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symmetry
S
S
Article
The Effect of a Secondary Task on Kinematics during
Turning in Parkinson’s Disease with Mild to
Moderate Impairment
Francesca Nardello , Emanuele Bertoli, Federica Bombieri, Matteo Bertucco * and
Andrea Monte
Department of Neurosciences, Biomedicine and Movement Sciences University of Verona, 43, 37131 Verona,
Italy; francesca.nardello@univr.it (F.N.); emanuele.bertoli@studenti.univr.it (E.B.);
federica.bombieri@univr.it (F.B.); andrea.monte@univr.it (A.M.)
*Correspondence: matteo.bertucco@univr.it; Tel.: +39-045-8425131
Received: 10 July 2020; Accepted: 29 July 2020; Published: 3 August 2020
Abstract:
Patients with Parkinson’s disease (PD) show typical gait asymmetries. These peculiar motor
impairments are exacerbated by added cognitive and/or mechanical loading. However, there is scarce
literature that chains these two stimuli. The aim of this study was to investigate the combined effects
of a dual task (cognitive task) and turning (mechanical task) on the spatiotemporal parameters in mild
to moderate PD. Participants (nine patients with PD and nine controls (CRs)) were evaluated while
walking at their self-selected pace without a secondary task (single task), and while repeating the days
of the week backwards (dual task) along a straight direction and a 60
◦
and 120
◦
turn. As speculated,
in single tasking, PD patients preferred to walk with a shorter stride length (p<0.05) but similar
timing parameters, compared to the CR group; in dual tasking, both groups walked slower with
shorter strides. As the turn angle increased, the speed will be reduced (p<0.001), whereas the
ground–foot contact will become greater (p<0.001) in all the participants. We showed that the
combination of a simple cognitive task and a mechanical task (especially at larger angles) could
represent an important training stimulus in PD at the early stages of the pathology.
Keywords: Parkinson’s disease; gait; dual task; turning; kinematics
1. Introduction
Gait functionality is accomplished with good health, whereas locomotion disturbances are
associated with an advancing age or with the presence of pathologies. Within 3 years of diagnosis, over
85% of people with Parkinson’s disease (PD) develop gait deteriorations [
1
,
2
], as well as a reduced
walking symmetry [
2
–
4
]. Such motor dysfunctions could be exacerbated under various conditions,
such as the dual task performance and the changing of the walking direction (i.e., turning).
Specifically, the execution of the two tasks simultaneously (“concurrent performance”) presents a
challenge for PD patients because of their disabled lower-level spinal centers and basal nuclei [
5
–
7
].
Studies have shown that, when compared to controls, subjects with PD show greater reductions in their
stride length [
8
,
9
] and, therefore, walking speed, as well as an increased variability of the kinematic
parameters [
10
–
16
]. These patterns are aggravated with the severity of the pathology [
17
,
18
] and with
the complexity of the concurrent task [
5
,
13
,
19
,
20
]. Since these findings strengthen the idea that the
cognitive function could contribute to gait regulation, it could be helpful to understand the effect of
different cognitive tasks, even very simple ones, in this kind of pathology [
21
–
23
]. This knowledge
could provide an insight on what is the best training stimulus to be administered in those patients.
Symmetry 2020,12, 1284; doi:10.3390/sym12081284 www.mdpi.com/journal/symmetry
Symmetry 2020,12, 1284 2 of 14
Concerning the walking direction, it has been shown that subjects with PD report turning
difficulties, which are associated with an augmented risk of falling [
24
–
27
]. These impairments are due
to the central nervous system’s involvement in body re-orientation when travelling in the new direction.
From a kinematical point of view, patients with PD highlighted a smaller step width [
9
,
28
],
a reduction in the step length and a decrease in their walking velocity during a change of direction of
45
◦
in the stepping tasks [
29
]. If the turning angle increased (i.e., to 90
◦
), patients approached turns
with a slower step length and by performing the turn with a larger number of steps [
30
]. Walking
with an auditory cue reduced the gait-timing variability, as well as the step length, and increased the
radius of gyration during a turn of 180
◦
[
31
]. Moreover, recent literature has shown that subjects with
PD spent more time during the turn (between 30
◦
and 180
◦
) and exhibit a reduction in the walking
stability compared to controls [
32
]. Turning 360
◦
in place seemed to be a more compromised condition
when compared to turning while walking, with similar impairments with and without episodes of
freezing [
33
,
34
]. As in the case of the cognitive additional demand, the turning conditions could
also represent an important stimulus in such a population. Hence, investigating different turning
conditions could provide important information about the optimal training strategy in people with PD.
To date, a lingering question in the literature regards the combination of mechanical and cognitive
perturbations. Indeed, few studies have combined the dual task condition with the mechanical
perturbations (e.g., change of direction) [
35
–
37
]. Furthermore, previous studies usually used turn
angles larger than 90◦, which represents per se an important perturbation for PD patients [30].
Therefore, we used the most common turning angles during daily life (60
◦
and 120
◦
) [
38
],
in combination with a simple cognitive task (repeating the days of the week backwards), to better
understand the effects of these perturbations on gait kinematics. This combined approach has involved
participants with mild to moderate PD in order to provide additional information on how the typical
Parkinson’s disease walking pattern is modified under simultaneous cognitive and mechanical loads.
Hence, the primary aim was to investigate if the presence of a “dual task” condition can further
alter the kinematics (i.e., spatiotemporal parameters) of walking, or, on the contrary, if it can represent
a good training stimulus in mild and moderate Parkinson’s disease. This cognitive task was studied
during forward/linear walking and during turning.
Based on the previously mentioned literature, we hypothesized that the simple cognitive and the
mechanical tasks will exhibit similar effects in both populations (patients and controls), whereas the
combination of the two stimuli will show a higher impact on PD patients.
2. Materials and Methods
2.1. Participants
This study has a cross-sectional, analytical, observational design. Nine patients with mild to
moderate PD (3 women and 6 men; mean
±
SD, 68.2
±
5.95 years old, 74.2
±
11.8 kg body mass,
1.70 ±0.10 m
height, and 25.6
±
3.07 kg
·
m
−2
body mass index (BMI)) and nine healthy age-matched
controls (4 women and 5 men; 67.2
±
3.45 years old, 72.6
±
13.1 kg, 1.68
±
0.08 m, and
25.7 ±3.43 kg·m−2
)
were recruited in this study.
All participants received written and oral instructions before the study and gave their written
informed consent for the experimental procedure. The study was conducted in accordance with the
Declaration of Helsinki, and the experimental protocol was approved by the Institutional Review
Board of the Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona
(protocol number 2018-UNVRCLE-0451799).
Participants were recruited from a sample of late adulthood people attending the adapted physical
activity program at the School of Sport and Exercise Science at our University (see their characteristics
in Table 1).
Symmetry 2020,12, 1284 3 of 14
Table 1. Characteristics of subjects with Parkinson’s disease.
Subject
No.
Age
(yrs) Sex
Body
Mass
(kg)
Body
Height
(m)
BMI
(kg·m−2)
Disease
Duration
(yrs)
Y&H
Score
UPDRS
Score MMSE Medication
Side of Appearance of
the First Motor
Symptom
PD1 77 F 80 1.64 29.74 4 1 26 29 Levodopa/carbidopa Left
PD2 66 F 63 1.58 25.24 4 3 37 27 Levodopa/carbidopa Left
PD3 71 M 70 1.70 24.22 3 1 24 28 Levodopa/benserazide Right
PD4 59 M 65 1.70 22.49 9 1 26 29 Levodopa/carbidopa Left
PD5 67 M 80 1.66 29.03 3 1 30 26 Levodopa/carbidopa Right
PD6 67 M 80 1.77 25.54 6 1 30 28 Levodopa/benserazide Left
PD7 63 F 55 1.59 21.76 1 1 23 29 Levodopa/benserazide Right
PD8 77 M 82 1.88 23.20 8 1 25 24 Levodopa/carbidopa Right
PD9 67 M 93 1.78 29.35 7 2 32 25 Levodopa/carbidopa Left
BMI: body mass index; Y&H: Hoehn and Yahr; UPDRS: Unified Parkinson’s Disease Rating Scale (motor section); MMSE: Mini Mental State Education.
Symmetry 2020,12, 1284 4 of 14
Patients were excluded if their medical condition proved unstable due to other neurological,
orthopedic, metabolic or cardiovascular co-morbidity factors affecting gait. There was no type of
rehabilitation in the month prior to recruitment or disease-modifying therapy that was not well defined.
A diagnosis of idiopathic PD was carried out by a neurologist, in accordance with the guidelines
established by the London Brain Bank [
39
]. The disease severity was classified according to the
modified Hoehn and Yahr scale (H&Y) [
40
], whereas the assessment of the degree of motor and
functional impairment was obtained using part III of the Unified Parkinson’s Disease Rating Scale
(UPDRS) [
41
]. Finally, cognitive function was assessed by using the Mini Mental State Examination
(MMSE), with scores of up to 30 (higher scores correspond to greater cognitive function).
We conducted an a priori screening to evaluate whether participants were able to carry out the
task instructions required for the experimental protocol (see the “Experimental procedures” later).
Based on this a priori screening, only individuals with PD with an MMSE score of 24 or higher were
able to perform the double stimuli, and therefore were recruited in the study.
2.2. Experimental Procedures
Tests were conducted in the Biomechanics Laboratory at the Department of Neurosciences,
Biomedicine and Movement Sciences. The spatial (distance) and temporal (time) characteristics of
the step pattern were measured using an eight-camera motion capture system (MX Ultranet, VICON,
Oxfordshire, UK), sampling at 100 Hz. This apparatus recorded the position of markers positioned
bilaterally on the feet: the calcaneus, lateral malleolus and 5th metatarsal-phalangeal joint.
Participants started from a standing position and walked barefoot at their self-selected speed over
a 10 m walkway (Figure 1, panel a). Each participant performed three different conditions: (i) forward
walking (WF (Figure 1, panel b)); (ii) walking, turning at 60
◦
, walking (T60); (iii) walking, turning at
120
◦
, walking (T120). Furthermore, T60 and T120 were conducted turning in both directions (left and
right (Figure 1, panels c and d)). During all turning tasks, a cone was positioned in the center of the
walkway (see the black hexagon in Figure 1) to identify the turning point. Furthermore, an operator
positioned himself at the end of the corridor lane that the subjects had to move. All directions were
tested in single and dual tasks, and the cognitive load consists of walking while repeating the days of
the week backwards [
17
]. Six trials of each condition were performed and the order of gait conditions
was randomly allocated (Figure 2). Subjects sat and rested in a chair for three minutes between trials.
Patients were tested at the peak dose in the medication cycle.
Symmetry2020,12,xFORPEERREVIEW4of15
Patientswereexcludediftheirmedicalconditionprovedunstableduetootherneurological,
orthopedic,metabolicorcardiovascularco‐morbidityfactorsaffectinggait.Therewasnotypeof
rehabilitationinthemonthpriortorecruitmentordisease‐modifyingtherapythatwasnotwelldefined.A
diagnosisofidiopathicPDwascarriedoutbyaneurologist,inaccordancewiththeguidelinesestablished
bytheLondonBrainBank[39].ThediseaseseveritywasclassifiedaccordingtothemodifiedHoehnand
Yahrscale(H&Y)[40],whereastheassessmentofthedegreeofmotorandfunctionalimpairmentwas
obtainedusingpartIIIoftheUnifiedParkinson’sDiseaseRatingScale(UPDRS)[41].Finally,cognitive
functionwasassessedbyusingtheMiniMentalStateExamination(MMSE),withscoresofupto30(higher
scorescorrespondtogreatercognitivefunction).
Weconductedanaprioriscreeningtoevaluatewhetherparticipantswereabletocarryoutthetask
instructionsrequiredfortheexperimentalprotocol(seethe“Experimentalprocedures”later).Basedonthis
aprioriscreening,onlyindividualswithPDwithanMMSEscoreof24orhigherwereabletoperformthe
doublestimuli,andthereforewererecruitedinthestudy.
2.2.ExperimentalProcedures
TestswereconductedintheBiomechanicsLaboratoryattheDepartmentofNeurosciences,
BiomedicineandMovementSciences.Thespatial(distance)andtemporal(time)characteristicsofthestep
patternweremeasuredusinganeight‐cameramotioncapturesystem(MXUltranet,VICON,Oxfordshire,
UK),samplingat100Hz.Thisapparatusrecordedthepositionofmarkerspositionedbilaterallyonthefeet:
thecalcaneus,lateralmalleolusand5thmetatarsal‐phalangealjoint.
Participantsstartedfromastandingpositionandwalkedbarefootattheirself‐selectedspeedovera10
mwalkway(Figure1,panela).Eachparticipantperformedthreedifferentconditions:i)forwardwalking
(WF(Figure1,panelb));ii)walking,turningat60°,walking(T60);iii)walking,turningat120°,walking
(T120).Furthermore,T60andT120wereconductedturninginbothdirections(leftandright(Figure1,
panelscandd)).Duringallturningtasks,aconewaspositionedinthecenterofthewalkway(seetheblack
hexagoninFigure1)toidentifytheturningpoint.Furthermore,anoperatorpositionedhimselfattheend
ofthecorridorlanethatthesubjectshadtomove.Alldirectionsweretestedinsingleanddualtasks,and
thecognitiveloadconsistsofwalkingwhilerepeatingthedaysoftheweekbackwards[17].Sixtrialsofeach
conditionwereperformedandtheorderofgaitconditionswasrandomlyallocated(Figure2).Subjectssat
andrestedinachairforthreeminutesbetweentrials.Patientsweretestedatthepeakdoseinthemedication
cycle.
Figure 1.
Schematic representation of walking conditions (
a
), and steps during walking (forward
walking (WF), (b) and turning (T60 in (c) and T120 in (d)).
Symmetry 2020,12, 1284 5 of 14
Symmetry2020,12,xFORPEERREVIEW5of15
Figure1.Schematicrepresentationofwalkingconditions(a),andstepsduringwalking(forwardwalking
(WF),(b)andturning(T60in(c)andT120in(d)).
Figure2.Flowchartoftheresearchdesign.
2.3.DataReduction
Kinematicdatawererecordedfrom3mbeforeandaftertheturningstep.Thequantitativegait
assessmentincludedbothtemporalandspatialparameters(Figure3),thatare:i)stancetime(s),theperiod
oftimewhenthefootisincontactwiththeground;ii)swingtime(s),theperiodoftimewhenthefootis
notincontactwiththeground;iii)stridetime(s),theintervaloftimetocompleteagaitstride;iv)cadence
(stride∙min
−1
),thenumberofstridestakeninaunitoftime;v)stridelength(m),thedistancefromtheinitial
contactofonefoottothefollowinginitialcontactofthesamefoot.Alltheseparameterswereobtainedusing
standarddefinitionsaccordingtoanalgorithmprogrammedinLabView(version10,NationalInstruments,
Austin,TX,USA).Walkingspeed(m∙s
−1
)wasappreciatedasthedistancetravelledduringacompletestride
cycle.
Figure 2. Flow chart of the research design.
2.3. Data Reduction
Kinematic data were recorded from 3 m before and after the turning step. The quantitative gait
assessment included both temporal and spatial parameters (Figure 3), that are: (i) stance time (s),
the period of time when the foot is in contact with the ground; (ii) swing time (s), the period of time
when the foot is not in contact with the ground; (iii) stride time (s), the interval of time to complete a
gait stride; (iv) cadence (stride
·
min
−1
), the number of strides taken in a unit of time; (v) stride length
(m), the distance from the initial contact of one foot to the following initial contact of the same foot. All
these parameters were obtained using standard definitions according to an algorithm programmed in
LabView (version 10, National Instruments, Austin, TX, USA). Walking speed (m
·
s
−1
) was appreciated
as the distance travelled during a complete stride cycle.
Symmetry2020,12,xFORPEERREVIEW6of15
Figure3.Gaitparameterassessmentforwalking/turningconditions.
Theaveragevalueofalltheperformedstepsineachconditionhasbeenutilizedinfurtheranalyses.
Thenumberoferrors(i.e.,whentellingadaybackwardswentwrong)wascountedandcollectedbyan
operatorduringthewalkingtrialsaswell.Forcontrols,wepooledtogetherthedatafromtherightandleft
lowerlimbs(n=9),whereasforPDpatients,thedatareferringtothelessaffectedside(PDNA)andtothe
moreaffectedside(PDA)wereconsideredseparately(n=9).
Finally,wecalculatedthelocomotorrehabilitationindex“LRI”as:LRI=100*(self‐selectedspeed
(SSWS)/optimalspeed(OWS)),wheretheself‐selectedspeed(SSWS)hasbeendirectlymeasuredandthe
optimalspeed(OWS)hasbeenestimatedaccordingtoapreviousstudy[42].
2.4.DataAnalysis
ThedataanalysiswasconductedusingSPSS19.0(SPSSInc,Chicago,IL,USA).Descriptivestatistics
wereusedtocomputethemeansandstandarddeviationsfortheoutcomevariables.Allthespatiotemporal
gaitdatawerenormallydistributed(Kolmogorov–SmirnovandShapiro–Wilktests)anddidnotviolatethe
assumptionsofhomogeneity.Inordertotestthemainhypotheses,aseriesof2(tasks:singletaskvs.dual
task)×3(gaitdirections:WFvs.T60vs.T120)repeatedmeasuresANOVAs,withgroups(CR,PDNA,PDA)
asthebetweenfactors,wereusedtoanalyzethegaitdata.Whenasignificantmaineffectwasfound(critical
pvalue<0.05),apost‐hoct‐testwasperformed.ABonferronicorrectionwasappliedwhenneeded.
3.Results
3.1.CognitiveTask
FortheMMSE,controls(28.1±1.66)showedsimilarscorestopatients(27.2±1.85(p=ns)).
Themajorityofthedualtasktrailsweresuccessful.WhereasindividualswithPDperformedthe
cognitivetaskwith97.2±6%,94.9±8%and95.2±10%accuracyduringWF,T60andT120,respectively,
andcontrolsperformedthesametrailswithanaccuracyof96.7±5%,95.3±6%and94.9±9%.Regarding
Figure 3. Gait parameter assessment for walking/turning conditions.
Symmetry 2020,12, 1284 6 of 14
The average value of all the performed steps in each condition has been utilized in further analyses.
The number of errors (i.e., when telling a day backwards went wrong) was counted and collected by
an operator during the walking trials as well. For controls, we pooled together the data from the right
and left lower limbs (n=9), whereas for PD patients, the data referring to the less affected side (PDNA)
and to the more affected side (PDA) were considered separately (n=9).
Finally, we calculated the locomotor rehabilitation index “LRI” as: LRI =100 * (self-selected speed
(SSWS)/optimal speed (OWS)), where the self-selected speed (SSWS) has been directly measured and
the optimal speed (OWS) has been estimated according to a previous study [42].
2.4. Data Analysis
The data analysis was conducted using SPSS 19.0 (SPSS Inc, Chicago, IL, USA). Descriptive
statistics were used to compute the means and standard deviations for the outcome variables. All the
spatiotemporal gait data were normally distributed (Kolmogorov–Smirnov and Shapiro–Wilk tests)
and did not violate the assumptions of homogeneity. In order to test the main hypotheses, a series
of 2 (tasks: single task vs. dual task)
×
3 (gait directions: WF vs. T60 vs. T120) repeated measures
ANOVAs, with groups (CR, PDNA, PDA) as the between factors, were used to analyze the gait data.
When a significant main effect was found (critical pvalue <0.05), a post-hoc t-test was performed.
A Bonferroni correction was applied when needed.
3. Results
3.1. Cognitive Task
For the MMSE, controls (28.1 ±1.66) showed similar scores to patients (27.2 ±1.85 (p =ns)).
The majority of the dual task trails were successful. Whereas individuals with PD performed
the cognitive task with 97.2
±
6%, 94.9
±
8% and 95.2
±
10% accuracy during WF, T60 and T120,
respectively, and controls performed the same trails with an accuracy of 96.7
±
5%, 95.3
±
6% and
94.9
±
9%. Regarding the gait direction, more correct answers were given while walking forward as
compared to turning (p<0.01 for T60 and T120) similarly in both groups.
3.2. Spatiotemporal Parameters
There were no differences between groups for age, body mass and height, or body mass index.
The average
±
SD values of the measured temporal and spatial variables have been reported in
Tables 2and 3, as well as the post-hoc results.
The stance time differed among tasks (F (1, 24) =34.456, p<0.001) and walking direction
(
F (2, 48) =27.234
,p<0.001), whereas there were no differences between groups (F (2, 24) =0.262,
p=ns
). In particular, the dual task showed an increased stance time compared to the single one.
The highest stance phase was observed during turning at 120
◦
, while the lowest was during walking in
the straight direction.
The swing phase showed a significant effect for direction (F (2, 48) =4.648, p<0.05), but not for
task (F (1, 24) =3.745, p =ns) and group (F (2, 24) =0.883, p =ns). Particularly, the 120
◦
turn took a
longer swing time in comparison to the other directions.
The cycle time showed significant differences among tasks (F (1, 24) =31.840, p<0.001) and
directions (F (2, 48) =34.227, p<0.001), whereas there were no group changes (F (2, 24) =0.618, p =ns).
Both groups increased the cycle time during the dual task condition, and the 120
◦
turn took the longest
time compared with the other conditions.
Therefore, the step frequency and cadence changed significantly with regard to task
(
F (1, 24) =30.257
and 30.317, p<0.001) and direction (F (2, 48) =31.329 and 31.441, p<0.001),
but not with group (F (2, 24) =0.458 and 0.457, p =ns).
Symmetry 2020,12, 1284 7 of 14
Table 2. Gait temporal parameters at single and dual tasking in all directions. Data are means ±SD.
Stance Time (s) Swing Time (s)
Walking Direction CR PDNA PDA CR PDNA PDA
WF_ST 0.72 ±0.05 0.74 ±0.12 a0.74 ±0.18 c,l 0.33 ±0.03 0.33 ±0.04 0.33 ±0.02 a
T60_ST 0.73 ±0.07 a0.76 ±0.13 a,h,m 0.75 ±0.12 b,g 0.33 ±0.04 0.33 ±0.04 0.35 ±0.03
T120_ST 0.75 ±0.07 b0.78 ±0.14 b,h,m 0.78 ±0.14 c,l,g 0.33 ±0.04 0.35 ±0.03 0.35 ±0.03
WF_DT 0.75 ±0.07 m0.80 ±0.12 a,m 0.78 ±0.11 c,l 0.33 ±0.04 0.34 ±0.04 0.35 ±0.05 a
T60_DT 0.78 ±0.11 a0.84 ±0.14 a0.82 ±0.14 b0.33 ±0.03 0.34 ±0.04 0.35 ±0.04
T120_DT 0.81 ±0.11 b,m 0.85 ±0.14 b,m 0.83 ±0.13 c,l 0.34 ±0.04 0.35 ±0.05 0.37 ±0.06
Stride Time (s) Cadence (Stride·min−1)
Walking Direction CR PDNA PDA CR PDNA PDA
WF_ST 1.05 ±0.08 a1.07 ±0.12 a,n 1.08 ±0.12 b,m 114.79 ±8.68 a113.55 ±12.27 c,n 112.74 ±11.91 b,d,m
T60_ST 1.06 ±0.11 a1.09 ±0.12 a,h 1.10 ±0.12 b113.77 ±10.01 a111.35 ±12.10 c,i 109.92 ±11.32 b,d
T120_ST 1.08 ±0.11 a1.14 ±0.14 c,n,h 1.13 ±0.13 a,m 112.16 ±9.96 b106.90 ±12.98 a,i,n 107.04 ±12.10 a,m
WF_DT 1.09 ±0.10 a,l 1.13 ±0.11 a,n 1.13 ±0.12 b,n 110.94 ±10.08 a,m 106.76 ±10.79 c,n 106.79 ±10.92 b,m
T60_DT 1.11 ±0.13 a1.18 ±0.13 a1.18 ±0.13 b108.88 ±12.57 a,g 102.94 ±11.55 c103.04 ±11.02 b
T120_DT 1.14 ±0.12 a,l 1.20 ±0.15 c,n 1.20 ±0.14 a,n 105.84 ±10.87 b,g,m 101.00 ±12.46 a,n 101.44 ±11.97 a,m
CR: control group; PDNA: Parkinson’s disease not affected side; PDA: Parkinson’s disease more affected side. WF: walking forward; T60: turning at 60
◦
; T120: turning at 120
◦
. ST: single
task; DT: dual task.
a
=p<0.05,
b
=p<0.01,
c
=p<0.001: significant difference by comparing ST to DT.
d
=p<0.05: significant difference by comparing the WF to T60.
g
=p<0.05;
h=p<0.01, i=p<0.001: significant difference by comparing the T60 to T120. l=p<0.05, m=p<0.01, n=p<0.001: significant difference by comparing the WF to T120.
Table 3. Step frequency, stride length and walking speed at single and dual tasking in all directions. Data are means ±SD.
Step Frequency (Hz) Stride Length (m) Walking Speed (m·s−1)
Walking
Direction CR PDNA PDA CR PDNA PDA CR PDNA PDA
WF_ST 0.95 ±0.08 a0.95 ±0.10 c,n 0.94 ±0.10 b,m 1.34 ±0.10 a,n,#,◦1.23 ±0.14 b,n,#
1.24
±
0.14
c,n,◦1.28 ±0.12 c,m,#,◦1.17 ±0.21 b,f,n,#
1.17
±
0.21
b,e,n,◦
T60_ST 0.95 ±0.08 a0.93 ±0.10 c,h 0.92 ±0.10 b1.33 ±0.08 b,h,#,◦1.20 ±0.14 b,i,# 1.23 ±0.16 c,i,◦1.26 ±0.12 c,i,#,◦1.06 ±0.17 f,i,# 1.06 ±0.18 e,i,◦
T120_ST 0.93 ±0.08 b0.89 ±0.11 a,h,n 0.89 ±0.10 a,m 1.24 ±0.07 a,h,n,#,◦1.05 ±0.13 i,n,#
1.05
±
0.11
i,n,◦1.15 ±0.12 b,i,m,#,◦0.95 ±0.15 i,n,# 0.95 ±0.14 i,n,◦
WF_DT 0.92 ±0.08 a,m 0.89 ±0.09 c,n 0.89 ±0.09 b,m 1.27 ±0.06 a,n,#,◦1.14 ±0.12 b,n,#
1.15
±
0.13
c,n,◦1.18 ±0.10 c,n,#,◦
1.09
±
0.17
b,d,n,# 1.11 ±0.18 b,n,◦
T60_DT 0.91 ±0.10 a,g 0.86 ±0.10 c0.86 ±0.09 b1.26 ±0.07 b,i,#,◦1.14 ±0.15 b,i,# 1.14 ±0.15 c,i,◦1.14 ±0.15 c,i,#,◦1.03 ±0.18 d,i,# 1.06 ±0.17 i,◦
T120_DT 0.88 ±0.09 b,g,m 0.84 ±0.10 a,n 0.84 ±0.10 a,m 1.18 ±0.08 a,i,n,#,◦1.02 ±0.16 i,n,#
1.01
±
0.16
i,n,◦1.04 ±0.14 b,i,n,#,◦0.89 ±0.16 i,n,# 0.89 ±0.14 i,n,◦
CR: control group; PDNA: Parkinson’s disease not affected side; PDA: Parkinson’s disease more affected side. WF: walking forward; T60: turning at 60
◦
; T120: turning at 120
◦
. ST: single
task; DT: dual task.
a
=p<0.05,
b
=p<0.01,
c
=p<0.001: significant difference by comparing ST to DT.
d
=p<0.05,
e
=p<0.01,
f
=p<0.001: significant difference by comparing the WF
to T60.
g
=p<0.05;
h
=p<0.01,
i
=p<0.001: significant difference by comparing the T60 to T120.
m
=p<0.01,
n
=p<0.001: significant difference by comparing the WF to T120.
#=p<0.05: significant difference by comparing the CR group to the PDNA group. ◦=p<0.05: significant difference by comparing the CR group to the PDA group.
Symmetry 2020,12, 1284 8 of 14
The stride length was affected by group (F (2, 24) =4.415, p<0.05), task (F (1, 24) =41.213,
p<0.001
) and direction (F (2, 48) =132.916, p<0.001). In particular, healthy controls walked with
longer strides when compared to patients, whereas no differences were observed among the sides in
the pathological group. All groups reduced their stride lengths during the dual task condition, and the
120◦turn showed the lowest value compared with the other conditions.
Additionally, the walking velocity changed with group (F (2, 24) =2.764, p<0.05), task
(
F (1, 24) =21.818
,p<0.001) and direction (F (2, 48) =104.061, p<0.001). In general, controls
walked faster than patients, and the latter group showed similar values in both sides. Furthermore, the
larger the turning the lower the velocity: the 120
◦
turn showed the lowest velocity value compared to
other directions.
The calculated LRI index significantly changed with group (F (2, 24) =4.672, p<0.05), task
(
F (1, 24) =14.712
,p<0.001) and direction (F (2, 48) =70.937, p<0.001). Because of the lack of a
significant difference, the data of the PDNA and PDA were pooled together. Our data confirmed that
patients walked with a lower LRI compared to controls in all the investigated conditions because of
their reduced walking speed, and such a pattern is more pronounced at turning 120◦(Figure 4).
Symmetry2020,12,xFORPEERREVIEW9of15
Thestancetimedifferedamongtasks(F(1,24)=34.456,p<0.001)andwalkingdirection(F(2,
48)=27.234,p<0.001),whereastherewerenodifferencesbetweengroups(F(2,24)=0.262,p=ns).
Inparticular,thedualtaskshowedanincreasedstancetimecomparedtothesingleone.Thehighest
stancephasewasobservedduringturningat120°,whilethelowestwasduringwalkinginthe
straightdirection.
Theswingphaseshowedasignificanteffectfordirection(F(2,48)=4.648,p<0.05),butnotfor
task(F(1,24)=3.745,p=ns)andgroup(F(2,24)=0.883,p=ns).Particularly,the120°turntooka
longerswingtimeincomparisontotheotherdirections.
Thecycletimeshowedsignificantdifferencesamongtasks(F(1,24)=31.840,p<0.001)and
directions(F(2,48)=34.227,p<0.001),whereastherewerenogroupchanges(F(2,24)=0.618,p=
ns).Bothgroupsincreasedthecycletimeduringthedualtaskcondition,andthe120°turntookthe
longesttimecomparedwiththeotherconditions.
Therefore,thestepfrequencyandcadencechangedsignificantlywithregardtotask(F(1,24)=
30.257and30.317,p<0.001)anddirection(F(2,48)=31.329and31.441,p<0.001),butnotwithgroup
(F(2,24)=0.458and0.457,p=ns).
Thestridelengthwasaffectedbygroup(F(2,24)=4.415,p<0.05),task(F(1,24)=41.213,p<
0.001)anddirection(F(2,48)=132.916,p<0.001).Inparticular,healthycontrolswalkedwithlonger
strideswhencomparedtopatients,whereasnodifferenceswereobservedamongthesidesinthe
pathologicalgroup.Allgroupsreducedtheirstridelengthsduringthedualtaskcondition,andthe
120°turnshowedthelowestvaluecomparedwiththeotherconditions.
Additionally,thewalkingvelocitychangedwithgroup(F(2,24)=2.764,p<0.05),task(F(1,24)
=21.818,p<0.001)anddirection(F(2,48)=104.061,p<0.001).Ingeneral,controlswalkedfasterthan
patients,andthelattergroupshowedsimilarvaluesinbothsides.Furthermore,thelargertheturning
thelowerthevelocity:the120°turnshowedthelowestvelocityvaluecomparedtootherdirections.
ThecalculatedLRIindexsignificantlychangedwithgroup(F(2,24)=4.672,p<0.05),task(F(1,
24)=14.712,p<0.001)anddirection(F(2,48)=70.937,p<0.001).Becauseofthelackofasignificant
difference,thedataofthePDNAandPDAwerepooledtogether.Ourdataconfirmedthatpatients
walkedwithalowerLRIcomparedtocontrolsinalltheinvestigatedconditionsbecauseoftheir
reducedwalkingspeed,andsuchapatternismorepronouncedatturning120°(Figure4).
Figure4.Comparisonoflocomotorrehabilitationindexvaluesbetweenthecontrolgroup(whitebars)
andthepathologicalgroup(blackbars),fortheforwarddirection(WF),turning60°(T60)andturning
120°(T120),inbothsingle(ST)anddual(DT)tasks.Averagevalues±SDhavebeenreported;dataof
thePDNAandPDAwerepooledtogether.Asignificantpost‐hoctesthasbeenreported:*=p<0.05
bycomparingthecontrolgrouptothepathologicalone;c=p<0.001:significantdifferenceby
Figure 4.
Comparison of locomotor rehabilitation index values between the control group (white bars)
and the pathological group (black bars), for the forward direction (WF), turning 60
◦
(T60) and turning
120
◦
(T120), in both single (ST) and dual (DT) tasks. Average values
±
SD have been reported; data of
the PDNA and PDA were pooled together. A significant post-hoc test has been reported:
*=p<0.05
by
comparing the control group to the pathological one; c =p<0.001: significant difference by comparing
the ST to DT; f =p<0.001: significant difference by comparing WF to T60; i =p<0.001: significant
difference by comparing T60 to T120; n=p<0.001: significant difference by comparing WF to T120
(same legend as in Tables 2and 3).
Finally, iso-velocity curves were calculated for each group and condition to understand the
complex interaction between stride length and frequency in determining the walk velocity (Figure 5).
During the straight gait (Figure 5, panel a), in single tasking, the patients with PD used the same
step frequency compared to controls, but they walked with a shorter stride length. As a consequence,
their walking velocities were lower. During the dual task, all curves moved down and to the left:
this implied a decrease in the walking speed for controls and patients, and the ratio between the stride
length and step frequency was the same.
Symmetry 2020,12, 1284 9 of 14
Symmetry2020,12,xFORPEERREVIEW10of15
comparingtheSTtoDT;f=p<0.001:significantdifferencebycomparingWFtoT60;i=p<0.001:
significantdifferencebycomparingT60toT120;n=p<0.001:significantdifferencebycomparingWF
toT120(samelegendasinTables2and3).
Finally,iso‐velocitycurveswerecalculatedforeachgroupandconditiontounderstandthe
complexinteractionbetweenstridelengthandfrequencyindeterminingthewalkvelocity(Figure5).
Figure5.Stridelengthisplottedasafunctionofthestepfrequency(i.e.,theiso‐velocitycurves):(a)
walkingforward(WF);(b)turningat60°(T60);(c)turningat120°(T120).Thesymbolsreferto
differentgroupsasfollows:CRsinthesingletask●;CRsinthedualtask○;thePDNAinthesingle
task■;PDNAinthedualtask□;PDAinthesingletask▲;PDAinthedualtaskΔ.ForPDNA
Figure 5.
Stride length is plotted as a function of the step frequency (i.e., the iso-velocity curves):
(
a
) walking forward (WF); (
b
) turning at 60
◦
(T60); (
c
) turning at 120
◦
(T120). The symbols refer to
different groups as follows: CRs in the single task
•
; CRs in the dual task
#
; the PDNA in the single
task
; PDNA in the dual task
; PDA in the single task
N
; PDA in the dual task
∆
. For PDNA sometimes
the symbols are not seen because they exactly coincide with the data of the other two groups.
This trend occurs similarly in turning (Figure 5, panels b and c), independently of group and task.
Importantly, the most significant reduction in the walking velocity occurred while turning 120
◦
and
confirms that a larger angle of turning leads to a lower walking velocity.
Symmetry 2020,12, 1284 10 of 14
4. Discussion
The present study focused on the effects of dual task and turning on the kinematic parameters in
mild to moderate Parkinson’s disease. We hypothesized that the simple cognitive and mechanical
tasks will display similar effects in both populations, while the combination of these two stimuli will
show a higher impact on patients. We found that: (i) the temporal walking parameters were affected by
the mental task, as well as by the mechanical demand (turning), but no significant differences among
populations were observed. On the contrary, the stride length and walking speed were lower in PD
patients compared to controls; (ii) the turning task had the capability to alter the walking parameters,
especially in people with PD, and the major changes in the walking strategy have been observed while
turning at a larger angle (120
◦
); (iii) the combination of the cognitive and the mechanical task was
challenging for patients. Indeed, their stride length and walking velocity showed significant alterations
compared to controls in all walking conditions; finally, (iv) no significant differences were observed
between the not affected/more affected side in all the investigated parameters, suggesting an equal
symmetry between the right and left body side.
Taking them together, our results highlighted that a simple mental task alone is not sizeable
enough to alter the walking strategy in patients with PD with mild to moderate impairments, whereas
the combination of this cognitive task with a change of direction has the capability to modify the
walking strategy, especially with a higher turning angle (120◦).
4.1. Effects on Gait Variables: A Task Comparison
In single tasking, our data confirmed that patients with mild to moderate PD walked with a
reduced gait velocity and a shorter step length compared to controls. Therefore, patients showed a
lower locomotor index rehabilitation if compared to controls with no evident differences between
the not affected and more affected side. This finding suggests that the mild to moderate pathology
compromises, in a similar way, the gait kinematics of the inferior limbs (e.g., it did not compromise the
symmetry among body sides). Since, postural control and gait are linked to cognitive function both in
healthy and pathological subjects [
18
,
22
,
42
], it is possible to assume that PD patients reduced their
stride length in order to increase the time spent on the ground, increasing the walking stability.
As we hypothesized, a simple dual task condition (repeating the days of the week backwards)
affected both groups similarly: all participants increased the ground contact (and the cycle time) and
decreased their cadence and frequency [
12
,
19
]. This finding endorses that subjects tried to maintain their
postural stability by spending more time on the ground, as this would prevent the risk of falling [
18
].
The lack of a difference among groups confirms that, by adding a cognitive load, a low disease
severity could not play a major role in determining motor impairments [
23
]. In addition, the high
focus on the additional task means a larger proportion of the attentional capacity is at the expense of
walking performance: people walked even more slowly with much shorter steps [
7
,
12
,
15
,
22
,
43
–
46
].
This “compensatory strategy” could be useful in achieving a greater control of gait and balance
disruption [20], and in counterbalancing the fluctuations of the center of mass.
Finally, the similar ratio between the stride length and step frequency means that subjects did not
change their stride pattern. This latter outcome suggests that the simple cognitive task was probably
not too demanding for all participants. More complex cognitive tasks (i.e., concurrent loads, mental
tracking) would probably point out the gap among groups [19,20].
4.2. Effects on Gait Variables: A Direction Comparison
In the present study, we investigated two turning angles that are very common during daily
activity [38]: the first (60◦) represents a simple turn and the other (120◦) a more difficult turn.
Our spatiotemporal data are in line with the previous literature [
8
,
10
,
18
,
21
]. With respect to
directions, whereas healthy participants were impacted by the 120
◦
turn, PD patients were also affected
Symmetry 2020,12, 1284 11 of 14
by the 60
◦
turn, but only for the walking velocity. Additionally, in this case, no appreciable differences
between the not affected and more affected side were observed.
Generally, the 120
◦
turning is characterized by an increased support time and a reduced number
of strides (i.e., cadence) and frequency, as well as a decreased speed and length. This angle requires
additional attentional resources: in fact, it relies more heavily on proprioception (i.e., directed by the
basal ganglia function) than both forward walking and the 60
◦
turn [
47
]. By considering the mechanical
approach, the impact of a larger turning could be explained by the kinetics of the movement. Indeed,
to move into a larger angle of turn, the subjects decreased their speed more (just for a greater angle of
turn) and, probably, used their turn foot as “pivot foot”. When the turn angle increased, the ankle
plantar flexion moment (and its peak) increased and the external rotators of the lower extremity played
a much greater role than in straight walking [
48
–
50
]. These alterations of the plantar flexors have
been accomplished with a reduced ankle power generated in the pre-swing phase (push-offpower).
Therefore, the larger the angle of turn the higher the mechanical demand. As a result, PD patients
tended to reduce the step length and to increase the contact time primarily to improve the stability of
the body. They showed an initial alteration of the walking pattern at a 60
◦
turn, but only the walking
velocity was affected. On the other hand, a 120
◦
turn showed evident differences when compared to
the straight direction in terms of both the temporal and spatial parameters; this finding supports the
idea of a more challenging stimulus.
Therefore, whereas the 60
◦
turn could represent a not suitable training stimulus, the 120
◦
may be
a good challenge for people with PD. As expected, all gait alterations are exacerbated during walking
with a combination of the two stimuli, especially in PD patients.
4.3. Effects on Gait Variables: Cognitive Task and Mechanical Task
The combined effects of dual (cognitive) and mechanical (turn) tasks represent an important
training stimulus in people with PD. Indeed, our data shows that the concomitant presence of a simple
mental and turning (60
◦
) task produced only a marginal effect on the main kinematics. In particular,
the timing parameters showed no significant differences compared with the straight line, and the
differences between the single and dual task are comparable to the ones obtained for healthy subjects.
Furthermore, even the step length and the step frequency showed a similar trend.
On the contrary, the matching between the same mental task and a more complex mechanical
demand (120
◦
turn) played a greater “destructive” impact especially in patients with PD. Indeed, their
temporal and spatial variables showed a much more marked gap than the controls’ ones.
Our results were based on a relatively small heterogeneous sample of disabled patients, who
lived independently in the community. Therefore, further researches are necessary to extend these
findings to a larger sample (i.e., patients with more severe gait deficits or episodes of freezing), or to
other conditions (i.e., OFF phase performance).
5. Conclusions
Our data showed that a mechanical task (i.e., turning) has the potential to modify gait strategy in
people with Parkinson’s disease, without changes in symmetry of the lower limbs. Of greatest interest,
the concomitant presence of a mechanical task and a simple cognitive task did not produce a further
impairment of this gait strategy. Therefore, using the investigated combined condition (turning and
repeating the days of the week backwards) could represent a significant training stimulus in such
patients. Indeed, the improvement of the mental and physical characteristics is very important in
improving the functionality of patients at the early stages of their pathology.
Author Contributions:
Conceptualization, F.N., F.B., A.M., M.B.; methodology, F.N., A.M.; software, F.N., E.B.;
data curation, F.N., E.B., A.M.; writing—original draft preparation, F.N., A.M., M.B.; writing—review and editing,
F.N., A.M., M.B. All authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Symmetry 2020,12, 1284 12 of 14
Acknowledgments:
We would like to thank Alessandro Corsi, Gianluca Fedel and Davide Nisi for their help in
data collection, and the subjects for participating in the study.
Conflicts of Interest:
The authors acknowledge that there are no conflicts of interest pertaining to this manuscript.
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