Results
Demographic charateris/cs (Table 2):
• pMS were around 12.3yo older than HV (p<0.001)
• no other significant differences were observed between groups
Efficiency of gait descriptors (Fig 3)
Along the T25FW, administered according to the MSFC recommandaLons2 (i.e. « as fast as possible »), significant differences were obviously found between groups
when considering the mean walking speed (Fig 3A). Other gait descriptors conceptually directly related to walking speed displayed the same paRern of alteraLon, such as individual foot mean walking speed (Fig 3B and 3C) or gait cycle Lme (Fig 3D)
People with MS (all)
P295
Detec3on and Quan3fica3on of Efficiency and Quality of
Gait Impairment in Mul3ple Sclerosis through Foot Path Analysis
R. Phan-‐Ba1,2, S. Piérard3, G. Moonen2, M. Van Droogenbroeck3, S. Belachew1,2
1: MYelin Disorders REseArch teaM (MYDREAM) (Liege, BE); 2: C.H.U. of Liege, Department of Neurology (Liege, BE); 3: INTELSIG Laboratory, Montefiore Ins/tute (Liege, BE)
Disclosures
R. Phan-‐Ba serves on scienLfic advisory boards for Genzyme-‐Sanofi AvenLs and has received funding for travel from Genyzme-‐Sanofi AvenLs, Bayer Schering Pharma and Biogen Idec.
S. Belachew serves on scienLfic advisory boards for Bayer Schering Pharma, Biogen Idec, Genzyme-‐Sanofi AvenLs, NovarLs Pharma, and Merck-‐ Serono; has received funding for travel and speaker honoraria from Bayer Schering Pharma, Biogen Idec, Genzyme-‐Sanofi AvenLs, NovarLs Pharma, TEVA, and Merck-‐Serono; and has received research and/or educaLonal grant supports from Biogen Idec, Merck-‐ Serono, Sanofi-‐AvenLs, TEVA, and NovarLs Pharma.
S. Pierard and M. Van Droogenbroeck have nothing to disclose.
28th Congress of the European Commi>ee for Treatment and Research In MulBple Sclerosis 10-‐13th October 2012, Lyon, France
ABSTRACT
IntroducLon: Walking speed is generally considered as the best outcome measure in trials for people with mulLple sclerosis (pMS). We recently designed a device based on range laser scanner capable to track feet paths of walking subjects. Our purpose was to explore gait descriptors of pMS and compare them with those of healthy volunteers (HV). Methods: Fourty-‐four pMS (considered as moderatly or highly disabled according to a cut-‐off EDSS value of 3.0) and 28 HV performed 4 walking tasks along 2 trajectories in 3 walking modes. Twenty-‐six gait descriptors crudely dichotomized in « efficiency» and « quality » of gait were compared in the 2 populaLons using unpaired t-‐tests. Results: (i) apart from an older age in pMS, the two populaLons were comparable, (ii) efficiency of gait descriptors including walking speed disLnguished HV from pMS, and pMS with moderate from pMS with high disability, (iii) quality of gait descriptors were also significantly altered in pMS, including in walking tasks where their walking speed was comparable to that of HV. Conclusions: RLS technology can disLnguish pMS from HV according to (i) more efficiency of gait descriptors than the sole walking speed and (ii) quality of gait descriptors, including in subjects with a « normal » walking speed.
IntroducBon and Purpose
• The vast majority of researchers and clinicians consider walking speed1,2 (WS) measured with a stopwatch as the best outcome measure to quanBfy gait of persons with mulLple sclerosis (pMS)
• We recently designed and validated on healthy voluteers (HV) a device based on range laser scanners technology (Fig 1)3 capable to track feet paths (Fig 2) during various walking tasks, through which several gait descriptors (currently 26) can be measured
• This exploratory study’s purpose was to compare gait descriptors from pMS versus those of HV
Methods
• This study was approved by the local ethics comiRee • Fourty-‐four pMS and 28 HV were recruited
• The design was cross-‐secLonnal
Walking Tasks
• The subjects were asked to walk along two trajectories: (i) a line of 9.62m (25 feet + 2m) and (ii) a 8-‐shaped figure of 20m (Fig 1)
• Four walking tasks were performed: the Timed 25-‐Foot Walk Test (T25FW), the Timed 20-‐Meter Walk Test (T20MW, 1 lap of trajectory ii), the Timed 100-‐Meter Walk Test (T100MW,
5 laps of trajectory ii) and the Timed 500-‐Meter Walk Test (T500MW, 25 laps of trajectory ii). PaLents with an EDSS > 4.0 were asked to walk as far as possible on the T500MW • Three walking modes were studied: preferred pace, as fast as possible and tandem gait (« heel-‐to-‐toe »)
• The walking paradigm used is resumed in Table 1 and took approximately 20 minutes per subject
RLS-‐derived gait descriptors
• Twenty-‐six gait descriptors can be extracted and quanLfied from the recorded foot paths
• A crude dichomizaLon was applied by separaLng efficiency of gait descriptors (EG), i.e. conceptually directly implicated in walking speed from quality of gait descriptors (QG), i.e. without any direct relaLon to walking speed but perhaps related to other gait feature such as balance and propriocepLon
• EG included mean walking speed, mean/maximum lel/right foot speed, gait cycle Lme while QG included mean, maximal and RMS deviaLon from the trajectory, mean interfeet distance, mean lateral interfeet distance, double/single limb support Lme, variability of lel/right foot trajectory and step length asymmetry
Sta/s/cal analysis
• HV (n=28) were compared to pMS (n=44), who were classified and compared according to their EDSS as ≤ 3.0 (n=22) or > 3.0 (n=22)
• Unpaired t-‐test comparison were applied with a two-‐tailed analysis and 0.05 as a level of significance and were performed using the funcLon "t_test" bundled with Octave (hRp://www.gnu.org/solware/octave/) version 3.2.4
Fig 1 The two trajectories surrounded by 4 range laser scanners, viewed from above
Table 1 Order of the walking tasks
T25FW T20MW T100MW T500MW Preferred pace 1, 2 7 10 12
As fast as possible 3, 4 8 11
Tandem gait 5, 6 9
Healthy Volunteers people with MS All EDSS ≤ 3.0 EDSS > 3.0 Number 28 44 22 22
Age (years, mean ± SD) 31.2 ± 1.3 42.5 ± 11.7 39.6 ± 11.8 45.2 ± 11.3
Gender (female, %) 46.4 63.6 68.2 48.1
EDSS (mean ± SD) n.a. 3.3 ± 1.3 2.2 ± 0.7 4.3 ± 0.7
MS type (CIS/RR/P, %) n.a. 14.9/59.6/23.4 31.8/68.2 0/48.1/51.9
Disease dura3on (year, mean ± SD) n.a. 11.7 ± 10.6 8.2 ± 8.6 14.9 ± 11.3 Table 2 Demographic data
0 0.5 1 1.5 2 2.5 3 3.5
healthy volunteers all patients EDSS <= 3.0 EDSS > 3.0
[-] mean velocity [ m / s ] T25FW+ , as fast as possible , 1st try *** ( p = 0.000000 ) *** ( p = 0.000005 ) ** ( p = 0.008850 ) *** ( p = 0.000000 ) 0 0.5 1 1.5 2 2.5 3 3.5
healthy volunteers all patients EDSS <= 3.0 EDSS > 3.0
[-] mean velocity of left foot [ m / s ]
T25FW+ , as fast as possible , 1st try *** ( p = 0.000000 ) *** ( p = 0.000038 ) * ( p = 0.015442 ) *** ( p = 0.000000 ) 0 0.5 1 1.5 2 2.5 3 3.5
healthy volunteers all patients EDSS <= 3.0 EDSS > 3.0
[-] mean velocity of right foot [ m / s ]
T25FW+ , as fast as possible , 1st try *** ( p = 0.000004 ) *** ( p = 0.000008 ) ( p = 0.077239 ) *** ( p = 0.000000 ) 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
healthy volunteers all patients EDSS <= 3.0 EDSS > 3.0
[-] gait cycle [ s ] T25FW+ , as fast as possible , 1st try *** ( p = 0.000261 ) *** ( p = 0.000033 ) ( p = 0.456288 ) *** ( p = 0.000001 ) A B C D
Fig 2 Example of feet path recorded along a distance of 25 feet
Healthy volunteers People with MS (EDSS ≤ 3.0) People with MS (EDSS > 3.0)
Quality of gait descriptors (Fig 4 and 5)
During the same walking test, we observed significant differences between the 3 studied populaLons in gait descriptors apparently unrelated to walking speed, such as the mean deviaLon from the trajectory (Fig 4A), the mean lateral interfeet distance (Fig 4B) or the Lme of double limb support (Fig 4C). InteresLngly, when the subjects were asked to walk along the same distance of 25 feet at their preferred pace, these same differences were present in moderately disabled pMS (Fig 5A), while their walking speed remained unaltered in comparison to HV (Fig 5B).
Figure 3 0 0.5 1 1.5 2
healthy volunteers all patients EDSS <= 3.0 EDSS > 3.0
[-] mean velocity [ m / s ] T25FW+ , comfortable , 1st try *** ( p = 0.000194 ) *** ( p = 0.000536 ) ( p = 0.224169 ) *** ( p = 0.000002 ) 0 0.02 0.04 0.06 0.08 0.1
healthy volunteers all patients EDSS <= 3.0 EDSS > 3.0
[-] mean deviation [ m ] T25FW+ , comfortable , 1st try *** ( p = 0.000277 ) ( p = 0.878774 ) ** ( p = 0.009554 ) ** ( p = 0.007362 ) -0.02 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16
healthy volunteers all patients EDSS <= 3.0 EDSS > 3.0
[-] mean deviation [ m ]
T25FW+ , as fast as possible , 2nd try
*** ( p = 0.000258 ) ( p = 0.453570 ) ** ( p = 0.003968 )
** ( p = 0.006810 )
References
1. Phan-ba et al. Comparison of the timed 25-foot and 100-meter walk as performance measure in multiple sclerosis. Neurorehabilitation and neural repair. 2011 Sep;25(7):672-9 2. Cutter et al. Development of a multiple sclerosis functional composite as a clinical trial outcome measure. Brain. 1999 May;122 (Pt 5):871-82
3. Pierard et al. A new low cost non intrusive feet tracker. Workshop on Circuits, Systems and Signal Processing (ProRISC). 2011 Nov: 382-7
0 0.05 0.1 0.15 0.2 0.25
healthy volunteers all patients EDSS <= 3.0 EDSS > 3.0
[-] mean lateral distance between feet [ m ]
T25FW+ , as fast as possible , 1st try
( p = 0.709934 ) *** ( p = 0.000166 ) * ( p = 0.015684 ) * ( p = 0.021021 ) -5 0 5 10 15 20 25 30 35 40
healthy volunteers all patients EDSS <= 3.0 EDSS > 3.0
[-] proportion of double limb support time [ % ]
T25FW+ , as fast as possible , 1st try
( p = 0.186944 ) * ( p = 0.012956 ) ( p = 0.729254 )
* ( p = 0.033193 )
People with MS (all)
Healthy volunteers People with MS (EDSS ≤ 3.0) People with MS (EDSS > 3.0)
Figure 4 Timed 25-‐Foot Walk Test in the « as fast as possible » mode of walk Figure 5 mode of walk T25FW in the « preferred pace »
A B C A
B
Conclusion – Discussion – PerspecBves
1. This exploratory study invesLgated the potenLal of RLS technology, which is easily applicable in the context of rouLne clinical pracLce (± 20 minutes per subject), to quanLfy gait alteraLons of pMS.
2. In addiLon to the mean walking speed, other gait descriptors can be measured and may enrich the sensiLvity of clinical trials considering gait « efficiency » as an outcome measure
• this assumpLon will be invesLgated with a larger number of subjects on a prospecLve basis
• this is specially relevant regarding the progressive type of MS where relevant outcome measures are lacking 3. Beyond these « efficiency » measures, differences in gait qualitaLve descriptors that might be relevant to balance,
propriocepLon and perhaps cogniLon have been observed in pMS, paving new grounds for the invesLgaLons of gait abnormaliLes in the field of mulLple sclerosis
