision disturbances Numbness/weakness Tingling/pain Dizziness Unsteady Gait Fatigue

5. Measure of Disease Severity Expanded Disability Status Scale The EDSS is based upon Neurological testing of Functional Systems (CNS areas regulating body functions):CNS  Pyramidal (Walking Ability) Pyramidal  Cerebellar (Coordination) Cerebellar  BrainStem (Speech and Swallowing) BrainStem  Sensory (Touch and Pain) Sensory  Bowel and Bladder Bowel and Bladder  Visual Visual  Mental Mental  Other (includes any other Neurological findings due to MS) Other

6. EDSS Steps 1.0-4.5 patients are fully ambulatory  Precise step number determined by FS score Steps 5.0-9.5 defined by impairment to ambulation Steps 6.0-7.0  need assistive device Steps 7.5-9.5  Wheelchair-bound/bedridden

7. MS Gait Compared to healthy controls:  Decreased velocity, stride length, range of motion As disease severity increases:  Variability of 25 FTW, Stance phase percentage increase  Gait Speed, Stride Length, Stride Rate decrease With increased fatigue,  no change in balance performance (Frzovic, 2000) gait speed (Morris, 2002) stride length (Morris, 2002) double limb support duration (Morris, 2002)  Velocity, Peak Knee Flexion, Ankle Power Generation Decreased (Crenshaw, in press)

8. Symmetry Symmetry measures often used to assess populations with unilateral injuries/disabilities MS lesions  develop in a random pattern in CNS  are distributed unequally between right and left hemispheres of the brain MS subjects  Unequal stance duration  Unequal step length http://mccoy.lib.siu.edu/projects/mgrey/pathology/brain/multiple_selerosis/

9. Symmetry Definition:  Both limbs are behaving identically Measures of Symmetry  Symmetry Index  Symmetry Ratio  Statistical Methods

10. Symmetry Index SI when it = 0, the gait is symmetrical Differences are reported against their average value. If a large asymmetry is present, the average value does not correctly reflect the performance of either limb Robinson RO, Herzog W, Nigg BM. Use of force platform variables to quantify the effects of chiropractic manipulation on gait symmetry. J Manipulative Physiol Ther 1987;10(4):172–6.

11. Symmetry Ratio Limitations: relatively small asymmetry and a failure to provide info regarding location of asymmetry Low sensitivity Seliktar R, Mizrahi J. Some gait characteristics of below-knee amputees and their reflection on the ground reaction forces. Eng Med 1986;15(1):27–34.

12. Statistical Measures of Symmetry Correlation Coefficients Principal Component Analysis Analysis of Variance Use single points or limited set of points Do not analyze the entire waveform Sadeghi H, et al. Symmetry and limb dominance in able-bodied gait: a review. Gait Posture 2000;12(1):34–45. Sadeghi H, Allard P, Duhaime M. Functional gait asymmetry in ablebodied subjects. Hum Movement Sci 1997;16:243–58.

13. New Method - Eigenvector Analysis The method proposed utilizes eigenvector analysis to compare time-normalized right leg gait cycles to time-normalized left leg gait cycles. Paired data points from the right and left waveforms are entered into an m row x n column matrix, where each pair of points is one of the m number of rows. Singular Value Decomposition (SVD) is then performed on this matrix to determine the principal and secondary eigenvectors.

14. Eigenvector Analysis Use eigenvector analysis to determine Waveform Trend Similarity Trend Similarity is defined as the ratio of the variance about the principle eigenvector to the variance along the principle eigenvector

15. Additional Symmetry Measures Range ratio quantifies the difference in range of motion of each limb, and is calculated by dividing the range of motion of the right limb from that of the left limb. Range offset, a measure of the differences in operating range of each limb, is calculated by subtracting the average of the right side waveform from the average of the left side waveform.

16. Trend Symmetry Expressed as ratio of the variance about eigenvector to the variance along the eigenvector Trend Symmetry: 5.17%Range Amplitude Ratio: 0.79, Range Offset:0

17. Range Amplitude Ratio Expressed as a ratio of the range of motion of the left limb to that of the right limb Range Amplitude Ratio: 2.0Trend Symmetry: 0.0, Range Offset: 19.45

18. Range Offset Calculated by subtracting the average of the right side waveform from the average of the left side waveform Range Offset: 10.0Trend Symmetry: 0.0, Range Amplitude Ratio: 1.0

19. Final Adjustments A second measure of symmetry examines the phase relationship between waveforms. To do this, we calculated the trend similarity for the sagittal plane joint angle between the normalized right and left limb waveforms. Then, one waveform was phase-shifted in 1- percent increments (e.g. sample 100 becomes sample 1, sample 1 becomes sample 2…) and the trend similarity was recalculated for each shift. The phase shift was then determined by identifying the index at which the smallest value for trend similarity occurred. The minimum trend similarity values are also reported.

20. Symmetry Measures Trend Symmetry  Quantifies waveform trend similarity Range Amplitude Ratio  quantifies the difference in range of motion of each limb Range Offset  a measure of the differences in operating range of each limb

21. Methods - Subjects 13 with MS  Age 44.4±10.6 years  Height 167.0±8.7 cm  Mass 79.1±20.1 kg  EDSS average 3.5 (range 2.5-4.5) 8 Healthy Controls  Age 40.9±9.6 years  Height 167.4±14.6 cm  Mass 72.6±14.2 kg

22. Methods – Data Collection Data Collection:  8 Motion-Analysis Cameras 60 Hz  2 AMTI Force Plates 960 Hz  2 Gait Analysis Conditions Fresh Fatigued

23. Methods – Data Analysis Created Ensemble averages of 15 gait cycles  sagittal plane kinematics for fresh and fatigued conditions Calculated Symmetry values  Affected/Unaffected – MS subjects  Left/Right – HC subjects Hip, Knee, and Ankle values were summed to determine composite symmetry measures

24. Methods – Data Analysis (HC)

25. Methods – Data Analysis (MS Fresh)

26. Methods – Data Analysis (MS Fatigued)

27. Methods – Statistics One-tailed independent samples t-test  Changes between fresh conditions of MS and control subjects One-tailed dependent samples t-test  Changes between fresh and fatigued conditions for MS subjects Correlation  EDSS and differences between fresh and fatigued conditions

28. Results – MS vs. Control example HC MS

29. Results – MS and Controls MS subjects generally more asymmetrical than controls p<0.05

30. Results – Fresh vs. Fatigued example Fresh Fatigued

31. Results – MS Fresh and Fatigued MS subjects generally become more asymmetrical when fatigued * p<.10

32. Results – Symmetry and EDSS No significant correlations between disease severity and changes in symmetry from fresh to fatigued conditions

33. Conclusions MS subjects are less symmetrical than healthy control subjects MS subjects generally become less symmetrical when fatigued There was no significant correlation between disease severity and changes in symmetry measures from fresh to fatigued conditions.

34. Ankle Joint Trend Symmetry Phase Shift (% Cycle Min Trend Symmetry Range Amplitude Range Offset 95% CI0 – 6.30-2.2 – 2.60 – 4.940.70 - 1.27-6.8 – 6.2 Unbraced0.9411.370.893.8 Braced29.01-324.761.72-5.6 Amputee17.560 1.30-3.7 Symmetry Example…Ankle Joint