Kinematic and Neural Dynamics of Postural Instability in Parkinson's Disease

NCT06405334 | Recruiting

• 1 other identifier: E4810-R
• Study Type: observational
• Target: 100
• Locations: 1 country
• Sites: 1

Brief Summary

Balance problems and falls are among the most common complaints in Veterans with Parkinson's Disease (PD), but there are no effective treatments and the ability to measure balance and falls remains quite poor. This study uses wearable sensors to measure balance and uses deep brain stimulation electrodes to measure electric signals from the brain in Veterans with PD. The investigators hope to use this data to better understand the brain pathways underlying balance problems in PD so that new treatments to improve balance and reduce falls in Veterans with PD can be designed.

Conditions

Parkinson's Disease

Keywords

Parkinson Disease; subthalamic nucleus; gait; postural instability; deep learning

Outcome Measures

Primary Outcomes (4)

• Event Identification Receiver Operating Characteristic Curve

  All events are validated using the video camera recording. Using the CNN-LSTM algorithm, the investigators create a series of predicted events for the entire dataset of wearable sensor usage. For each event type, the investigators will then compare the predicted events based on this CNN-LSTM algorithm to the actual validated events. This will also allow us to assess the sensitivity, specificity, positive predictive value and negative predictive value for each event type. Finally, the investigators will create separate receiver operating characteristic (ROC) curves and calculate the AUC for each event type.

  4 years

• Silhouette Scores

  All kinematic variables are first standardized using z-score conversion and then transformed into a new set of uncorrelated principal components that retain the original data's variation. Following dimensionality reduction with PCA, the investigators utilize k-means clustering to identify potential subgroups. K-means clustering partitions the data into distinct, non-overlapping subgroups based on minimizing within-cluster variance, with the optimal number of clusters determined through the elbow method. While k-means is the most common method and has been effective thus far, small sample size datasets typically fare better using hierarchical clustering. This method, conversely, constructs a hierarchy of clusters by iteratively combining the most similar clusters. Silhouette scores are calculated to assess how well separated the clusters are from each other.

  4 years

• Associative STN alpha band power

  Associative and motor STN will be parcellated and the DBS lead reconstructed based on our prior work. The investigators will then use bipolar LFP recordings from the appropriate contact pairs to construct time frequency histograms and examine the event-related modulation of power in the response preparation, movement execution and post-movement execution phases of the postural response.

  4 years

• Postural step length response during associative STN vs. motor STN stimulation vs. no stimulation

  The investigators will assess changes in reactive postural response kinematics to associative vs. motor vs. no STN stimulation to test whether any stimulation or stimulation location can improve PI. Linear mixed-effects models are used to test for within-patient changes in pull test kinematic parameters between groups. These models are adjusted for pull intensity, and baseline step length values. Models use a Bonferroni p-value correction to account for multiple testing. The investigators have previously been able to determine within-patient kinematic differences using our variable pull test method in a sample size of 13 movement disorder patients. With \~15 pull test trials for each condition, the investigators can demonstrate within-patient kinematic differences of about 5 cm in initial step length and 100 ms in reaction time.

  4 years

Study Arms (1)

PD-Postural Instability

Veterans with postural instability

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Veterans with Parkinson's disease who experience postural instability and are treated at the Minneapolis VA Health Care System

You may qualify if:

• All Veterans with a clinical diagnosis of Parkinson's disease as made by their treating neurologist in Hoehn and Yahr stage 2-3 with the ability to give informed consent will be considered for possible participation in this study.
• Veterans cannot be past stage 3 as our measures depend on physical independence and fall risk prediction is less useful after stage 3.
• Capacity to consent will be assessed with the University of California, San Diego Brief Assessment of Capacity to Consent (UBACC).
• A score of less than 14.5 will be used as the cut-off to decide whether a Veteran is capable of consenting as the false positive rate is zero below this score with marginal increases in sensitivity above this score (89% sensitivity, 100% specificity).
• Aim 3

You may not qualify if:

• Veterans with dementia of sufficient severity to impair their ability to make healthcare related decisions for themselves will be excluded.
• Veterans with other forms of parkinsonism (PSP, CBGD, etc.) will be excluded.
• Veterans past H\&Y Stage 3 will be excluded.
• Veterans with symptomatic orthostatic hypotension (defined as sustained drop in systolic blood pressure by 20 mmHg or diastolic blood pressure by 10 mmHg within 3 minutes of standing after being supine for five minutes) will also be excluded as this is an entity the investigators are not characterizing and could confound/bias the dataset.
• Aim 3:

Sponsors & Collaborators

• VA Office of Research and Development: lead
• University of Minnesota: collaborator

Study Sites (1)

Minneapolis VA Health Care System, Minneapolis, MN

Minneapolis, Minnesota, 55417-2309, United States

RECRUITING

MeSH Terms

Conditions

Parkinson Disease

Condition Hierarchy (Ancestors)

Parkinsonian Disorders; Basal Ganglia Diseases; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Movement Disorders; Synucleinopathies; Neurodegenerative Diseases

Study Officials

• Robert A McGovern

  Minneapolis VA Health Care System, Minneapolis, MN

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Robert A McGovern

CONTACT

(612) 629-7904; Robert.McgovernIII@va.gov

Nicole Walker, MS

CONTACT

(612) 467-3229; nicole.walker6@va.gov

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: FED
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: May 3, 2024
• First Posted: May 8, 2024
• Study Start: November 1, 2024
• Primary Completion (Estimated): October 31, 2028
• Study Completion (Estimated): October 31, 2028
• Last Updated: November 3, 2025

Record last verified: 2025-10

Data Sharing

• IPD Sharing: Will share
• Shared Documents: SAP, CSR, ANALYTIC CODE
• Time Frame: At the time of manuscript publication or the end of the study, whichever comes first.
• Access Criteria: The dataset will be publicly available as above and the analysis code will be made available upon request. If an outside group wants to validate the event annotations, the video recordings will be made available via data use agreement between the two entities that specifically outlines the method of data sharing, which data will be shared, what it will be used for and the security methods by which the integrity of the data will be maintained.

Locations

US (1)