Gait Symmetry With Application to

Subjects with Multiple Sclerosis

Stephanie Crenshaw, James Richards, Caralynne MillerDepartment of Health, Nutrition, and Exercise SciencesUniversity of DelawareAmerican College of Medicine 53rd Annual MeetingMay 31-June 3, 2006 Denver, Colorado

Gait Symmetry

Modified by W. Rose from the original presentation to emphasize the trend symmetry measure. Trend symmetry values converted to new scale where +1=exact symmetry, -1=exact anti-symmetry, 0=no symmetry.

Matlab code to compute trend symmetry and related quantities: trendsymmetry.m. Needs two input files, e.g. x1_trendsymtest.txt, x21…txt, or knee_abdang_R and …_L.txt, etc.

Labview code to compute trend symmetry and related quantities: MainInteractiveWCR.vi. Needs one Orthotrak NRM file as input, e.g. 0.NRM.

Purposes

1. To explain newly developed Symmetry Analysis Method

2. To apply Symmetry Analysis Method to Clinical Population of Subjects with Multiple Sclerosis

Symmetry

Definition: Both limbs are behaving identically

Measures of Symmetry Symmetry Index Symmetry Ratio Statistical Methods

Symmetry Index

When SI = 0, gait is symmetrical Differences are relative to 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.

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LR

LR

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XXSI

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.

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R

X

XSR

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: areview. 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.

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 2 column matrix, where each pair of points is one of the m rows. Singular Value Decomposition (SVD) is then performed on this matrix to determine the principal and secondary eigenvectors.

Eigenvector Analysis

Use eigenvector analysis to determine Waveform Trend Similarity

Trend Similarity (or Symmetry) is defined as

( . . . )( . . . )

.

1 Variance about Principal EigenvectorVariance along Principal Eigenvector

Trend Symmetry

where +/- depends on slope of principal eigenvector (+ = symmetric, - = antisymmetric)

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.

Trend Symmetry

Expressed as 1-(ratio of the variance about eigenvector to the variance along the eigenvector)

Trend Symmetry: 0.948 Range Amplitude Ratio: 0.79, Range Offset:0

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: 2.0 Trend Symmetry: 1.0, Range Offset: 19.45

Range Offset

Calculated by subtracting the average of the right side waveform from the average of the left side waveform

Range Offset: 10.0 Trend Symmetry: 1.0, Range Amplitude Ratio: 1.0

Final Adjustments Trend similarity can be used to estimate

the phase relationship between waveforms.

Phase-shift one waveform in 1-percent increments (e.g. sample 100 becomes sample 1, sample 1 becomes sample 2…), up to a max shift of +-20%. Compute trend similarity at each phase shift.

Phase shift with greatest trend similarity is an estimate of the phase offset between the waves.

Ankle Joint

Trend Symmetry

Phase Shift (% Cycle)

Max Trend Symmetry

Range Amplitude

Range Offset

95% CI 0.937-1.00

-2.2 – 2.6 0 – 4.94 0.70 - 1.27

-6.8 – 6.2

Unbraced 0.99 1 0.99 0.89 3.8

Braced 0.71 -3 0.75 1.72 -5.6

Amputee 0.82 0 0.82 1.30 -3.7

Symmetry Example…Ankle Joint

These trend symmetry values are on the new scale, where +-1=perfect symmetry, 0=no symmetry.

Symmetry Measures Applied to Patients with MS

Remainder of this presentation describes the application of the symmetry measures to subjects with MS and healthy controls.

Methods - Subjects

13 with MS Age 44.4±10.6 yrs 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 yrs Height 167.4±14.6

cm Mass 72.6±14.2 kg

Methods – Data Collection

Data Collection: 8 Motion-Analysis Cameras

60 Hz 2 AMTI Force Plates

960 Hz 2 Gait Analysis Conditions

Fresh Fatigued

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

Methods – Data Analysis (HC)

HIP KNEE ANKLE SUM Trend Symmetry 0.01 0.36 0.73 1.01 Range Amplitude Ratio 0.94 0.93 0.88 2.75 Range Offset -0.72 0.02 0.49 0.2

These trend symmetry values are on the old scale, where 0=perfect symmetry, 1=no symmetry. Couldn’t change the snapshot of a table.

Methods – Data Analysis (MS Fresh)

HIP KNEE ANKLE SUM Trend Symmetry 0.23 2.55 6.93 9.71 Range Amplitude Ratio 1.31 1.14 0.65 3.1 Range Offset -4.48 1.49 1.34 -1.65

These trend symmetry values are on the old scale, where 0=perfect symmetry, 100=no symmetry. Couldn’t change the snapshot of a table.

Methods – Data Analysis (MS Fatigued)

HIP KNEE ANKLE SUM Trend Symmetry 0.79 5.86 3.52 10.17 Range Amplitude Ratio 1.55 1.07 0.75 3.37 Range Offset -6.08 -0.39 1.39 -5.08

These trend symmetry values are on the old scale, where 0=perfect symmetry, 100=no symmetry. Couldn’t change the snapshot of a table.

Results – MS vs. Control example

HC

MS

Results – MS and Controls MS subjects generally more

asymmetrical than controls

* p<0.05

MS HC Trend Symmetry * 3.6 ± 2.6 1.1 ± 0.5 Range Amplitude Ratio 3.1 ± 0.3 3.0 ± 0.2 Range Offset -1.1 ± 5.7 -1.6 ± 4.9 Phase Shift * 2.7 ± 1.6 1.3 ± 0.5 Adjusted Trend Symmetry * 2.6 ± 2.2 0.8 ± 0.5

These trend symmetry values are on the old scale, where 0=perfect symmetry, 100=no symmetry. Couldn’t change the snapshot of a table.

Results – Fresh vs. Fatigued example

Fresh

Fatigued

Results – MS Fresh and Fatigued MS subjects generally become more

asymmetrical when fatigued

* p<.10

FRESH FATIGUED Trend Symmetry * 3.6 ± 2.6 4.6 ± 3.3 Range Amplitude Ratio * 3.1 ± 0.3 3.2 ± 0.3 Range Offset -1.1 ± 5.7 -0.8 ± 6.4 Phase Shift * 2.7 ± 1.6 3.5 ± 2.7 Adjusted Trend Symmetry 2.6 ± 2.2 3.0 ± 2.4

These trend symmetry values are on the old scale, where 0=perfect symmetry, 100=no symmetry. Couldn’t change the snapshot of a table.

Results – Symmetry and EDSS

No significant correlations between disease severity and changes in symmetry from fresh to fatigued conditions

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The trend symmetry values are on the old scale, where 0=perfect symmetry, 100=no symmetry. Couldn’t change the snapshot of a figure.

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.