NCT06405334 · VA Office of Research and Development
Kinematic and Neural Dynamics of Postural Instability in Parkinson's Disease
What this study is about
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.
View original scientific description
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.
Primary outcome measures
Event Identification Receiver Operating Characteristic Curve
Time frame: 4 years
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.
Silhouette Scores
Time frame: 4 years
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.
Associative STN alpha band power
Time frame: 4 years
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.
Postural step length response during associative STN vs. motor STN stimulation vs. no stimulation
Time frame: 4 years
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.
Who can participate
This study lists these criteria on ClinicalTrials.gov. A study coordinator reviews eligibility during screening — this page does not determine whether you qualify.
Inclusion criteria
- Aims 1 and 2 Inclusion criteria:
- 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 Inclusion criteria:
- In addition to the inclusion criteria for Aims 1 and 2, Veterans with an implanted STN DBS lead with a Percept device in place.
Exclusion criteria
- Aims 1 and 2 Exclusion criteria:
- 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: Exclusion criteria:
- In addition to the exclusion criteria for Aims 1 and 2, Veterans with DBS leads implanted in other locations will be excluded.
Where
- Minneapolis, Minnesota
Collaborators
University of Minnesota
Related conditions & keywords
Frequently asked questions
What is a clinical trial?
A clinical trial is a research study that tests new medical treatments, drugs, devices, or procedures to determine their safety and effectiveness. Trials are carefully designed and monitored to protect participants while advancing medical knowledge.
Is it safe to participate?
Clinical trials follow strict safety guidelines and ethical standards. Trials must be reviewed and approved, and participants are closely monitored by medical professionals throughout the study. You can withdraw at any time if you choose.
Will I be compensated?
Many clinical trials offer compensation for your time, travel expenses, and inconvenience. The specific compensation varies by study and will be discussed during the screening process. All study-related medical care is typically provided at no cost to participants.
Will I receive a placebo instead of treatment?
When effective treatment exists, participants typically receive either the standard treatment plus the study intervention, or the standard treatment plus placebo. You would not be denied effective care. Placebos are primarily used when no proven treatment is available, or in addition to standard care. Your trial consent form will clearly explain what treatments you may receive.
Can I leave a trial if I change my mind?
Absolutely. Participation in clinical trials is completely voluntary. You have the right to withdraw from the study at any time, for any reason, without penalty or loss of benefits to which you are otherwise entitled.
How long does a clinical trial last?
Trial duration varies widely depending on the study design and purpose. Some trials last just a few weeks, while others may continue for months or years. The study coordinator will provide specific timeline information during your screening call.
Data: ClinicalTrials.gov · synced Nov 3, 2025 · Source of record for eligibility and locations