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
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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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
Functional Neurology 2014; 29(2): 99-105 101
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:
Masters and servants in Parkinsonian gait
Functional Neurology 2014; 29(2): 99-105 103
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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