scholarly journals Step Length Is a Promising Progression Marker in Parkinson’s Disease

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2292
Author(s):  
Julius Welzel ◽  
David Wendtland ◽  
Elke Warmerdam ◽  
Robbin Romijnders ◽  
Morad Elshehabi ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Disease Progression ◽  
Step Length ◽  
Minor Effect ◽  
Progression Marker ◽  
Gait Parameters ◽  
Ancova Model ◽  
Length Changes ◽  
A Minor

Current research on Parkinson’s disease (PD) is increasingly concerned with the identification of objective and specific markers to make reliable statements about the effect of therapy and disease progression. Parameters from inertial measurement units (IMUs) are objective and accurate, and thus an interesting option to be included in the regular assessment of these patients. In this study, 68 patients with PD (PwP) in Hoehn and Yahr (H&Y) stages 1–4 were assessed with two gait tasks—20 m straight walk and circular walk—using IMUs. In an ANCOVA model, we found a significant and large effect of the H&Y scores on step length in both tasks, and only a minor effect on step time. This study provides evidence that from the two potentially most important gait parameters currently accessible with wearable technology under supervised assessment strategies, step length changes substantially over the course of PD, while step time shows surprisingly little change in the progression of PD. These results show the importance of carefully evaluating quantitative gait parameters to make assumptions about disease progression, and the potential of the granular evaluation of symptoms such as gait deficits when monitoring chronic progressive diseases such as PD.

scholarly journals Gait Training Methods and ChangesiIn Gait Parameters in Parkinson`s Disease (Literature Review)

2020 ◽  
Vol 2 (7) ◽  
Author(s):  
Aušra Stuopelytė ◽  
Rasa Šakalienė
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Step Length ◽  
Gait Training ◽  
Auditory Stimulation ◽  
Training Methods ◽  
Dual Tasking ◽  
Gait Parameters ◽  
Rhythmic Auditory Stimulation ◽  
Walking Velocity

Parkinson’s disease is a chronic progressive neurological disorder that can impact function to a variable degree. Changes in gait parameters are the most common signs of Parkinson’s disease. Patients with Parkinson’s disease walk with a reduced step length, step time, walking velocity and walking cadence, increased stride cycle time, coefficient of variation of the step amplitude and step time and increased risk to fall. So, various gait training methods are applied. The effect of rhythmic auditory stimulation on gait in Parkinson’s disease patients is analysed. We can use various kinds of music, metronome, scansion and clapping as a rhythmic auditory stimulation.One of gait training methods in Parkinson’s disease patients is treadmill training. There are attempts to combine treadmill training with transcranial magnetic stimulation and virtual reality. We can use Nordic walking method and because walking technique requires straight posture, trunk rotation, bigger step and heel stride. More often robot–assisted gait training is used in patients with Parkinson’s disease gait training. The effect of dual–tasking and walking with music methods for gait and balance training in patients with Parkinson’s disease is also analysed. This method requires participants to perform primary and secondary tasks at the same time. The secondary task can be cognitive or motor. Dual–tasking is widely analysed because opinions about applying this method are very controversial. Walking with music method is more often analysed in scientific literature. This method could not be compared to rhythmic auditory stimulation method because the latter requires precise walking to rhythm and walking with music method is oriented to emotional component (music is chosen according patients’ music taste). As these methods are applied, we can see an increase in chosen walking and maximal walking velocities, step length and time, distance covered, and decrease in the coefficient of variation of the step time and turning time.Keywords: Gait impairments, walking velocity, rhythmic auditory stimulation.

scholarly journals Influence of Autocorrelated Rhythmic Auditory Stimulations on Parkinson’s Disease Gait Variability: Comparison With Other Auditory Rhythm Variabilities and Perspectives

2020 ◽  
Vol 11 ◽  
Author(s):  
Alexis Lheureux ◽  
Thibault Warlop ◽  
Charline Cambier ◽  
Baptiste Chemin ◽  
Gaëtan Stoquart ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Long Range ◽  
Coefficient Of Variation ◽  
Gait Speed ◽  
Step Length ◽  
Temporal Organization ◽  
Fluctuation Analysis ◽  
Gait Parameters ◽  
Stride Duration

Parkinson’s Disease patients suffer from gait impairments such as reduced gait speed, shortened step length, and deterioration of the temporal organization of stride duration variability (i.e., breakdown in Long-Range Autocorrelations). The aim of this study was to compare the effects on Parkinson’s Disease patients’ gait of three Rhythmic Auditory Stimulations (RAS), each structured with a different rhythm variability (isochronous, random, and autocorrelated). Nine Parkinson’s Disease patients performed four walking conditions of 10–15 min each: Control Condition (CC), Isochronous RAS (IRAS), Random RAS (RRAS), and Autocorrelated RAS (ARAS). Accelerometers were used to assess gait speed, cadence, step length, temporal organization (i.e., Long-Range Autocorrelations computation), and magnitude (i.e., coefficient of variation) of stride duration variability on 512 gait cycles. Long-Range Autocorrelations were assessed using the evenly spaced averaged Detrended Fluctuation Analysis (α-DFA exponent). Spatiotemporal gait parameters and coefficient of variation were not modified by the RAS. Long-Range Autocorrelations were present in all patients during CC and ARAS although all RAS conditions altered them. The α-DFA exponents were significantly lower during IRAS and RRAS than during CC, exhibiting anti-correlations during IRAS in seven patients. α-DFA during ARAS was the closest to the α-DFA during CC and within normative data of healthy subjects. In conclusion, Isochronous RAS modify patients’ Long-Range Autocorrelations and the use of Autocorrelated RAS allows to maintain an acceptable level of Long-Range Autocorrelations for Parkinson’s Disease patients’ gait.

scholarly journals Association of SNCA Parkinson's Disease Risk Polymorphisms With Disease Progression in Newly Diagnosed Patients

2021 ◽  
Vol 11 ◽  
Author(s):  
Aleksandra A. Szwedo ◽  
Camilla Christina Pedersen ◽  
Anastasia Ushakova ◽  
Lars Forsgren ◽  
Ole-Bjørn Tysnes ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Confidence Interval ◽  
Disease Progression ◽  
Mental State ◽  
Mini Mental State Examination ◽  
Rating Scale ◽  
Minor Effect ◽  
The Impact ◽  
State Examination

Objectives: To evaluate the impact of SNCA polymorphisms originally identified as risk factors for Parkinson's disease (PD) on the clinical presentation and progression of the disease in a large cohort of population-based patients with incident PD.Methods: Four hundred thirty-three patients and 417 controls from three longitudinal cohorts were included in the study. Disease progression was recorded annually for up to 9 years using the Unified Parkinson's Disease Rating Scale (UPDRS) or Mini-Mental State Examination. Genotypes for five variants within the SNCA locus (rs2870004, rs356182, rs5019538, rs356219, and rs763443) were determined. We studied the association between each variant and disease progression using linear mixed-effects regression models.Results: The clinical profile of the patients with PD at the point of diagnosis was highly uniform between genotype groups. The rs356219-GG genotype was associated with a higher UPDRS II score than A-allele carriers (β = 1.52; 95% confidence interval 0.10–2.95; p = 0.036), but no differences were observed in the rate of progression of the UPDRS II scores. rs356219-GG was also associated with a faster annual change in Mini-Mental State Examination score compared with A-carriers (β = 0.03; 95% confidence interval 0.00–0.06; p = 0.043).Conclusions: We show that the known PD-risk variant rs356219 has a minor effect on modifying disease progression, whereas no differences were associated with rs2870004, rs356182, rs5019538, and rs763443. These findings suggest that SNCA variants associated with PD risk may not be major driving factors to the clinical heterogeneity observed for PD.

scholarly journals Contribution of Step Length to Increase Walking and Turning Speed as a Marker of Parkinson’s Disease Progression

PLoS ONE ◽  
2016 ◽  
Vol 11 (4) ◽  
pp. e0152469 ◽  
Author(s):  
Nicolas Bayle ◽  
Amar S. Patel ◽  
Diana Crisan ◽  
Lanjun J. Guo ◽  
Emilie Hutin ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Disease Progression ◽  
Step Length

Corelation of gait parameters, cognitive impairment and brain atrophy in patients with Parkinson’s disease and the «normally aging population»

2021 ◽  
Author(s):  
P. Y. Diachenko ◽  
I. I. Leta ◽  
G. S. Moskovko
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Function ◽  
Brain Atrophy ◽  
Stride Length ◽  
Aging Population ◽  
Step Length ◽  
Normal Aging ◽  
Gait Velocity ◽  
Gait Parameters

Objective — to identify the most significant markers of gait that indicate a decrease in cognitive function based on investigation of the corelation of cognitive impairment, gait parameters and atrophy of brain structures in groups of patients with Parkinson’s disease and the «normally aging population». Methods and subjects. 66 subjects were examined: 30 patients with Parkinson’s disease (mean age 54.9 ± 5.9, 50 % men) and 33 without neurological pathology (mean age 52.7 ± 7.6, 66 % men). All of them underwent neurological examination, assessment of temporal and spatial gait parameters using the GaitRite system, grading of brain atrophy using a comprehensive visual rating scale of MRI scans and assessment of cognitive status using the Montreal Cognitive Assessment Scale. Results. Cognitive performance was significantly lower in the subgroup of patients with Parkinson’s disease compared to the subgroup of «normally aging population». The gait profile of patients with Parkinson’s disease significantly differed from the gait profile of individuals from the «normal aging» subgroup by slower gait velocity, shorter step length and stride length for both limbs. The gait parameters, which showed a strong correlation with cognitive tests, differed in the subgroups, but gait velocity, stride length and step length for both extremities were common among them. These common gait parameters showed a strong direct correlation with brain atrophy in the subgroup of patients with Parkinson’s disease, but only velocity correlated with atrophy in the subgroup of «normal aging» among all of them. It was determined by the method of multiple regression analysis that it was precisely the atrophy of the brain that turned out to be the most influential factor in the decrease in cognitive function in the general group and subgroups. Conclusions. The gait profile in Parkinson’s disease subgroup is characterized by lower velocity, shorter step length, stride length for both limbs and significantly differs from the subgroup of «normal aging». These changes are a consequence of the influence of the disease on the motor sphere. Velocity showed a strong correlation in both subgroups not only with cognitive abilities, but also with cerebral atrophy. This confirms the hypothesis about the possibility of using gait velocity as a universal sensitive marker for current and longitudinal assessment of cognitive function, especially in clinical practice.  

scholarly journals The Effects of Metronome Frequency Differentially Affects Gait on a Treadmill and Overground in People with Parkinson’s Disease

2019 ◽  
Author(s):  
Madelon Wygand ◽  
Guneet Chawla ◽  
Nina Browner ◽  
Michael D Lewek
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Gait Speed ◽  
Repeated Measures ◽  
Step Length ◽  
Yahr Stage ◽  
Gait Parameters ◽  
Walking Environment ◽  
Stage 1 ◽  
Walking Speeds

AbstractObjectiveTo determine the effect of different metronome cue frequencies on spatiotemporal gait parameters when walking overground compared to walking on a treadmill in people with Parkinson’s diseaseDesignRepeated-measures, within-subject designSettingResearch laboratoryParticipantsTwenty-one people with Parkinson’s disease (Hoehn & Yahr stage 1-3)InterventionsParticipants walked overground and on a treadmill with and without metronome cues of 85%, 100%, and 115% of their baseline cadence for one minute each.Main Outcome MeasuresGait speed, step length, and cadenceResultsAn interaction effect between cue frequency and walking environment revealed that participants took longer steps during the 85% condition on the treadmill only. When walking overground, metronome cues of 85% and 115% of baseline cadence yielded decreases and increases, respectively, in both cadence and gait speed with no concomitant change in step length.ConclusionsThese data suggest that people with PD are able to alter spatiotemporal gait parameters immediately when provided the appropriate metronome cue and walking environment. We propose to target shortened step lengths by stepping to the beat of slow frequency auditory cues while walking on a treadmill, whereas the use of fast frequency cues during overground walking can facilitate faster walking speeds.

scholarly journals A Wearable Sensor System to Measure Step-Based Gait Parameters for Parkinson’s Disease Rehabilitation

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6417 ◽  
Author(s):  
Niveditha Muthukrishnan ◽  
James J. Abbas ◽  
Narayanan Krishnamurthi
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Young Adults ◽  
Excellent Agreement ◽  
Step Length ◽  
Optoelectronic System ◽  
Data Set ◽  
Single Measure ◽  
Complete Representation ◽  
Gait Parameters

Spatiotemporal parameters of gait serve as an important biomarker to monitor gait impairments as well as to develop rehabilitation systems. In this work, we developed a computationally-efficient algorithm (SDI-Step) that uses segmented double integration to calculate step length and step time from wearable inertial measurement units (IMUs) and assessed its ability to reliably and accurately measure spatiotemporal gait parameters. Two data sets that included simultaneous measurements from wearable sensors and from a laboratory-based system were used in the assessment. The first data set utilized IMU sensors and a GAITRite mat in our laboratory to monitor gait in fifteen participants: 9 young adults (YA1) (5 females, 4 males, age 23.6 ± 1 years), and 6 people with Parkinson’s disease (PD) (3 females, 3 males, age 72.3 ± 6.6 years). The second data set, which was accessed from a publicly-available repository, utilized IMU sensors and an optoelectronic system to monitor gait in five young adults (YA2) (2 females, 3 males, age 30.5 ± 3.5 years). In order to provide a complete representation of validity, we used multiple statistical analyses with overlapping metrics. Gait parameters such as step time and step length were calculated and the agreement between the two measurement systems for each gait parameter was assessed using Passing–Bablok (PB) regression analysis and calculation of the Intra-class Correlation Coefficient (ICC (2,1)) with 95% confidence intervals for a single measure, absolute-agreement, 2-way mixed-effects model. In addition, Bland–Altman (BA) plots were used to visually inspect the measurement agreement. The values of the PB regression slope were close to 1 and intercept close to 0 for both step time and step length measures. The results obtained using ICC (2,1) for step length showed a moderate to excellent agreement for YA (between 0.81 and 0.95) and excellent agreement for PD (between 0.93 and 0.98), while both YA and PD had an excellent agreement in step time ICCs (>0.9). Finally, examining the BA plots showed that the measurement difference was within the limits of agreement (LoA) with a 95% probability. Results from this preliminary study indicate that using the SDI-Step algorithm to process signals from wearable IMUs provides measurements that are in close agreement with widely-used laboratory-based systems and can be considered as a valid tool for measuring spatiotemporal gait parameters.

scholarly journals Quantifying Spatiotemporal Gait Parameters with HoloLens in Healthy Adults and People with Parkinson’s Disease: Test-Retest Reliability, Concurrent Validity, and Face Validity

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3216
Author(s):  
Daphne J. Geerse ◽  
Bert Coolen ◽  
Melvyn Roerdink
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Concurrent Validity ◽  
Walking Speed ◽  
Step Length ◽  
Face Validity ◽  
Retest Reliability ◽  
Gait Parameters ◽  
Position Data ◽  
Test Retest Reliability

Microsoft’s HoloLens, a mixed-reality headset, provides, besides holograms, rich position data of the head, which can be used to quantify what the wearer is doing (e.g., walking) and to parameterize such acts (e.g., speed). The aim of the current study is to determine test-retest reliability, concurrent validity, and face validity of HoloLens 1 for quantifying spatiotemporal gait parameters. This was done in a group of 23 healthy young adults (mean age 21 years) walking at slow, comfortable, and fast speeds, as well as in a group of 24 people with Parkinson’s disease (mean age 67 years) walking at comfortable speed. Walking was concurrently measured with HoloLens 1 and a previously validated markerless reference motion-registration system. We comprehensively evaluated HoloLens 1 for parameterizing walking (i.e., walking speed, step length and cadence) in terms of test-retest reliability (i.e., consistency over repetitions) and concurrent validity (i.e., between-systems agreement), using the intraclass correlation coefficient (ICC) and Bland–Altman’s bias and limits of agreement. Test-retest reliability and between-systems agreement were excellent for walking speed (ICC ≥ 0.861), step length (ICC ≥ 0.884), and cadence (ICC ≥ 0.765), with narrower between-systems than over-repetitions limits of agreement. Face validity was demonstrated with significantly different walking speeds, step lengths and cadences over walking-speed conditions. To conclude, walking speed, step length, and cadence can be reliably and validly quantified from the position data of the wearable HoloLens 1 measurement system, not only for a broad range of speeds in healthy young adults, but also for self-selected comfortable speed in people with Parkinson’s disease.

scholarly journals External cueing on gait parameters in Parkinson’s Disease

2019 ◽  
Vol 10 (3) ◽  
pp. 2452-2456
Author(s):  
Deepa S ◽  
Ramana K
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Motor Task ◽  
Step Length ◽  
Gait Pattern ◽  
Motor Symptom ◽  
Walking Ability ◽  
Abnormal Gait ◽  
Gait Parameters ◽  
Post Test

Parkinson’s disease which is characterized by paucity of movement, leading to the abnormal gait parameters. The gait pattern is characterized by shuffling as festinant gait. Freezing is an incapacitating motor symptom is also one of the leading causes of gait abnormality leading to falls. Cueing strategy evokes a more goal-directed type of motor control results in improved gait parameters. Aims and Objectives:-The purpose of this study to find the effectiveness of external cueing on the gait parameters as cadence, step length and stride length. Materials and Methodology: - 30 subjects diagnosed as Parkinson’s disease were randomly assigned to three groups, the walking ability was assessed using a 10 meter walk test, and pre test score was recorded. The external cueing technique was applied for a session of 4 days per week for 4 weeks; each session lasted for about 30 minutes, at the end for 4 weeks the post test scores were recorded. Results: - External cueing with a combination of audio- visual showed significant improvement in the gait parameters. Conclusion: - The improvement showed in the pre test to post test reflected the need for introducing the external cueing in improving gait and attention during a motor task. 

Quantitative Gait Analysis Using a Pose-Estimation Algorithm with a Single 2D-Video of Parkinson’s Disease Patients

2021 ◽  
pp. 1-13
Author(s):  
Jung Hwan Shin ◽  
Ri Yu ◽  
Jed Noel Ong ◽  
Chan Young Lee ◽  
Seung Ho Jeon ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Pose Estimation ◽  
Estimation Algorithm ◽  
Step Length ◽  
Video Tracking ◽  
Gait Velocity ◽  
Gait Parameters ◽  
Validation Experiment ◽  
Time Required

Background: Clinician-based rating scales or questionnaires for gait in Parkinson’s disease (PD) are subjective and sensor-based analysis is limited in accessibility. Objective: To develop an easily accessible and objective tool to evaluate gait in PD patients, we analyzed gait from a single 2-dimensional (2D) video. Methods: We prospectively recorded 2D videos of PD patients (n = 16) and healthy controls (n = 15) performing the timed up and go test (TUG). The gait was simultaneously evaluated with a pressure-sensor (GAITRite). We estimated the 3D position of toes and heels with a deep-learning based pose-estimation algorithm and calculated gait parameters including step length, step length variability, gait velocity and step cadence which was validated with the result from the GAITRite. We further calculated the time and steps required for turning. Then, we applied the algorithm to previously recorded and archived videos of PD patients (n = 32) performing the TUG. Results: From the validation experiment, gait parameters derived from video tracking were in excellent agreement with the parameters obtained with the GAITRite. (Intraclass correlation coefficient > 0.9). From the analysis with the archived videos, step length, gait velocity, number of steps, and the time required for turning were significantly correlated (Absolute R > 0.4, p < 0.005) with the Freezing of gait questionnaire, Unified PD Rating scale part III total score, HY stage and postural instability. Furthermore, the video-based tracking objectively measured significant improvement of step length, gait velocity, steps and the time required for turning with antiparkinsonian medication. Conclusion: 2D video-based tracking could objectively evaluate gait in PD patients.

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