Autocorrelated Rhythmic Auditory Stimulations for Parkinson's Disease Patients

Study Overview
=================
Brief Summary
-----------------
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.

Detailed Description
-----------------
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.

Official Title
-----------------
Autocorrelated Rhythmic Auditory Stimulations as the Best Way to Use a Metronome for Parkinson's Disease Patients: a Prospective Cohort Study

Conditions
-----------------
Parkinson Disease

Intervention / Treatment
-----------------
* Device: Metronome


Participation Criteria
=================
Eligibility Criteria
-----------------
Inclusion Criteria: Idiopathic Parkinson's Disease according to UK Brain Bank criteria A modified Hoehn & Yahr scale between 1 and 3 Able to walk for at least 10 minutes in a row Dopaminergic was stable for a minimum of 4 weeks before the study starts A Mini-Mental State Examination (MMSE) >24 Exclusion Criteria: Severe co-morbidity, other neurological problems, acute medical problems (e.g. MI, diabetes) and joint problems affecting mobility Unpredictable Off-periods (score >2, MDS-UPDRS item 4.5)
Sexes Eligible for Study
-----------------
All

Accepts Healthy Volunteers
-----------------
No

Study Plan
=================
How is the study designed?
-----------------

Design Details

Primary Purpose: Other
Intervention Model: Single Group Assignment
Interventional Model Description: A single group of 9 patients completed the 4 conditions presented in the Methods section.
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Parkinson's Disease patients<br> | Device: Metronome<br>* Patients completed 4 walking sessions of at least 10 minutes each. During each session, no auditory rhythm was given, or the rhythm of a Rhythmic Auditory Stimulation (RAS) adapted to the pace of comfort of each patient using a metronome was broadcasted via headphones. In all, 4 conditions were tested: walk with no RAS or an isochronous RAS or a random RAS or a RAS with an autocorrelated metronome rhythm.<br>|

What is the study measuring?
-----------------
Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Long-Range Autocorrelations |  | Change from baseline in long-range autocorrelations during each intervention condition (2 days, 2 x 10 min walking each day) | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Mean gait speed | Total walking distance (m)/ Acquisition duration (s) | Change from baseline in mean gait speed during each intervention condition (2 days, 2 x 10 min walking each day) | 
| Step length | Gait speed (m/s)*60/Gait cadence (steps/min) | Change from baseline in step length during each intervention condition (2 days, 2 x 10 min walking each day) | 
| Gait cadence | Total number of steps (#)/Acquisition duration (min) | Change from baseline in gait cadence during each intervention condition (2 days, 2 x 10 min walking each day) | 
| Coefficient of variation of stride duration | [SD/mean stride duration] * 100 | Change from baseline in coefficient of variation during each intervention condition (2 days, 2 x 10 min walking each day) | 

 Terms related to the study
=================
Keywords Provided by Centre Hospitalier Valida
-----------------
Parkinson's Disease, rhythmic auditory stimulation, cueing, Long-Range Autocorrelations