Accidental Fall, Deep Brain Stimulation, Disease Progression, Gait Disorders, Neurologic, Parkinson Disease, Subthalamic Nucleus
Conditions
Keywords
Postural Instability, Gait Impairment, Freezing of Gait, DBS, Frequency, Low, Alternating, Variable, High
Brief summary
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).
Detailed description
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.
Interventions
DEVICEHigh-Frequency-Only Stimulation
Control condition, constant high-frequency DBS stimulation (130Hz)
DEVICELow-Frequency-Only Stimulation
Experimental condition, constant low-frequency DBS stimulation (60 Hz)
DEVICEAlternating, 50 sec High-Frequency, 10 sec Low-Frequency Stimulation
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.
DEVICEAlternating, 50 sec High-Frequency, 50 sec Low-Frequency Stimulation
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.
DEVICEAlternating, 10 sec High-Frequency, 50 sec Low-Frequency Stimulation
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.
DEVICEAlternating, 10 sec High-Frequency, 10 sec Low-Frequency Stimulation
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.
DRUGOFF Dopaminergic Medication
All six device interventions will be performed in medication OFF state
DRUGON Dopaminergic Medication
All six device interventions will be performed in medication ON state
Sponsors
James Liao
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
TREATMENT
Masking
NONE
Masking description
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.
Intervention model description
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.
Eligibility
Sex/Gender
ALL
Age
21 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Bilateral STN DBS for PD * Medtronic Percept PC implanted DBS battery/pulse generator/recording system * Presence of balance and/or walking impairment and/or freezing of gait * Can walk without assistance, OFF meds, based on yes/no verbal response
Exclusion criteria
* Severity of gait impairment should not require dependency to walker or cane * Cannot tolerate monopolar stimulation at either of the two middle electrode contacts (prerequisite for the recording mode of the DBS) at high frequency (130 Hz) or low frequency (60 Hz). * Concomitant conditions that may affect significantly the evaluation of balance or gait, including orthopedic, rheumatologic or other neurological diseases * Contraindication to physical therapy * Age \< 21 * Diagnosis of dementia * Not agreeable to having video taken of entire research visit
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Stride Time Coefficient of Variation | During the intervention | Marker of gait instability, derived from kinematic recordings from body-worn wireless sensors. |
| Percentage of Time with Tremor Present | During the intervention | Marker of tremor severity, derived from kinematic recordings from body-worn wireless sensors. |
| Tremor Amplitude | During the intervention | Marker of tremor severity, derived from kinematic recordings from body-worn wireless sensors. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Total Freezing Time | During the intervention | Marker of gait instability, derived from kinematic recordings from body-worn wireless sensors. |
| Freezing Index | During the intervention | Marker of gait instability, derived from kinematic recordings from body-worn wireless sensors. |
| Gait Velocity | During the intervention | Marker of bradykinesia, derived from kinematic recordings from body-worn wireless sensors. |
| Step Cadence | During the intervention | Marker of bradykinesia, derived from kinematic recordings from body-worn wireless sensors. |
| LFP and EEG power spectrum correlation with behavior and kinematics | During the intervention | 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. |
| LFP and EEG connectivity correlation with behavior and kinematics | During the intervention | 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. |
Countries
United States
Contacts
PRINCIPAL_INVESTIGATORJames Liao, MD PhD
The Cleveland Clinic
Outcome results
None listed