Masters and Servants

Functional Neurology 2014; 29(2): 99-105 99

Giovanni Albani, MDa

Veronica Cimolin, PhDb

Alfonso Fasano, MD, PhDc

Claudio Trotti, PTa

Manuela Galli, PhDb,d

Alessandro Mauro, MDa,e

a Division of Neurology and Neurorehabilitation,

Ospedale San Giuseppe, Istituto Auxologico Italiano,

IRCCS, Piancavallo (Verbania), Italyb Department of Electronics, Information

and Bioengineering, Politecnico di Milano, Milan,

Italyc Movement Disorders Center, TWH, UHN, Division

of Neurology, University of Toronto, Toronto, Ontario,

Canada d IRCCS San Raffaele Pisana, Tosinvest Sanit,

Rome, Italye Rita Levi Montalcini Department of Neurocience,

University of Turin, Turin, Italy

Correspondence to: Veronica Cimolin

[email protected]

Summary

Gait disorder is a very frequent and disabling symp-

tom in Parkinsons disease (PD). The aim of this

study was to identify the main kinetic and kinematic

features of PD gait according to different disease

stages: early (Early Group), intermediate without

freezing (Non-Freezers) and intermediate with freez-

ing (Freezers). Kinematic data showed a distal to

proximal progression of impairment from the early to

the intermediate with freezing stage. The Early Group

showed more accentuated ankle dorsiflexion during

stance than the other PD subgroups; the Freezers

showed a more flexed hip position at initial contact

and a reduced range of motion (ROM) during stance

compared with the other patients. The individuals in

the intermediate stage (with or without freezing) dis-

played limited knee ROM.

Distal to proximal progression of lower limb impair-

ment in PD might be an expression of a rostral to cau-

dal degeneration of locomotor control centers.

Evaluation of the relationship between gait features

Masters and servants in parkinsonian gait: athree-dimensional analysis of biomechanicalchanges sensitive to disease progression

and disease progression may promote the develop-

ment of tailored rehabilitation programs.

KEY WORDS: biomechanics, gait analysis, Parkinsons disease,

rehabilitation

Introduction

Gait disorders are among the most common and dis-

abling symptoms of Parkinsons disease (PD) (Tan et

al., 2012) and they can manifest themselves through

clinical involvement of a variety of body segments:

shuffling of the feet, ankle and knee stiffness, flexion

of the pelvis and trunk, slowness of movement of the

entire lower limbs and a lack of associated move-

ments (e.g. arm swinging), associated with difficulty

changing direction or modulating velocity.

The relationship between gait features and disease

progression is not fully understood. Indeed, freezing of

gait (FOG) is more frequent in the advanced stages of

PD, but has also been reported in the early stages in

7.1% of cases (Giladi et al., 2001). FOG is considered

the clinical expression of a dysfunction of cortico-sub-

cortical interplay, given its responsiveness to external

cues (Frazzitta et al., 2009), and its correlation with

motor planning deficits (Knobl et al., 2012) or dysex-

ecutive syndrome (Amboni et al., 2008, 2012). Late

onset of levodopa-resistant FOG has been suggested

to indicate progression of the degenerative processes

from dopaminergic basal ganglia pathways to non-

dopaminergic structures controlling locomotion

(Bonnet et al., 1987).

Human society is characterized by a hierarchical sub-

division into masters and servants; this is a concept

that can also be applied to human physiology, with

decisional power and automatic task execution being,

respectively, the hallmarks of the two conditions. As

regards gait physiology, the dividing line between

them was first drawn when Sherrington studied the

effects of intracollicular transection in decerebrated

cats (Sherrington, 1906). Supraspinal structures, such

as the mesencephalic locomotor region and the pon-

tomedullary reticular formation, regulate the automat-

ic processes of the step cycle (Grillner et al., 2005)

and are under the control of higher centers of the cen-

tral nervous system (basal ganglia and cortex), which

are involved in the goal-directed strategies of walking

(Takakusaki et al., 2008).

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G. Albani et al.

100 Functional Neurology 2014; 29(2): 99-105

Even though three-dimensional kinematic analysis

has been widely used to describe the pathological fea-

tures of gait, little attention has, as yet, been paid to

the possible relationship between kinematic parame-

ters and the clinical progression of motor symptoms

and the presence of FOG. Accordingly, rehabilitation

trials have focused only on spatiotemporal parame-

ters, as also concluded by a recent Cochrane review

on randomized controlled studies (Tomlinson et al.,

2012): the clinical benefit following physiotherapy was

found to be significant only for velocity or step length,

while kinematic and kinetic parameters were not men-

tioned among the outcome measures.

However, spatiotemporal parameters may represent

only part of the pathophysiology underlying parkinson-

ian gait, specifically the part under the highest-level

control centers. This is confirmed by the sensitivity of

these parameters to attentional strategies (McIntosh

et al., 1997) and by their correlation with executive

functions both in normal subjects (Springer et al.,

2006) and in PD patients (Amboni et al., 2012).

Furthermore, conventional spatiotemporal parameters

such as cadence, step length or walking speed are not

sensitive enough to define subtle stage differences in

PD, with the exception of the coefficient of stride time

variability (Schaafsma et al., 2003). Finally, spatiotem-

poral parameters might insufficiently describe subtle

changes. For instance, it was recently found that

peduncolopontine nucleus stimulation improves FOG

during turning without any effect on step length or on

indexes of step variability (Thevathasan et al., 2011).

There is thus a strong need to uncover the relation-

ship between impaired biomechanical parameters and

the progression of parkinsonian gait, not least in order

to promote the development of tailored rehabilitation

programs, based on a comprehensive understanding

of the underlying pathophysiological mechanisms.

The aim of the present study was to identify the bio-

mechanical hallmarks of parkinsonian gait categorized

according to the clinical severity of PD.

Materials and methods

Participants

We recruited 37 consecutive PD patients, diagnosed

according to the UK Brain Bank criteria (Hughes et al.,

1992), and 10 age-matched healthy controls (Control

Group CG). Table I reports the demographic and

clinical characteristics of the entire PD group, of the

three subgroups of PD patients, and of the CG. All the

participants were free from other neurological, visual,

vestibular or muscular/orthopedic limb disorders liable

to influence their gait. Other exclusion criteria were:

cognitive impairment (Mini-Mental State Examination

score 25 or Frontal Assessment Battery score 12),

psychiatric diseases or severe systemic comorbidities.

The patients were assessed using the motor part of

the Unified Parkinsons disease Rating Scale

(UPDRS-III) and the Hoehn & Yahr stages (Giladi et

al., 2000).

The patients were divided into three groups: Early

Group (12 patients, Hoehn & Yahr stage < 2), Non-

Freezers (11 intermediate patients without FOG,

Hoehn & Yahr stage 2), and Freezers (14 patients

with FOG and Hoehn & Yahr stage 2). The presence

of FOG was established when the following criteria

were fulfilled: a score 2 on item 14 of UPDRS-III

(freezing when walking) and the occurrence of FOG

during clinical evaluation in OFF medication state

prior to gait analysis. None of the Non-Freezers

reported the occurrence of FOG during ON medication

state, thus ruling out a condition of real ON FOG

(Espay et al., 2012).

Gait analysis

The patients were recorded in OFF medication state,

after at least 12 hours had elapsed since withdrawal of

dopaminergic medication. To allow analysis of over-

ground gait, the participants were required to walk

along an eight-meter walkway. Six trials while walking

at preferred speed were recorded. Data were collect-

ed for each trial, using a six-camera VICON motion

analysis system (Oxford Metrics, UK) with reflective

markers placed according to the standard VICON

Plug-in-Gait marker set (Davis et al., 1991) and two

force platforms (Kistler, CH). Gait data were normal-

ized as % of gait cycle. In order to define the partici-

pants gait patterns and to quantify their deviations

from normality, several parameters (time/distance

parameters, joint angle values in specific gait cycle

instants, peak values in joint power graphs) were

identified and analyzed. The gait analysis-related

Table I - Demographic and clinical features of Parkinsons disease patients (total group and three subgroups) and healthycontrols.

Parkinsons disease patients CGEarly Group Non-Freezers Freezers Total

N. of subjects 12 11 14 37 10M/F ratio 7/5 7/4 6/8 20/17 7/3Age (years) 63.610.5 65.312.7 69.86.3 65.99.7 63.29.6Height (m) 1.70.1 1.70.2 1.70.4 1.70.3 1.70.1Disease duration (years) 3.01.6 5.33.7 9.26.0 5.94.6 -UPDRS III (med OFF) 22.65.3* 37.211.3 56.29.6 36.716.8 -

Abbreviations and symbols: M=males; F=females; CG=Control Group; * = p

parameters analyzed in this study are described in

table II.

Statistical analysis

Mean values () and standard deviations () of all thegait indexes were computed for each pathological

subgroup and for the CG. Variability in the spatiotem-

poral gait parameters was also measured, according

to the following coefficient of variation (CV) formula

[Ewens and Grant, 2005] : CV= /.Kolmogorov-Smirnov tests were used to verify

whether the parameters were normally distributed and

since they were found not to be normally distributed,

an analysis of variance for non-parametric data

Masters and servants in Parkinsonian gait


Table II - Descriptions of the gait parameters assessed in the present study.

Gait Parameter Description

Spatiotemporal parameters

% stance (%gait cycle) the part of the gait cycle that begins with initial contact and ends at toe-off of thesame limb, expressed as a percentage of the whole gait cycle

Mean velocity (m/s) the mean velocity of progression

Stride length the longitudinal distance from one foot strike to the next one of the same limb,normalized to the subjects height

Cadence (steps/min) the number of steps in a set amount of time (1 minute)

Kinematic parameters (degrees)

Mean PT the mean value of the pelvic joint plot in the sagittal plane (Pelvic Tilt graph) duringthe gait cycle

PT ROM the range of motion at the pelvic joint in the sagittal plane (Pelvic Tilt graph)during the gait cycle, calculated as the difference between the maximum andminimum values of the plot

Hip IC the value of the hip flexion-extension angle (hip position on sagittal plane) at initialcontact, representing the position of the hip joint at the beginning of the gait cycle

Hip min in St the minimum value of hip flexion (hip position in the sagittal plane) in the stancephase, representing the extension ability of the hip during this phase of the gait cycle

Hip ROM the range of motion at the hip joint in the sagittal plane during the gait cycle,calculated as the difference between the maximum and minimum values of the plot

Knee IC the value of the knee flexion-extension angle (knee position in the sagittal plane) atinitial contact, representing the position of the knee joint at the beginning of the gait cycle

Knee min in St the minimum value of knee flexion (knee position in the sagittal plane) in mid-stance,representing the extension ability of the knee during this phase of the gait cycle

Knee Max in Sw the peak of knee flexion (knee position in the sagittal plane) in the swing phase,representing the flexion ability of the knee joint during this phase of the gait cycle

Knee ROM the range of motion at the knee joint (in the sagittal plane) during the gait cycle,calculated as the difference between the maximum and minimum values of the plot

Ankle IC the value of the ankle joint angle (in the sagittal plane) at the initial contact, representingthe position of the knee joint at the beginning of the gait cycle

Ankle Max in St the peak of ankle dorsiflexion (in the sagittal plane) during the stance phase,representing the dorsiflexion ability of the ankle joint during this phase of the gaitcycle

Ankle min in St the minimum value of the ankle joint angle (in the sagittal plane) in the stance phase,representing the plantarflexion ability of the ankle joint at toe-off

Ankle Max in Sw the peak of ankle dorsiflexion (in the sagittal plane) during swing phase, representing thedorsiflexion ability of the ankle joint in this phase of the gait cycle

Ankle ROM the range of motion at the ankle joint (in the sagittal plane) during the stance phase,calculated as the difference between the maximum and minimum values of the plot inthis phase of the gait cycle

Kinetics

Ankle moment Max in St (N*m/kg) the maximum value of ankle dorsiflexion moment during terminal stance

Ankle Power Max in St (W/kg) the maximum value of generated ankle power during terminal stance, representing

the push-off ability of the foot during walking


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(Kruskal-Wallis) was employed, followed by a post-

hoc Mann-Whitney U-test. Data referring to the right

and the left side were compared using the Wilcoxon

signed rank test. The Chi2 test was used to compare

gender distribution. All tests were two-sided with the

level of significance set at p

Kinematic and kinetic profiles in the Freezers

The hip flex-extension plot showed that the Freezers

were characterized by greater flexion at initial contact

(Hip at IC) and in the stance phase (Hip min in St) with

a reduced ROM compared with the values recorded in

the CG and the other two patient subgroups. All the

patients showed greater knee flexion in midstance

(Knee min in St) and greater ankle dorsiflexion than

did the CG.

Discussion

This study originates from an awareness that spa-

tiotemporal parameters alone are insufficient to

describe parkinsonian gait, and consequently that

there is a need to evaluate the role that could poten-

tially be played by biomechanical parameters in mon-

itoring locomotion through the different stages of the

disease.

We found two main results:



Figure 1 - Coefficient of variation

values for the most significant

spatiotemporal parameters in

three subgroups of Parkinsons

disease patients.*= p

i) we confirmed that spatiotemporal data are not sensi-

tive enough to detect inter-group differences, with the

exception of the CV of cadence and stride length. Our

results therefore supported the findings of previous

investigations (Schaafsma et al., 2003; Arias and

Cudeiro, 2008) and studies which have shown that CV

might be an index of fall risk (Nieuwboer et al., 2001), a

marker of FOG, and a manifestation of the declining abil-

ity to produce a steady gait rhythm (Hausdorff, 2007).

ii) more important, we identified biomechanical param-

eters able to discriminate between PD patients who

have comparable spatiotemporal data but are at differ-

ent disease stages.

To the best of our knowledge, this is the first study cor-

relating the biomechanical features of parkinsonian gait

with disease severity, namely with a prevalently distal vs

a prevalently proximal impairment (in the Early Group vs

the Freezers, respectively). The Early Group showed

greater ankle dorsiflexion during stance while the

Freezers were characterized by a more flexed position

of the hip at initial contact and in the stance phase with

a reduced ROM. The Non-Freezers displayed an inter-

mediate pattern, characterized by greater knee joint

flexion at initial contact and a limited ROM.

A prevalent involvement of proximal joints has already

been reported in PD patients with recurrent falls, as they

display less rhythmic accelerations of the pelvis in the

vertical and anteroposterior planes than PD non-fallers

(Michaowska et al., 2005; Latt et al., 2009). In keeping

with our data, Nieuwboer et al. (2007) reported

decreased ROMs in the sagittal plane and increased hip

and knee flexion with a forward sway of the pelvis in the

pre-FOG phase. The proximal limb involvement seen in

FOG patients might be a manifestation of pelvic step

failure (Ducroquet et al., 1968) and trunk rigidity: pelvic

rotation contributes to the scaling of stride length and

consequently stride velocity by changing, during normal

walking, from a situation in which it is more in-phase

with thoracic rotation to one in which it is more out of

phase. In PD, as seen in other conditions (such as preg-

nancy and low back pain), poor rotation of the pelvis

may contribute to failure of this mechanism, highlighting

the clinical relevance of this biomechanical impairment

(an impairment that is less relevant when the ankle or

knee are involved). Indeed, in order to limit the thorax-

pelvis relative phase and the concomitant large rotations

of the spine, PD patients use strategies such as walking

slowly, with small steps, adapting the timing of thoracic

rotations to that of pelvic ones, or refraining from adapt-

ing the timing of pelvic rotations to the movements of the

leg (Huang et al., 2010). Consequently, PD patients

have been found to display a normal knee-hip dissocia-

tion during stance but a reduced dissociation during the

swing phase (Nieuwboer et al., 2007). During this

phase, Chastan et al. (2009) reported that while controls

show a fall in the center of gravity, reversed before foot

contact, PD patients might lose this active braking

capacity, with only a slight amelioration of this biome-

chanical behavior after L-dopa administration. This fur-

ther supports the hypothesis that part of the mechanism

of gait is under the control of non-dopaminergic struc-

tures. Accordingly, deep brain stimulation of the pedun-

colopontine nucleus was found to ameliorate only prox-

imal and not distal lower limb movements (Thevathasan

et al., 2011).

Our findings confirm the early assumptions of Penfield

and Boldrev (1937) that distal limb movements are

under cortico-subcortical control (i.e. under the control

of the basal ganglia and cortex) while pelvic motion is

predominantly under the control of reticolospinal path-

ways related to stability. At first glance, our results on

the progression of gait impairment do not seem to fit

with the caudo-rostral progression of PD-related

degeneration hypothesized by Braak and Del Tredici

(2008). However, a hypothesis compatible with our

findings is that that the initial degeneration of locomo-

tor midbrain structures reaches a higher threshold of

neuronal death than that required in upper structures

to produce clinical effects. This hypothesis could be

schematically represented in an integrative model of a

functional hierarchy of gait parameters in PD (Fig. 3).

Moreover, failure of cortical compensatory mecha-

nisms over the course of the disease could not be

ruled out. Accordingly, a cortical activation is reported

by a gait-related imagery-task study (Wai et al., 2012),

and by functional MRI studies which describe hyperac-

tivation patterns in frontal regions without differences

with the passive paradigm (Katschning et al., 2011).

One limitation of this study is the lack of association of

gait analysis with neurophysiological or neuroimaging

data and, more importantly, the lack of a longitudinal

assessment. More important still, a study session in

each patient also during their ON phase, for compari-

son with their OFF phase, might have allowed the

integration of non-dopaminergic parameters with the

parameters proposed in this study.

Pending future prospective studies exploring these

hypotheses, our study contributes to the identification of

biomechanical indexes that may be considered ser-

vants of gait control and highlights their importance

among the outcome measures of rehabilitation trials for

parkinsonian gait.

G. Albani et al.

104 Functional Neurology 2014; 29(2): 99-105

Figure 3 - Representation of the proposed integrative model of

a functional hierarchy of gait parameters in parkinsonian

pathology.


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Acknowledgments

The authors would like to acknowledge Matteo Comis

valuable contribution to the data collection.

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