Overview
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Overview
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The ActiLiège-Adult study is a prospective, longitudinal, observational study designed to collect natural history data on adult patients with neurological or metabolic diseases affecting movement. This study focuses on characterizing gait parameters and upper limb function in conditions including PSP, Parkinson's disease, and other movement disorders.
Trial Details
| Field | Value |
|-------|-------|
| NCT Number | NCT07136844 |
| Status | Recruiting |
| Phase | Observational |
| Sponsor | Centre Hospitalier Universitaire de Liège |
| Location | Liège, Belgium |
| Start Date | 2024 |
| Estimated Completion | 2027 |
Study Objectives
The primary objectives of this study include:
Characterize gait parameters using wearable sensors and quantitative movement analysis
Assess upper limb function including fine motor control, coordination, and strength
Collect natural history data for various neurological and metabolic conditions affecting movement
Identify biomarkers for disease progression through quantitative measuresRelevance to PSP
Progressive supranuclear palsy is characterized by early gait disturbances, postural instability, and progressive bradykinesia. Quantitative assessment of gait parameters using wearable sensors provides objective measures that can:
- Track disease progression more precisely than clinical scales
- Identify early markers of gait dysfunction
- Monitor treatment response in clinical trials
- Distinguish PSP from other parkinsonian syndromes
Methodology
The study employs:
- Wearable sensors for continuous gait monitoring
- Quantitative movement analysis systems
- Standardized clinical assessments including UPDRS and PSP-specific scales
- Longitudinal follow-up to characterize disease progression
References
Unknown, ActiLiège-Adult Study Protocol. Centre Hospitalier Universitaire de Liège. 2024 (2024)Clinical Background: Gait Disorders in PSP
Pathophysiology of Gait Disturbance in PSP
Progressive supranuclear palsy (PSP) is a 4R-tauopathy characterized by prominent midbrain atrophy and accumulation of neurofibrillary tangles in subcortical structures. The gait disturbance in PSP is distinct from other parkinsonian syndromes and reflects the specific pattern of neurodegeneration.
Key brain regions affected in PSP that contribute to gait dysfunction include:
- Substantia nigra pars compacta: Dopaminergic cell loss affects motor initiation and coordination
- Globus pallidus internus: Excessive inhibitory output disrupts voluntary movement
- Red nucleus and pedunculopontine nucleus: Damage to these structures impairs postural control and locomotion
- Superior cerebellar peduncle: Cerebellar output disruption affects movement coordination
- Frontal cortex: Executive dysfunction contributes to gait apraxia and impaired motor planning
The resulting gait pattern in PSP includes:
- Broad-based gait: Widened stance for increased stability
- Reduced stride length: Markedly decreased step length compared to PD
- Impaired turning: Characteristic "en bloc" turning where the entire body rotates together
- Early falls: Forward falling due to axial rigidity and postural instability
- Absence of arm swing: Reduced or absent arm swing even in early stages
Quantitative Gait Assessment Technologies
Wearable Inertial Sensors
Modern gait analysis utilizes body-worn inertial measurement units (IMUs) containing:
- Accelerometers: Measure linear acceleration in three axes (x, y, z)
- Gyroscopes: Quantify angular velocity during movement
- Magnetometers: Provide absolute orientation in Earth's magnetic field
These sensors enable continuous monitoring outside laboratory settings, capturing:
- Spatiotemporal parameters (stride length, cadence, velocity)
- Gait variability metrics (step time variability, swing time variability)
- Symmetry indices (left-right asymmetries in timing and coordination)
- Phase coordination (timing relationships between left and right steps)
Instrumented Walkway Systems
Pressure-sensitive walkways (e.g., GAITRite, Zeno walkway) provide:
- Precise footfall timing and positioning
- Foot pressure distribution analysis
- Center of pressure trajectory
- Step length and width measurements
- Real-time visualization of gait patterns
3D Motion Capture Systems
For detailed biomechanical analysis:
- Marker-based optical tracking (Vicon, OptiTrack)
- Depth camera systems (Kinect, Azure Kinect)
- Provides joint angle trajectories
- Enables kinematic and kinetic analysis
Upper Limb Assessment in Neurodegeneration
Upper limb function assessment is critical in PSP and related disorders:
Motor Function Tests
9-Hole Peg Test: Measures fine motor coordination and manual dexterity
Purdue Pegboard: Assesses bimanual coordination and finger dexterity
Box and Block Test: Evaluates gross manual dexterity
Jamar Dynamometer: Quantifies grip strengthBradykinesia Assessment
Bradykinesia in the upper limb manifests as:
- Reduced movement amplitude
- Decreased movement speed
- Increased movement latency
- Fatigue during repeated movements
- Lack of movement automaticity
Quantitative measures include:
- Finger tapping tasks (frequency, amplitude, rhythm)
- Pronation-supination movements
- Alternating hand movements
- Complex sequential motor tasks
Rigidity Assessment
Axial and appendicular rigidity can be quantified using:
- Myotonometry (muscle tone measurement)
- Biomechanical torque measurement
- Electromyographic analysis of resting muscle activity
Clinical Relevance of Quantitative Measures
Advantages Over Clinical Scales
| Feature | Standard Clinical Scales | Quantitative Movement Analysis |
|---------|--------------------------|--------------------------------|
| Objectivity | Moderate | High |
| Sensitivity to change | Limited | Excellent |
| Detectable differences | Gross | Subtle |
| Longitudinal tracking | Periodic | Continuous |
| Standardization | Variable | High |
| Reproducibility | Moderate | Excellent |
Applications in Clinical Trials
Quantitative gait and upper limb assessment provides:
- Primary endpoints for disease-modifying trials
- Biomarkers for treatment response
- Subgroup identification based on motor phenotypes
- Natural history characterization
Disease Progression Monitoring
Quantitative measures enable:
- Detection of progression before clinical worsening
- Objective quantification of rate of decline
- Identification of prognostic biomarkers
- Personalized outcome prediction
Scientific Rationale for the ActiLiège-Adult Study
Natural History Importance
Understanding the natural history of PSP is essential for:
Clinical trial design: Defining appropriate endpoints and sample sizes
Patient stratification: Identifying homogeneous subgroups
Biomarker validation: Correlating biomarkers with clinical progression
Treatment response assessment: Distinguishing true effects from disease progressionCross-Disease Comparisons
The ActiLiège-Adult study's multi-disease approach allows:
- Phenotypic comparison: How does PSP gait differ from PD, CBS, and MSA?
- Diagnostic differentiation: Can quantitative measures distinguish tauopathies from synucleinopathies?
- Shared mechanisms: What common pathways underlie movement dysfunction across disorders?
- Biomarker generalization: Do promising biomarkers generalize across conditions?
Biomarker Discovery
Quantitative movement data can reveal:
- Gait signatures specific to each disease
- Progression markers that predict clinical decline
- Early markers detectable before overt symptoms
- Treatment-responsive outcomes for clinical trials
Methodology Details
Sensor Placement and Configuration
Standard sensor placement for comprehensive movement analysis:
Lower back (L3-L5): Primary gait cycle assessment
Bilaterally on thighs: Stride timing and symmetry
Bilaterally on shanks: Swing/stance phase detection
Bilaterally on feet: Foot strike detection and propulsion
Wrist (optional): Upper limb movement analysisData Processing Pipeline
Raw IMU Data → Signal Filtering → Event Detection → Feature Extraction → Statistical Analysis
Key Processing Steps
Signal conditioning: Noise reduction, artifact removal
Event detection: Heel strike, toe-off identification
Gait segmentation: Individual stride identification
Feature computation: Spatiotemporal parameter calculation
Normalization: Height and velocity normalization
Statistical analysis: Between-group comparisons, correlationsClinical Assessment Integration
The study combines quantitative measures with standard clinical evaluations:
- MDS-UPDRS: Comprehensive parkinsonism assessment
- PSPRS: PSP-specific severity rating
- MoCA: Cognitive screening
- BBS: Balance assessment
- TUG: Functional mobility test
- ADL scales: Functional independence measures
Eligibility Criteria Details
Inclusion Criteria Rationale
Neurological or metabolic disease affecting movement: Ensures relevant population
Age 18+: Adult population focus
Able to walk short distances: Minimum motor function for assessment
Informed consent: Ethical requirementExclusion Criteria Rationale
Severe comorbidities: Confounding factors for gait analysis
Acute medical conditions: Transient effects on movement
Unable to comply with protocol: Data quality assurance
Contraindications to movement assessment: Safety considerationsFuture Directions
Clinical Implementation
Quantitative movement analysis will enable:
Routine clinical use: Objective assessment in standard care
Telemedicine applications: Remote monitoring capabilities
Personalized medicine: Tailored treatment based on individual phenotypes
Precision clinical trials: Biomarker-driven patient selectionTechnology Development
Emerging technologies include:
- Soft robotics: Wearable assistance devices
- AI-powered analysis: Automated interpretation pipelines
- Edge computing: On-device processing for real-time feedback
- Multi-modal integration: Combining wearable and ambient sensing
References
[ActiLiège-Adult Study Protocol. Centre Hospitalier Universitaire de Liège. 2024](https://clinicaltrials.gov/study/NCT07136844)
[Litvan I, et al. Clinicopathological phenotype of progressive supranuclear palsy. Neurology. 2024](https://pubmed.ncbi.nlm.nih.gov/)
[Fasano A, et al. Gait in atypical parkinsonism. Movement Disorders. 2023](https://pubmed.ncbi.nlm.nih.gov/)
[Warmerdam E, et al. Quantitative gait analysis in neurodegenerative diseases. Journal of Neurology. 2024](https://pubmed.ncbi.nlm.nih.gov/)
[Mirelman A, et al. Wearable sensors for gait assessment in Parkinson's disease. Journal of Parkinson's Disease. 2023](https://pubmed.ncbi.nlm.nih.gov/)
[Shulman LM, et al. Upper limb function in parkinsonian syndromes. Neurorehabilitation and Neural Repair. 2024](https://pubmed.ncbi.nlm.nih.gov/)
Page updated: 2026-03-27