Parkinson Disease Clinical Trial
Official title:
Autocorrelated Rhythmic Auditory Stimulations as the Best Way to Use a Metronome for Parkinson's Disease Patients: a Prospective Cohort Study
Parkinson's Disease (PD) patients suffer from gait impairments responsible for falls and bad quality of life: reduced speed and stride length, randomness in stride duration variability (reduced Long-Range Autocorrelations (LRA)). Authors showed beneficial effects of isochronic Rhythmic Auditory Stimulation (RAS) on stride length and speed but a deleterious effect on LRA. The aim of this prospective cohort study was to compare between 3 different RAS (isochronic, random and autocorrelated) on 9 PD patients' gait parameters and stride duration variability. Although the autocorrelated RAS (AC) does not improve the LRA present in the stride duration variability, the AC does, however, maintain an acceptable level of LRA for PD patients' gait stability. The autocorrelated RAS would therefore possibly be the best way to apply auditory cueing to PD patients but this must be confirmed by future longitudinal studies.
BACKGROUND
Basal Ganglia dysfunction in Parkinson's Disease (PD) induces gait impairment such as shorter
stride length, reduced gait speed, reduced arm swing and an increased randomness in stride
duration variability of gait cycles. This increased randomness in gait variability is a
typical symptom which can lead to falls, autonomy loss and reduced quality of life. Recently,
the Long-Range Autocorrelations (LRA) assessment allowed to emphasize the deterioration of
the temporal organization of PD patients' gait variability and demonstrated correlations with
disease severity and balance status. These LRA involve a long-memory process which means that
every stride depends on the duration of the previous near and far strides. Gait variability
should be balanced and should stay in an optimal framework between randomness and
over-regularity. This means that LRA should be balanced to keep the healthy adaptive
capabilities of the system, to be in the "Optimal Movement Variability" which allows the
person to move in a stable but still adaptive way. LRA measurement would therefore be the
first quantitative biomarker of gait instability and risk of falling, which is of particular
clinical interest.
It is now well known that PD patients have a greater gait variability with a decrease of the
LRA. That means that PD patients are more likely to fall which lowers the quality of life. It
is also well known that gait disorders do not respond well to dopaminergic pharmacological
treatments. Therefore, it seems important to develop non-pharmacological treatments to
improve LRA. Rhythmic Auditory Stimulation (RAS), by mean of a metronome, has been studied
for years to improve PD patients' gait. Authors showed that the use of a fixed-tempo
isochronic RAS reduced the stride duration variability, acting like an external rhythm
generator and bypassing the basal ganglia that act like an impaired internal rhythm generator
in PD patients. It is then suggested that a broader use of a isochronic RAS, by the mean of a
metronome, should be beneficial in gait rehabilitation for PD patients' gait parameters, such
as gait speed, stride length, stride duration variability and quality of life.
However, it has been demonstrated that the use of a isochronic RAS decreases LRA in healthy
persons and also PD patient. Authors suggested that the cognitive load required by a
isochronic RAS would be too elevated for PD patients, creating a dual tasking and diminishing
its applicability in a cueing device. This RAS would compel patients to a stereotyped gait
instead of an adaptive autocorrelated gait. Then the question is: Should clinicians continue
to use an isochronic RAS by the mean of a metronome for PD patients' gait rehabilitation ? Or
should clinicians use autocorrelated RAS to avoid loss of adaptivity but still get the
beneficial effects of the metronome ? The objective of this study was to analyze the effects
of 3 different RAS (isochronic metronome, autocorrelated metronome and random metronome) on
PD patients' gait parameters and stride duration variability (magnitude and temporal
organization).
METHODS
Patients
This study was unicentric. Nine PD patients participated in the study and were recruited from
the department of Neurology of Cliniques universitaires Saint-Luc (Brussels, Belgium). The
study was approved by the local ethics committee. All patients gave informed written consent
to the study. Eligibility criteria will be described in another section.
Procedure
Patients were asked to walk around 4 times (1 time for each condition presented below) on an
oval indoor track of 42 m during 10 minutes each time to get 512 consecutive strides
necessary to measure the LRA. The indoor track was chosen in order to collect data in a
standardized way and to avoid bias linked to environmental conditions that could potentially
affect patients' balance, such as terrain and/or weather conditions. Two unidimensional
accelerometers were taped on patients' both lateral malleoli in the antero-posterior
direction. These accelerometers were connected to a recording device (Vitaport 3 - Temec
Instruments B.V., Kerkrade, The Netherlands) attached to the patients' waist. This system
allowed to record at 512 Hz each positive acceleration peak that correspond to each heel
strike. The peak of acceleration, detected by the software internally developed, determined
the stride duration.
Four conditions were presented to patients in a randomized order. One condition consisted on
walking without any RAS (Spontaneous Condition, SC). The three other conditions were
respectively the Isochronic tempo RAS Condition (IC), the Random RAS Condition (RC) and the
Autocorrelated RAS Condition (AC). Each of these three conditions consisted in walking with
slight RAS which differ by their temporal organization. Each of them were composed with the
software Matlab 2014R (Mathworks, M.A.) and adapted to each patient according to spontaneous
gait speed determined by a 10m Walk Test achieved before the experiment. Consequently the IC,
RC and AC respectively contained no RAS variation, random variation of the RAS and
autocorrelated RAS organized in time and characterized by a Hurst (H) exponent = 0.80. To
resume, even if these three RAS had the same mean of the interbeat duration, RAS differ from
each other by the presence or the absence of rhythm variations (different H and alpha
exponents). During the experiment, patients were listening to the RAS through earphones
(Apple EarPods) by the mean of a MP3 player.
Before data collection, patients listened to the RAS and were asked to mark the rhythm with a
finger tapping to see if the temporal structure of the RAS was accurately detected. After
this, patients were asked to "walk accordingly to the proposed rhythm". A minimum of 10
minutes is necessary to get 512 consecutive gait cycles (number required for the application
of the signal processing methods detailed below). The heading direction taken by the patients
(clockwise or counterclockwise) was randomized between them but each patient kept the same
heading direction after randomization. The experiment was always performed at the same time
of the day for the same patient during ON phase of dopaminergic treatment to avoid drug
effect. Furthermore, a maximum of two conditions were tested during one day with a minimum
break of 5 minutes between each of the conditions to avoid a fatigue effect. Patients
returned a second day to perform the other 2 conditions.
Functional assessment
Functional assessments covered the 3 domains of International Classification of Functioning,
Disability and Health (ICF) : body functions and structures, activity and participation.
Assessments will be described in another section.
Gait assessment
Data were extracted from 512 consecutive gait cycles which is required to measure gait
variability.
Spatiotemporal gait variables
Mean gait speed, gait cadence and stride length were measured as follow:
- Mean gait speed (m.s-1) = Total walking distance (m)/ Acquisition duration (s)
- Gait cadence (#steps.min-1) = Total number of steps (#)/Acquisition duration (min)
- Step length (m) = Gait speed (m/s)*60/Gait cadence (steps/min)
Stride duration variability
Stride duration variability can be assessed 2 ways: in terms of magnitude or in terms of
organization (how stride duration evolves across consecutive gait cycles).
Magnitude of the stride duration variability:
To determine the effect of the RAS on the magnitude of the stride duration variability during
512 gait cycles, the mean, the standard deviation (SD) and the coefficient of variation (CV =
[SD/mean] * 100) were assessed.
Temporal organization of the stride duration variability (LRA):
Three methods (Rescaled Range Analysis (Hurst exponent; H), Power Spectral Density (α
exponent) and d relationship (d = H- [(1+ α)/2])) and the "surrogate data tests" were used to
measure LRA. The presence of LRA can be shown with a high level of proof when these 3
conditions are met:
- H is greater than 0.5
- α is significantly different from 0 and less than 1
- d ≤ 0.10 If an inconsistency appears between H and α, the Randomly Shuffled Surrogate
Data Test is applied in order to reject null hypothesis of an absence of temporal
structure in studied series.
Data were treated by the mean of CVI Labwindows (C++).
Statistical analysis:
Statistical analyses were conducted using SigmaPlot 13.0. A one-way repeated measures ANOVA
was applied to determine the presence or absence of effect of the various RAS on
spatiotemporal gait parameters (gait speed, gait cadence, stride length) and on stride
duration variability (linear measures (mean, SD, CV) and nonlinear measures (H exponent and
α)). Another one-way repeated measures ANOVA was applied to analyze the variability of the
inter-beat duration of the RAS (linear and nonlinear measures). When a significant difference
between groups was detected with the ANOVA, a post hoc Tukey Test was performed to compare
each mean with the other means to isolate the groups from each other. Spearman's correlation
coefficient was measured to analyze the link between the nonlinear measures (H, α) of the
stride duration and the inter-beat duration of the RAS. The results were considered
statistically different for p-values < 0.05.
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