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The purpose of this study is to assess how alternating-frequency Deep Brain Stimulation (DBS) works to improve postural instability and gait, while also treating other motor symptoms of Parkinson Disease (PD).
Postural instability, gait impairment, and falls are among the greatest unmet needs in Parkinson disease (PD). A single fall can be catastrophic, and impairments that limit mobility lead to social isolation or depression, and adversely affect bone and cardiovascular health. Unfortunately, postural instability and gait disorders are refractory to current pharmacological and surgical treatments, including deep brain stimulation (DBS). This project will directly address this pressing need. We will recruit participants to perform a gait task, using a new, alternating DBS frequency paradigm, while body movements and neural signals are recorded. The findings will lead to improved therapies to address these symptoms in the future.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Alternating-Frequency DBS | Experimental | In this single-arm study, all participants will receive all interventions in a crossover fashion. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| High-Frequency-Only Stimulation | Device | Control condition, constant high-frequency DBS stimulation (130Hz) |
|
| Measure | Description | Time Frame |
|---|---|---|
| Stride Time Coefficient of Variation | Marker of gait instability, derived from kinematic recordings from body-worn wireless sensors. | During the intervention |
| Percentage of Time with Tremor Present | Marker of tremor severity, derived from kinematic recordings from body-worn wireless sensors. | During the intervention |
| Tremor Amplitude | Marker of tremor severity, derived from kinematic recordings from body-worn wireless sensors. | During the intervention |
| Measure | Description | Time Frame |
|---|---|---|
| Total Freezing Time | Marker of gait instability, derived from kinematic recordings from body-worn wireless sensors. | During the intervention |
| Freezing Index | Marker of gait instability, derived from kinematic recordings from body-worn wireless sensors. |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| James Liao, MD PhD | The Cleveland Clinic | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Cleveland Clinic Foundation | Cleveland | Ohio | 44195 | United States |
At time of publication, a point of contact individual on the study team will be identified. Third parties will be able to request access to de-identified data used to support the publication findings by application to the Cleveland Clinic IRB. A data use agreement will be put in place between the CCF Cleveland Clinic and this third party for approved use of the data.
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On a single day, participants will switch between six DBS frequency conditions. Gait and body kinematics will be monitored during these conditions. The order that participants experience the six conditions will be randomized, and participants will be blinded to the condition. In addition, the assessments will be performed OFF and then repeated ON medication.
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There is only one arm in the study. Participants will be masked to which device intervention is active, but they will not be masked to the medication state.
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| Low-Frequency-Only Stimulation | Device | Experimental condition, constant low-frequency DBS stimulation (60 Hz) |
|
| Alternating, 50 sec High-Frequency, 10 sec Low-Frequency Stimulation | Device | Experimental condition where stimulation frequency is changed from high (130Hz) to low (60Hz) frequency. The time interval for each frequency is 50 seconds for high, and 10 seconds for low, respectively. |
|
| Alternating, 50 sec High-Frequency, 50 sec Low-Frequency Stimulation | Device | Experimental condition where stimulation frequency is changed from high (130Hz) to low (60Hz) frequency. The time interval for each frequency is 50 seconds for high, and 50 seconds for low, respectively. |
|
| Alternating, 10 sec High-Frequency, 50 sec Low-Frequency Stimulation | Device | Experimental condition where stimulation frequency is changed from high (130Hz) to low (60Hz) frequency. The time interval for each frequency is 10 seconds for high, and 50 seconds for low, respectively. |
|
| Alternating, 10 sec High-Frequency, 10 sec Low-Frequency Stimulation | Device | Experimental condition where stimulation frequency is changed from high (130Hz) to low (60Hz) frequency. The time interval for each frequency is 10 seconds for high, and 10 seconds for low, respectively. |
|
| OFF Dopaminergic Medication | Drug | All six device interventions will be performed in medication OFF state |
|
| ON Dopaminergic Medication | Drug | All six device interventions will be performed in medication ON state |
|
| During the intervention |
| Gait Velocity | Marker of bradykinesia, derived from kinematic recordings from body-worn wireless sensors. | During the intervention |
| Step Cadence | Marker of bradykinesia, derived from kinematic recordings from body-worn wireless sensors. | During the intervention |
| LFP and EEG power spectrum correlation with behavior and kinematics | Neural recordings (LFP = Local Field Potential and EEG = Electroencephalogram) from the DBS electrode and from EEG electrodes will be analyzed in the frequency domain. Assessed frequency bands will include delta, theta, alpha, beta, and gamma activity. These will be correlated with behavior and kinematic recordings to determine the neural correlates of gait instability and other parkinsonian symptoms. | During the intervention |
| LFP and EEG connectivity correlation with behavior and kinematics | Neural recordings (LFP = Local Field Potential and EEG = Electroencephalogram) consist of multiple channels of simultaneously measured electrical activity. Connectivity is a measure of correlations between each pair of recorded and postprocessed channels, at each frequency band, over time. A machine learning algorithm will be trained to correlate the connectivity to behavior and kinematic recordings, to determine the neural correlates of gait instability and other parkinsonian symptoms. | During the intervention |
| ID | Term |
|---|---|
| D010300 | Parkinson Disease |
| D020233 | Gait Disorders, Neurologic |
| D018450 | Disease Progression |
| ID | Term |
|---|---|
| D020734 | Parkinsonian Disorders |
| D001480 | Basal Ganglia Diseases |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
| D009069 | Movement Disorders |
| D000080874 | Synucleinopathies |
| D019636 | Neurodegenerative Diseases |
| D009461 | Neurologic Manifestations |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D020969 | Disease Attributes |
| D010335 | Pathologic Processes |
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