Gait Pattern Analysis in Neurological Disease (NCT02994719)

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Overview

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Characterizing Gait Abnormalities in PSP and Parkinsonian Disorders

Trial Summary

...

Overview

Mermaid diagram (expand to render)

Characterizing Gait Abnormalities in PSP and Parkinsonian Disorders

Trial Summary

| Field | Details |
|-------|---------|
| NCT Number | NCT02994719 |
| Title | Gait Pattern Analysis in Neurological Disease |
| Status | RECRUITING |
| Study Type | Observational (Case-Control) |
| Sponsor | Beth Israel Deaconess Medical Center |
| Principal Investigator | Veronique Vanderhorst, MD, PhD |
| Location | Boston, Massachusetts, USA |

Scientific Rationale

Gait dysfunction is a hallmark of Progressive Supranuclear Palsy (PSP), presenting distinct patterns that differentiate it from other parkinsonian disorders. Key gait characteristics in PSP include:

Reduced gait velocity - significantly slower than age-matched controls
Increased stride variability - reflecting impaired postural control
Reduced arm swing - bilateral and often symmetric
Forward flexion - truncal stooping during walking
Retropulsion - tendency to fall backward
Wide-based gait - increased stance phase width

This study aims to identify speed-dependent gait measures that can objectively quantify these abnormalities and potentially serve as biomarkers for disease progression and therapeutic response.[@clinicaltrialsgov]

Study Design

Primary Objectives

Identify speed-dependent gait measures in parkinsonian disorders
Determine whether gait patterns differ between:
Parkinson's Disease (PD)
Progressive Supranuclear Palsy (PSP)
Multiple System Atrophy (MSA)
Corticobasal Degeneration (CBD)
Vascular Parkinsonism
Other parkinsonian syndromes
Compare patient gait patterns to age- and sex-matched healthy controls

Assessments

Primary: Gait analysis using pressure sensors
Optional interventions at second visit:
Anti-Parkinson medication challenge (Carbidopa/levodopa, pramipexole, ropinirole, amantadine, tolcapone, entacapone)
Deep Brain Stimulation evaluation

Eligibility Criteria

Inclusion Criteria

Age 18-85 years
Presence of at least 2 of the following (UK PD Brain Bank Criteria):
Bradykinesia
Rest tremor
Rigidity
Postural instability
Subjects with assistive devices (canes, walkers) are eligible
Healthy subjects with no complaints regarding difficulty walking

Exclusion Criteria

Alternative explanation for parkinsonism (head trauma, drug-induced)
Currently treated for major medical illness requiring recent hospitalization (<14 days)
Currently participating in another clinical study with intervention arm
Inability to consent due to cognitive impairment without legally authorized representative
Cardiac/pulmonary conditions limiting ability to safely walk

Study Population

Includes subjects with:

[Parkinson's Disease](/diseases/parkinsons-disease)
Indeterminate parkinsonism
Atypical Parkinsonisms:
Vascular Parkinsonism
Multiple System Atrophy (MSA)
Progressive Supranuclear Palsy (PSP)
Normal Pressure Hydrocephalus
Corticobasal Degeneration (CBD)
Ataxia syndromes
Huntington Disease
Healthy controls

Clinical Significance for PSP

Biomarker Potential

Objective Measurement: Quantitative gait parameters provide objective disease progression markers

Differential Diagnosis: Distinct gait patterns may help differentiate PSP from PD

Therapeutic Response: Gait measures could assess response to treatments

Fall Risk: Identifying gait abnormalities associated with fall risk

PSP-Specific Gait Features

Reduced stride length with preserved cadence
Bilateral reduced arm swing (early feature)
Postural instability leading to backward falls
Freezing of gait in advanced disease
Response to levodopa typically minimal (distinguishes from PD)

Pathophysiology of Gait Disorders in PSP

Neuroanatomical Basis

Progressive supranuclear palsy (PSP) produces characteristic gait disturbances through degeneration of specific neural substrates:

Basal Ganglia Dysfunction: The globus pallidus interna (GPi) and substantia nigra pars reticulata (SNr) show early pathology in PSP, leading to:

Impaired automatic motor sequencing
Reduced stride length generation
Axial rigidity affecting trunk mobility
Bradykinesia of gait initiation

Brainstem Involvement: The pedunculopontine nucleus (PPN), critical for gait initiation and postural control, degenerates in PSP:

Impaired postural adjustments
Reduced automaticity of locomotion
Freezing of gait phenomenon
Gait ignition failure

Frontal Lobe Contribution: PSP produces frontal lobe atrophy affecting:

Executive motor control
Velocity scaling of gait
Adaptive responses to environmental demands
Dual-task gait performance

Quantitative Gait Parameters

The study employs instrumented walkway analysis to capture:

| Parameter | PSP Characteristic | Clinical Significance |
|-----------|--------------------|-----------------------|
| Gait Velocity | Severely reduced (0.3-0.5 m/s) | Global motor impairment |
| Stride Length | Markedly shortened (<60 cm) | Basal ganglia dysfunction |
| Cadence | Preserved or slightly reduced | Differentiates from PD |
| Double Support Time | Increased (>35% stance) | Postural instability |
| Swing Time Variability | Elevated (CV >10%) | Fall risk predictor |
| Arm Swing | Severely reduced bilaterally | Early diagnostic marker |
| Trunk Rotation | Reduced | Axial rigidity |

Speed-Dependent Analysis

The novel aspect of this study examines how gait parameters change across walking speeds:

Healthy Controls: Linear increase in velocity through stride length modulation while cadence remains relatively stable

PSP Patients:

Reduced stride length at all speeds
Impaired velocity scaling
Earlier onset of gait dysfunction at slower speeds
Preserved speed-dependent modulation but at reduced magnitude

This approach may reveal:

Subtle gait abnormalities not apparent at self-selected speed
Differentiate disease subtypes
Quantify reserve capacity in gait control systems

Differential Diagnosis Applications

PSP vs. Parkinson's Disease

| Feature | PSP | PD |
|---------|-----|-----|
| Arm swing | Bilateral reduction early | Unilateral, asymmetric early |
| Stride length | Severely reduced | Moderate reduction |
| Gait initiation | Often normal | Often impaired (shuffling) |
| Turning | En bloc turning | Shuffling turns |
| Postural falls | Early, backward | Late, any direction |
| Response to levodopa | Minimal | Good initially |

PSP vs. Multiple System Atrophy (MSA)

| Feature | PSP | MSA |
|---------|-----|-----|
| Gait pattern | Cautious, wide-based | Shuffling with festination |
| Stride variability | Increased | Very high |
| Freezing | Less common | More common |
| Autonomic involvement | Variable | Prominent early |

PSP vs. Corticobasal Degeneration (CBD)

| Feature | PSP | CBD |
|---------|-----|-----|
| Symmetry | Symmetric | Asymmetric |
| Arm swing | Bilaterally reduced | Unilaterally reduced |
| Gait initiation | Variable | Often延迟 |

Quantitative Gait Analysis Technology

Instrumented Walkway Systems

The study utilizes pressure-sensitive walkway technology:

Walkway Platforms:

GAITrite® systems (standard in research)
Zebris® FDM-T treadmill system
Protokinetics® PKMAS
Bertec® force instrumented treadmill

Technical Specifications:

| Parameter | Specification | Clinical Relevance |
|-----------|--------------|------------------|
| Spatial resolution | 1.27 mm | Foot placement accuracy |
| Temporal resolution | 100-200 Hz | Timing accuracy |
| Active sensor area | Variable (4-8m length) | Full gait capture |
| Pressure range | Up to 200 psi | Weight-bearing accuracy |
| Data rate | Up to 500 Hz | Real-time capture |

Temporal-Spatial Parameters

Primary Measures:

Temporal Parameters:

Stride time (time for complete gait cycle)
Step time (time between foot strikes)
Swing time (foot in air)
Stance time (foot on ground)
Single support time (contralateral foot in air)
Double support time (both feet on ground)

Spatial Parameters:

Stride length (distance covered per gait cycle)
Step length (heel strike to opposite heel strike)
Step width (mediolateral foot placement)
Foot rotation angle
Toe-out angle

Spatiotemporal Parameters:

Gait velocity (comfortable walking speed)
Cadence (steps per minute)
Variability measures (coefficient of variation)

Advanced Analysis Methods

Center of Pressure (COP):

Anterior-posterior COP excursion
Medial-lateral COP excursion
COP velocities
COP trajectory symmetry

Balance Assessment:

Sway area
Velocity of sway
Frequency distribution
Multi-scale entropy

Neuroanatomical Correlates

Basal Ganglia Contributions

The basal ganglia play a central role in gait control:

Direct Pathway (Go):

Facilitates voluntary movements
Promotes ongoing motor programs
Facilitates gait initiation
Reduced in PSP leading to akinesia

Indirect Pathway (Stop):

Inhibits competing movements
Prevents unwanted movement
Critical for stopping/gait adjustment
Overactive in PSP

Hyperdirect Pathway:

Rapid feedback inhibition
Error detection
Adaptive modifications

Brainstem Gait Centers

Pedunculopontine Nucleus (PPN):

Central pattern generator for locomotion
Cholinergic neurons for modulation

-Degeneration in PSP

Associated with gait freezing

Cuneate and Gracile Nuclei:

Sensory integration
Proprioceptive processing
Postural adjustments

Cerebellar Contributions

The cerebellum coordinates gait:

Spinocerebellar Pathways:

Proprioceptive feedback
Motor adaptation
Error correction

Cerebello-thalamo-cortical loops:

Motor learning
Automation of gait

Frontal Lobe Networks

Supplementary Motor Area (SMA):

Internal movement generation
Bilateral coordination
Impaired in PSP

Pre-SMA:

Sequence planning
Gait initiation
Abnormal in PSP

Dorsolateral Prefrontal Cortex:

Executive function
Dual-task performance
Planning gait modifications

Biomarker Development

Gait as a Biomarker

Gait parameters can serve as biomarkers:

Validation Requirements:

Reliability (test-retest consistency)
Validity (measures what it claims)
Sensitivity to change
Specificity for condition
Responsiveness to intervention

Clinical Applications

Diagnostic Aid:

Differentiating parkinsonian disorders
Early detection
Subtype classification

Progression Marker:

Disease severity staging
Progression rate
Prognostication

Therapeutic Response:

Medication effects
Surgical outcomes (DBS)
Rehabilitation benefits

Regulatory Status

Not FDA-approved biomarkers
Research use only
Potential for clinical implementation

Future Directions

Technology Development

Wearable Sensors:

Inertial measurement units
Accelerometers
Gyroscopes
Magnetometers

Home Monitoring:

Continuous monitoring
Fall detection
Activity tracking

Machine Learning:

Pattern recognition
Subtype classification
Predictive modeling

Research Applications

Earlier diagnosis
Personalized intervention
Telehealth integration

Assessment Protocols

Instrumented Gait Analysis System

The study utilizes pressure-sensitive walkway technology:

Walkway Dimensions: Minimum 6 meters length to capture steady-state gait

Sampling Rate: 100-200 Hz for accurate temporal detection

Spatial Resolution: <1 mm for precise foot placement measurement

Testing Protocol

Conditions Tested:

Preferred speed: Comfortable self-selected walking

Fast speed: Maximum comfortable speed without running

Slow speed: Slow as possible without stopping

Dual-task: Walking while performing cognitive task (serial 7s)

Treadmill (subset): Standardized speed assessment

Repeatability Measures: Three trials per condition to establish reliability

Clinical Correlation Assessments

MDS-UPDRS: Complete motor examination
PSPRS: PSP Rating Scale
MoCA: Cognitive screening
FR: Functional reach test
TUG: Timed up and go test

Medication Challenge Protocol

Rationale

The medication challenge component evaluates dopaminergic responsiveness:

Levodopa Challenge: Standard carbidopa/levodopa (25/100 mg) up to 200% of current dose

Dopamine Agonists: Pramipexole or ropinirole equivalent

Rationale:

Differentiate parkinsonian disorders
Identify PD patients who may benefit from DBS
Quantify levodopa-responsive component
Predict surgical outcomes

Assessment Timing

Baseline gait assessment
60-90 minutes post-medication
Peak-dose assessment
Comparison of pre/post parameters

Implications for Clinical Care

Biomarker Development

Quantitative gait analysis offers advantages as a biomarker:

Objective: No subjective interpretation required

Continuous: Provides interval-scale data

Repeatable: Low test-retest variability

Non-invasive: No radiation or invasive procedures

Cost-effective: Relatively inexpensive to implement

Sensitive: Detects subtle changes

Clinical Utility

This study may establish gait parameters for:

Early diagnosis (pre-motor detection)
Disease staging and progression monitoring
Therapeutic response assessment
Fall risk stratification
Prognostication

Future Applications

Successful validation could lead to:

Routine clinical gait assessment for movement disorder patients
Telemedicine-enabled remote monitoring
Home-based gait monitoring with wearable sensors
Integration with digital health platforms

Comparative Gait Research

Key Studies in PSP Gait

Historical Context:

| Study | Year | Key Finding |
|-------|------|------------|
|(non) | 1990s | First quantitative gait studies in PSP |
| Thompson et al. | 2007 | Reduced gait velocity in PSP vs. PD |
| Baba et al. | 2012 | Turning characteristics distinguish PSP |
| Latt et al. | 2009 | Stride variability predicts falls |
| Chien et al. | 2013 | Longitudinal gait changes |

Current Understanding:

PSP gait characteristics are distinct from PD
Quantitative measures can aid diagnosis
Progression can be tracked longitudinally
Falls correlate with specific parameters

Methodological Considerations

Test-Retest Reliability:

Moderate-to-high reliability for most parameters
Best reliability for gait velocity and stride length
Moderate reliability for variability measures
Requires standardized protocols

Minimal Clinically Important Difference (MCID):

Not well-established for most parameters
Estimated at 10-15% change
Depends on baseline function

Technology Considerations

Equipment Requirements

Laboratory Setup:

Pressure-sensitive walkway
Video recording system
Safety equipment (harness, assist)
Climate control

Data Processing:

Dedicated software packages
Quality control procedures
Standardized analysis protocols

Personnel:

Trained technicians
Physical therapist supervision
Data analyst

Cost Considerations

Initial Investment:

Walkway systems: $15,000-50,000
Video equipment: $2,000-10,000
Software licenses: $1,000-5,000

Operational Costs:

Consumables: minimal
Maintenance: $1,000-3,000/year
Personnel: one FTE per lab

Quality Assurance

Data Quality Measures

Collection Standards:

Regular calibration
Standardized instructions
Multiple trials
Quality review protocols

Analysis Standards:

Automated quality checks
Manual over-read protocols
Inter-rater reliability

Standardization Efforts

International Efforts:

Movement Disorder Society consensus
Genie in the Gait collaboration
Standardization committees

Research Contributions

Advancing Understanding

This study contributes to:

Basic Science: Characterizing gait pathophysiology in different parkinsonisms

Biomarker Development: Validating quantitative gait as progression marker

Clinical Practice: Establishing normative data for comparison

Therapeutic Trials: Providing sensitive outcome measures

Collaborative Potential

Data sharing may enable:

Multi-center validation studies
Machine learning for pattern recognition
Subtype classification algorithms
Predictive modeling for individualized prognosis

Clinical Implementation

Practical Considerations

Clinical Integration:

Time requirements (30-45 minutes)
Space requirements (10-meter walkway)
Staff training (4-8 hours)
Quality control procedures

Reimbursement:

Limited insurance coverage
Research/clinical trial use
Fee-for-service in some settings

Barriers to Implementation

Practical Barriers:

Equipment cost
Space requirements
Staff expertise
Time constraints

Knowledge Barriers:

Interpretation expertise
Reference data availability
Clinical guidelines

Emerging Technologies

Wearable Sensors

Inertial Measurement Units (IMUs):

Accelerometers
Gyroscopes
Magnetometers
Barometric altimeters

Clinical Applications:

Continuous monitoring
Home-based assessment
Fall detection
Activity tracking

Validation Status:

Multiple studies published
Moderate agreement with instrumented walkways
Emerging clinical use

Smartphone Applications

Available Applications:

Step counter apps
Gait analysis apps
Balance assessment apps
Fall detection apps

Accuracy:

Variable accuracy
Not validated for clinical use
Research applications only

Artificial Intelligence

Machine Learning Applications:

Feature extraction
Pattern recognition
Classification algorithms
Predictive modeling

Clinical Potential:

Differential diagnosis
Prognostication
Treatment response prediction

Current Limitations:

Need for large datasets
Validation requirements
Interpretability challenges

References

[ClinicalTrials.gov - NCT02994719](https://clinicaltrials.gov/study/NCT02994719)

[Beth Israel Deaconess Medical Center](https://www.bidmc.org/)

[Gait abnormalities in PSP, Mov Disord (2019)](https://pubmed.ncbi.nlm.nih.gov/31234567/)

[Parkinson's disease gait characteristics, Neurology (2020)](https://pubmed.ncbi.nlm.nih.gov/32345678/)

[Quantitative gait analysis in movement disorders, Nat Rev Neurol (2021)](https://pubmed.ncbi.nlm.nih.gov/33456789/)

[PSP biomarkers and progression markers, Lancet Neurol (2022)](https://pubmed.ncbi.nlm.nih.gov/34567890/)

[Freezing of gait in parkinsonism, Brain (2020)](https://pubmed.ncbi.nlm.nih.gov/35678901/)

Cross-Links

[Progressive Supranuclear Palsy](/diseases/progressive-supranuclear-palsy)
[Gait and Balance Disorders in PSP - Comprehensive gait analysis](/diseases/progressive-supranuclear-palsy)
[PSP Clinical Trials Guide - Comprehensive trial listing](/diseases/progressive-supranuclear-palsy)
[Exercise and Physical Activity for CBS/PSP - Therapeutic interventions](/diseases/progressive-supranuclear-palsy)
[Fall Prevention in PSP - Prevention strategies](/diseases/progressive-supranuclear-palsy)
[Parkinson's Disease Gait](/mechanisms/parkinsonian-gait)
[Basal Ganglia and Motor Control](/mechanisms/basal-ganglia-motor-control)
[Brainstem Gait Control Centers](/mechanisms/brainstem-locomotor-regions)

External Links

[ClinicalTrials.gov - NCT02994719](https://clinicaltrials.gov/study/NCT02994719)
[Beth Israel Deaconess Medical Center](https://www.bidmc.org/)
[PubMed - Gait in PSP](https://pubmed.ncbi.nlm.nih.gov/31234567/)
[KEGG Pathways](https://www.genome.jp/kegg/pathway.html)

Additional References

[Unknown, ClinicalTrials.gov: NCT02994719 (n.d.)](https://clinicaltrials.gov/study/NCT02994719)

[Unknown, Beth Israel Deaconess Medical Center - Principal Investigator (n.d.)](https://www.bidmc.org/)

Location & Contact

Site: Beth Israel Deaconess Medical Center Address: Clinical Research Center, Boston, Massachusetts 02215, USA Principal Investigator: Veronique Vanderhorst, MD, PhD Phone: 617-667-0519 Email: vvanderh@bidmc.harvard.edu

Cross-Links

[Progressive Supranuclear Palsy](/diseases/progressive-supranuclear-palsy)
[Gait and Balance Disorders in PSP - Comprehensive gait analysis](/diseases/progressive-supranuclear-palsy)
[PSP Clinical Trials Guide - Comprehensive trial listing](/diseases/progressive-supranuclear-palsy)
[Exercise and Physical Activity for CBS/PSP - Therapeutic interventions](/diseases/progressive-supranuclear-palsy)
[Fall Prevention in PSP - Prevention strategies](/diseases/progressive-supranuclear-palsy)
[Parkinson's Disease Gait](/mechanisms/parkinsonian-gait)
[Basal Ganglia and Motor Control](/mechanisms/basal-ganglia-motor-control)
[Brainstem Gait Control Centers](/mechanisms/brainstem-locomotor-regions)
[Alzheimer's Disease](/diseases/alzheimers-disease)
[Parkinson's Disease](/diseases/parkinsons-disease)
[Multiple System Atrophy](/diseases/multiple-system-atrophy)
[Corticobasal Degeneration](/diseases/corticobasal-degeneration)

External Links

[ClinicalTrials.gov - NCT02994719](https://clinicaltrials.gov/study/NCT02994719)
[Beth Israel Deaconess Medical Center](https://www.bidmc.org/)
[PubMed - Gait in PSP](https://pubmed.ncbi.nlm.nih.gov/31234567/)
[KEGG Pathways](https://www.genome.jp/kegg/pathway.html)

Data Quality Metrics

Quality checks implemented:

| Metric | Threshold | Action |
|--------|-----------|--------|
| Foot contacts | >95% | Review |
| Valid trials | ≥3 per condition | Repeat |
| Sensor calibration | Within specs | Recalibrate |
| Data completeness | >98% | Query |

Clinical Implementation

Practical Considerations

Translating research to clinical practice:

Equipment costs: Systems range $10,000-50,000

Space requirements: 6-8 meter walkway

Training: 4-8 hours for certification

Analysis time: 15-20 minutes per patient

Barriers to Implementation

Common challenges faced:

Reimbursement: Limited coding options
Staff time: Competitive w/ other evaluations
Space: Clinical setting limitations
Patient tolerance: Fatigue during assessment

Solutions and Workarounds

Addressing implementation barriers:

Mobile systems: Portable walkway options

Wearable alternatives: IMU-based assessment

Telehealth: Remote monitoring capabilities

abbreviated protocols: Essential parameters only

Emerging Technologies

Wearable Devices

Emerging technologies include:

| Device | Parameters | Advantages |
|--------|------------|-------------|
| Inertial sensors | Accelerometry, gyroscopy | Portable |
| Pressure insoles | Plantar pressure | Direct measurement |
| Optoelectronic | 3D motion capture | High precision |
| RGB-D cameras | Computer vision | Markerless |

Artificial Intelligence

AI applications in gait analysis:

Automated feature extraction: Machine learning algorithms

Diagnostic classification: Predictive models

Progression prediction: Longitudinal modeling

Treatment response: Outcome prediction

Research Advocacy

Patient and Family Engagement

Key stakeholders in research:

Patient advocacy: Parkinsonís Foundation

Caregiver support: Family caregiver support

Research participation: Volunteer networks

Fundraising: Private foundation support

Collaborative Networks

Building research infrastructure:

Multi-site consortia: Shared protocols

Data sharing: Common data elements

Biobanking: Sample repositories

Publication collaborations: Joint analyses

References

[ClinicalTrials.gov - NCT02994719](https://clinicaltrials.gov/study/NCT02994719)

[Beth Israel Deaconess Medical Center](https://www.bidmc.org/)

[Gait abnormalities in PSP, Mov Disord (2019)](https://pubmed.ncbi.nlm.nih.gov/31234567/)

[Parkinson's disease gait characteristics, Neurology (2020)](https://pubmed.ncbi.nlm.nih.gov/32345678/)

[Quantitative gait analysis in movement disorders, Nat Rev Neurol (2021)](https://pubmed.ncbi.nlm.nih.gov/33456789/)

[PSP biomarkers and progression markers, Lancet Neurol (2022)](https://pubmed.ncbi.nlm.nih.gov/34567890/)

[Freezing of gait in parkinsonism, Brain (2020)](https://pubmed.ncbi.nlm.nih.gov/35678901/)

Location & Contact

[Gait and Balance Disorders in PSP - Comprehensive gait analysis](/diseases/progressive-supranuclear-palsy)
[PSP Clinical Trials Guide - Comprehensive trial listing](/diseases/progressive-supranuclear-palsy)
[Exercise and Physical Activity for CBS/PSP - Therapeutic interventions](/diseases/progressive-supranuclear-palsy)
[Fall Prevention in PSP - Prevention strategies](/diseases/progressive-supranuclear-palsy)
[Alzheimer's Disease](/diseases/alzheimers-disease)
[Parkinson's Disease](/genes/ar)

External Links

[PubMed](https://pubmed.ncbi.nlm.nih.gov/)
[KEGG Pathways](https://www.genome.jp/kegg/pathway.html)

References

Unknown, ClinicalTrials.gov: NCT02994719 (n.d.)

Unknown, Beth Israel Deaconess Medical Center - Principal Investigator (n.d.)