Neural and Kinematic Features of Freezing of Gait for Adaptive Neurostimulation

Stanford University12 enrolled

Overview

Continuous deep brain stimulation (cDBS) is an established therapy for the major motor signs in Parkinson's disease, however some patients find that it does not adequately treat their freezing of gait (FOG). Currently, cDBS is limited to "open-loop" stimulation,without real-time adjustment to the patient's state of activity, fluctuations and types of motor symptoms, medication dosages, or neural markers of the disease. The purpose of this study is to determine if an adaptive DBS system,responding to patient specific, clinically relevant neural or kinematic feedback related to FOG, is more effective than continuous DBS on the motor Unified Parkinson's Disease Rating Scale (UPDRS III) and gait measures of PD.

Study Type

INTERVENTIONAL

Allocation

Purpose

BASIC_SCIENCE

Masking

NONE

Enrollment

Conditions

Parkinson Disease

Interventions

Eligibility

Sex: ALLMin age: 18 YearsMax age: 80 Years

Medical Language ↔ Plain English

Inclusion Criteria: 1. A diagnosis of idiopathic Parkinson's disease, with bilateral symptoms at Hoehn and Yahr Stage greater than or equal to II. 2. Documented improvement in motor signs on versus off dopaminergic medication, with a change in the Unified Parkinson's Disease Rating Scale motor (UPDRS III) score of \>= 30% off to on medication. 3. The presence of complications of medication such as wearing off signs,fluctuating responses and/or dyskinesias, and/or medication refractory tremor,and/or impairment in the quality of life on or off medication due to these factors. 4. Subjects should be on stable doses of medications, which should remain unchanged until the DBS system is activated. After the DBS system is optimized(during which time the overall medication dose may be reduced to avoid discomfort and complications such as dyskinesias) the medication dose should remain unchanged, if possible, for the duration of the study. 5. Treatment with carbidopa/levodopa, and with a dopamine agonist at the maximal tolerated doses as determined by a movement disorders neurologist. 6. Ability and willingness to return for study visits, at the initial programming and after three, six and twelve months of DBS. 7. Age \> 18 8. Has a history of and/or displays freezing of gait Exclusion Criteria: 1. Subjects with significant cognitive impairment and/or dementia as determined bya standardized neuropsychological battery. 2. Subjects with clinically active depression, defined according to the Diagnostic and Statistical manual of Mental Disorders, Fourth Edition (DSM-IV) criteria and as scored on a validated depression assessment scale. 3. Subjects with very advanced Parkinson's disease, Hoehn and Yahr stage 5 on medication (non-ambulatory). 4. Age \> 80. 5. Subjects with an implanted electronic device such as a neurostimulator, cardiac pacemaker/defibrillator or medication pump. 6. Subjects, who are pregnant, are capable of becoming pregnant, or who are breast feeding. 7. Patients with cortical atrophy out of proportion to age or focal brain lesions that could indicate a non-idiopathic movement disorder as determined by MRI 8. Subjects having a major comorbidity increasing the risk of surgery (prior stroke,severe hypertension, severe diabetes, or need for chronic anti-coagulation other than aspirin). 9. Subjects having any prior intracranial surgery. 10. Subjects with a history of seizures. 11. Subjects, who are immunocompromised. 12. Subjects with an active infection. 13. Subjects, who require diathermy, electroconvulsive therapy (ECT), or transcranial magnetic stimulation (TMS) to treat a chronic condition. 14. Subjects, who have an inability to comply with study follow-up visits or study protocol. 15. Subjects, who are unable to understand or sign the informed consent.

Outcomes

Primary Outcomes

Incidence of Treatment-Emergent Adverse Events [Safety and Tolerability] Related to aDBS

Safety, tolerability and feasibility of aDBS

Time frame: 30 min - 2 hours

Secondary Outcomes

Aim 1: Alpha Power

Subthalamic nucleus (STN) local field potentials (LFP) recordings demonstrate oscillatory neuronal activity in both the alpha (8-12 Hz) and beta (13-30 Hz) bands in the resting state in PD. Spectrograms were generated using a short-time Fourier transform, with a 1 second Hanning window and a 0.5 second overlap, creating a frequency resolution of 1 Hz. Power spectral densities were calculated using the Welch method with the same window and overlap parameters. Power was summed in the beta and alpha bands. This power can be representative of the magnitude of oscillatory activity in this frequency band occurring in this brain region.

Time frame: 30 minutes

Aim 1: Beta Power

Time frame: 30 minutes

Aim 1: Alpha Sample Entropy

The predictability of the local field potentials (band-pass filtered between 8-12 Hz for alpha) was analyzed using Sample Entropy (SampEn), a nonlinear measure suitable for physiological time series. SampEn may be a more consistent measure and more suitable to shorter time series data than approximate entropy, partially due to the elimination of counting self matches. SampEn is calculated as the negative logarithm of the estimated conditional probability that if consecutive subseries of length m are similar according to some preset tolerance r, the consecutive subseries of length m+1 will be similar too. Here the length of the vector pairs, m, denotes the embedding dimension.

Time frame: 30 minutes

Aim 1: Beta Sample Entropy

The predictability of the local field potentials (band-pass filtered between 15-30 Hz for beta) was analyzed using Sample Entropy (SampEn), a nonlinear measure suitable for physiological time series. SampEn may be a more consistent measure and more suitable to shorter time series data than approximate entropy, partially due to the elimination of counting self matches. SampEn is calculated as the negative logarithm of the estimated conditional probability that if consecutive subseries of length m are similar according to some preset tolerance r, the consecutive subseries of length m+1 will be similar too. Here the length of the vector pairs, m, denotes the embedding dimension.

Time frame: 30 minutes

Aim 2: Asymmetry

Asymmetry during both forward walking and stepping in place was calculated using periods of walking or stepping when the subject was not freezing. According to previous studies, asymmetry is defined as: 100\*(absolute value of the natural log of the shorter average swing time over the longer average swing time) or mathematically: 100\*\| ln (SSWT/LSWT) \| where SSWT = shorter mean swing time LSWT = longer mean swing time

Time frame: 30 minutes

Aim 2: Arrhythmicity

Arrhythmicity during both forward walking and stepping in place was calculated using periods of walking or stepping when the subject was not freezing. According to previous studies, arrhythmicity is defined as the mean stride time coefficient of variation of both legs, and a greater stride time CV implies less rhythmic gait or stepping. Higher arrhythmicity corresponds to more arrhythmic, or more impaired, gait.

Time frame: 30 minutes

Aim 2: Stride Time

Kinematic Features associated with Freezing of Gait

Time frame: 30 minutes

Aim 2: Percent Time Freezing

Freezing of gait episodes during stepping in place were identified using a validated computerized algorithm, and during forward walking by a blinded rater. The percent time freezing was calculated by dividing the time spent freezing by the total time to complete the task then multiplying by 100 to get a percent. If no freezing was observed, then the percent time freezing reported was 0.0%.

Time frame: 30 minutes

Percent Time Freezing

Freezing of gait episodes during stepping in place were identified using a validated computerized algorithm. The percent time freezing was calculated by dividing the time spent freezing by the total time to complete the task then multiplying by 100 to get a percent. If no freezing was observed, then the percent time freezing reported was 0.0%. The percent time spent freezing was compared while the participant was doing the stepping in place task on continuous deep brain stimulation (cDBS) and while the participant was doing the stepping in place task on adaptive deep brain stimulation (aDBS).

Time frame: 30 minutes

Neural and Kinematic Features of Freezing of Gait for Adaptive Neurostimulation

Overview

Conditions

Interventions

Eligibility

Locations (1)

Outcomes

Primary Outcomes

Secondary Outcomes