Utilizing Neural Signatures and Virtual Reality to Advance DBS Programming
Conditions: Parkinson Disease, DBS, Deep Brain Stimulation, Freezing of Gait, Virtual Reality
Sponsor: The Cleveland Clinic

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ClinicalTrials.gov Final Outcomes Report 
  
NCT Number: 
05103384 
Project Title: 
Utilizing Neural Signatures and Virtual 
Reality to Advance DBS Programming 
Principal Investigaor Name: 
Jay L. Alberts, PhD 
Principal Investigator 
Organization and Address: 
Cleveland Clinic 
9500 Euclid Ave 
Cleveland, OH 44195 
Document Date: 
9/27/2023  
 
 

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Title: Utilizing Neural Signatures and Virtual Reality to Advance DBS Programming 
Primary Investigator: Jay L. Alberts, PhD 
Study Funder: Michael J. Fox Foundation for Parkinson’s Research 
Protocol Date: 9/27/2023 
 
PROJECT GOAL: Falls related to postural and gait impairments and freezing of gait (FOG) occur in 
nearly 80% of Parkinson’s disease (PD) patients and are the greatest motor-related contributor to health 
care costs and the primary reason for transition to dependent care settings among PD patients.1-3 Despite 
their prevalence in the daily lives of PD patients, identifying FOG episodes in a clinical4,5 or laboratory6,7 
environment is challenging. Consequently, the neural signature underlying FOG remains elusive.6,8 A 
necessary step in treating FOG is characterizing neural activity within the basal ganglia during FOG 
episodes. An approach to evaluate the neural signals associated with FOG includes recording the neural 
activity in the area of the subthalamic nucleus (STN) or globus pallidus internus (GPi) from implanted 
deep brain stimulation (DBS) leads.7,9-11 The proposed project combines the most advanced virtual reality 
(VR) technology and neural recording techniques to identify specific neural correlates of FOG while 
patients physically walk through a virtual environment, Virtual-Gait Task (V-GAIT), that simulates 
motor and cognitive\limbic triggers.  
 
Objective:  To identify the corresponding neural signatures of FOG associated with motor and 
cognitive\limbic triggers.  
Fifteen individuals with PD will complete the V-GAIT modules while synchronized kinematic 
and neural data from the DBS lead within the STN or GPi are recorded. The kinematic data will be 
utilized to identify the timing of FOG episodes in the neural data. The neural correlates of FOG in the ON 
and OFF medication states within each domain will be evaluated.  
 
METHODOLOGY AND APPROACH 
The V-GAIT platform utilizes a VR headset to deliver high fidelity realistic virtual environments 
resembling a home environment while the participant walks on an omnidirectional treadmill. Briefly, the 
VR headset provides a realistic display with high resolution and refresh rate, wide field of view, and color 
clarity currently available. The 360-degree moving platform allows the user to naturally walk and turn in 
any direction. The 3-dimensional linear and angular position of the head, waist, and both feet are tracked 
using motion sensors that are embedded in the headset, waist belt, and foot straps. To ensure safety, a 
supported harness is worn by the user. To monitor overall exertion and provide a proxy for stress, a heart 
rate monitor is integrated into the V-GAIT platform. 
 
V-GAIT Module: This module replicates a home, including a kitchen. The tasks will include, but not be 
limited to, walking in hallways will have digital doorways which reduce the width of the passageway and 
a virtual room where participants will appear to walk on an elevated platform to trigger anxiety-induced 
FOG. 
 
INCLUSION/EXCLUSION CRITERIA 
 
Participants: Fifteen individuals with idiopathic PD will be recruited for the study. Individuals who have 
previously undergone DBS surgery with the Medtronic Percept BrainSense DBS system will complete the 
protocol while neural data from the DBS electrodes are streamed. 
 
Inclusion Criteria: 
o Clinical diagnosis of idiopathic PD 
o Previous implantation of Percept DBS system as standard of care for their PD treatment 

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o Self-reported response of one or greater on question #3 of the FOG-Q 
o Ability to ambulate independently for a minimum of 10 minutes 
o Ability to provide informed consent 
 
Exclusion Criteria: 
o Neurological disease other than PD 
o Musculoskeletal impairment that affects one’s ability to ambulate for 15 minutes continuously 
o Presence of active and untreated psychiatric symptoms meeting Diagnostic and Statistical Manual 
of Mental Disorders-4th Edition (DSM-IV) criteria for Axis-I disorder. Depression and anxiety 
are very common in patients with Parkinson’s disease and are often mitigated as part of routine 
care. Depression and anxiety will not preclude study participation 
o Cognitive impairment meeting Diagnostic and Statistical Manual of Mental Disorders-4th Edition 
(DSM-IV) criteria for dementia on formal neuropsychological evaluation 
o Current alcohol or substance abuse 
o Hearing or visual impairment precluding VR use 
o Lack of fluency in English which may invalidate certain tests 
 
 
RESEARCH DESIGN AND METHODS 
Individuals with the Medtronic Percept DBS system will be medically stable status post DBS surgery 
prior to enrollment.   
 
Screening: Potential participants will be identified and screened by a member of the study team. They 
will undergo an in-person informed consent process. They will also complete a familiarization session 
with the VR headset and treadmill. The Percept system allows for continuous streaming of LFP data from 
the implanted device.  
V-GAIT Assessments: Participants will perform two assessment sessions. During the sessions, the 
participants will complete the V-GAIT as outlined in Table 1. The sessions can be performed 
consecutively on the same day or on separate days depending on patient tolerance and preference.  
Table 1: Assessment States 
 
DBS State 
PD Medication State 
Session 1 
Off 
Off 
Session 2 
Off 
On 
 
DATA COLLECTION PROCEDURES 
Neural Recording Procedures:  The proposed study design will enable synchronized recordings to be 
made in the form of LFP from the six or eight channels of implanted DBS lead(s), as well as IMU sensors 
from the V-GAIT platform to quantify gait-related behaviors using a commercial EEG recording 
platform. The physiological and sensor data will be synchronized to motor task and gait-related activities 
and events associated with participant performance on the V-GAIT paradigm through additional analog 
and digital ports using a low voltage electrical current (1.5 mA) through surface electrodes placed on the 
participant’s neck. 
 
Behavioral Tasks: The Unified Parkinson’s Disease Rating Scale (UPDRS) will be conducted by a rater 
blinded to medication state.  
 

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DATA ANALYSIS 
Biomechanical Data Analysis: All data will be recorded and analyzed off-line using custom-scripts in 
Matlab using the Chronux toolbox to examine changes in oscillatory neural activity time-locked to FOG 
episodes identified with the kinematic data from the body worn motion sensors in the motion capture 
area. The 3D position data of each foot will be utilized to determine steps and other biomechanical 
stepping variables FOG episodes will be identified utilizing the data from the body-worn motion sensors.  
Neural Data Analysis: Neural data will be detrended and passed through a moving window line noise 
subtraction algorithm to remove drifting baseline and continuous noise artifacts, respectively. From the 
Percept device, 6 electrode pair combinations, 3 combinations per DBS lead, will be recorded directly 
with the Percept communicator. Windows containing movement artifacts will be visually identified by 
large fluctuations in the time series and high amplitude broadband activity in the spectrogram and 
removed from further analysis. Triggered spectrograms will be calculated for each trial using the multi-
taper method with a 100 ms, 50 ms overlap moving window, 2.5 Hz frequency resolution, and 1 taper.  
Local Field Potential (LFP) Outcomes: The relationship of synchronization and desynchronization 
changes in oscillatory activity within the delta, theta, alpha, beta and/or gamma bands as well as the 
power of high-frequency oscillations (200+ Hz) will be calculated in relation to all events identified with 
the kinematic data, i.e. normal walking and FOG episodes. Power spectral densities will be used to 
determine the power and confidence bands of oscillatory activity across frequencies during these events.  
Statistical Analysis: Neural data outcomes, average power within alpha, beta, and/or gamma frequency 
bands, will be quantified using descriptive statistics during FOG episodes and during periods of 
functional walking while performing the V-Gait modules. Within and across participant analyses will 
determine the degree of consistency and similarity of the neural signal during FOG episodes between 
each medication state (ON and OFF). 
 
Confidentiality: CCF study investigators will have sole access to the study data. To protect 
confidentiality, participants’ data will be identified only by coded subject number and stored in a secure 
location in a de-identified manner. A password-protected, electronic record linking subject numbers with 
identifying information will be maintained in a password-protected folder on a secure server and only 
CCF-based study investigators will have access to this file. Data analysis will be conducted by the study 
investigators in consultation with biostatistics, where appropriate. Dissemination of the results will 
largely involve aggregate data, although individual data points may be used where illustrative. All 
dissemination of the study findings will maintain confidentiality and include only de-identified data, 
except in the situation where express written permission has been obtained from the participant in 
advance. 
 
Adverse Events and Safety: A Data Safety Monitoring Board (DSMB) will oversee this Phase I study. 
Non-conflicted members in the following areas: neurology, neurosurgery, statistics and bio-ethics will be 
recruited. Additionally, the Principal and Co-Investigators, along with the rest of the research team, will 
continuously monitor subject safety and data integrity. Adverse events and Unanticipated Problems will 
be reviewed by the Principle and Co-Investigators. If an Adverse Event occurs, it will be recorded on the 
Adverse Event Summary Sheet, and this will be submitted along with the Adverse Event Report in 
accordance with the stated time limitations. No clinical electrophysiological or imaging report will be 
generated as the experiments performed do not constitute diagnostic studies. However, if an unexpected 
finding is observed during the electrophysiological analysis, the appropriate clinical consults will be 
ordered. 
 
 
 
                                                    
 

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