Essential Tremor (ET) is a prevalent movement disorder, affecting approximately 4% of individuals over the age of 40. Deep Brain Stimulation (DBS) has demonstrated efficacy in controlling various tremor manifestations in ET, yet there remains considerable uncertainty regarding optimal stimulation parameters - particularly frequency and amplitude - to achieve maximal tremor control without adversely affecting speech. Voice tremor is a significant symptom in ET and can severely impact communication and quality of life. Although DBS can effectively suppress limb tremor, its specific effects on vocal tremor are less understood. This study will investigate how varying DBS frequency and amplitude (standardized via Total Electrical Energy Delivered, TEED) influence the severity and acoustic characteristics of voice tremor in ET patients. The study will be primarily conducted at UCM with collaborative support from neurology departments throughout the greater Chicago area. We will employ a randomized crossover design enrolling 15 subjects with ET and existing DBS implants, with a study duration spanning 15 months.

Aim 1: Determine the impact of varying DBS frequencies on voice tremor parameters. Rationale: While limb tremor modulation has been linked to specific frequency settings (e.g., 130 Hz vs. 190 Hz), corresponding data for voice tremor remain sparse. Understanding how frequency alters vocal tremor can guide more tailored DBS programming for speech. Approach: Enroll ET patients with existing DBS implants who exhibit voice tremor. Evaluate stimulation at 130 Hz, 160 Hz, and 190 Hz, normalizing for amplitude via TEED calculations. Collect sustained vowels, short phrases, and spontaneous speech under each frequency condition and perform Fourier-based analysis to calculate tremor frequency/amplitude in the 4-12 Hz range. Expected Outcomes: Identification of specific frequency ranges that optimally reduce voice tremor and clarification of how frequency settings modulate vocal tremor severity.

Aim 2: Examine how incremental changes in Total Electrical Energy Delivered (TEED) affect voice tremor characteristics. Rationale: TEED incorporates multiple factors - voltage, pulse width, frequency, and impedance - but has not been systematically explored in relation to voice tremor. Isolating the effect of increased total energy independent of frequency shifts may reveal new strategies to optimize tremor suppression. Approach: Starting from 130 Hz as the baseline, increment TEED by 2/3 to match the energies delivered at 160 Hz and 190 Hz. Collect and process speech under these incremented TEED levels. Assess differences in tremor frequency/amplitude across incremental TEED steps to distinguish total-energy effects from frequency-specific effects. Expected Outcomes: Demonstration that total energy changes alone can significantly modify voice tremor and potential identification of lower vs. higher TEED settings that yield similar voice tremor suppression.

Aim 3: Identify a sub-region or hotspot within the VIM nucleus associated with optimal voice improvement through retrospective analysis. Rationale: Heterogeneity in VIM stimulation suggests sub-territories of the VIM may differentially influence voice outcomes. Locating an anatomical hotspot for voice tremor control can improve surgical targeting and programming. Approach: Gather post-operative imaging and documented voice evaluations from ET patients with VIM DBS. Use MR/CT co-registration and finite element modeling to estimate Volume of Tissue Activated (VTA) for each patient's settings. Compare VTA location/extent with voice tremor outcomes to identify sub-regions predictive of better speech results. Expected Outcomes: Identification of a consistent VIM sub-region correlated with superior voice outcomes and informed strategies for refined surgical targeting and parameter selection in future DBS patients.

Study Design: Randomized crossover design enrolling 15 subjects with ET and existing DBS implants. Sample size provides 82% power to detect clinically meaningful differences in tremor frequency (alpha = 0.05, effect size 0.8). Study duration: 15 months.

Participant Selection: Inclusion criteria: (1) Confirmed ET diagnosis with DBS implanted for tremor management, (2) Stable clinical condition allowing temporary DBS parameter adjustments, (3) Presence of audible voice tremor, (4) Ability to provide informed consent (MoCA score >= 18). Exclusion criteria: (1) Cognitive impairment precluding informed consent, (2) Severe speech impairment from other etiologies that would confound voice tremor assessments, (3) Contraindications to modifying DBS.

Recruitment: Through Loyola Medical Center neurology department and collaborating neurologists in Chicago area. Flyers posted in neurology clinics. Written informed consent obtained in person or via secure virtual platform.

Intervention Procedures: Each participant completes testing under six conditions: (1) Baseline clinical settings, (2) 130 Hz matched TEED, (3) 160 Hz matched TEED, (4) 190 Hz matched TEED, (5) 130 Hz TEED + 2/3, (6) 160 Hz TEED + 2/3. Computer-generated randomization to avoid order bias. Minimum 5-10 minute washout between stimulation conditions. TEED standardization: TEED = Voltage^2 x Frequency x PulseWidth / Impedance. A trained clinician supervises parameter adjustments and monitors for adverse events.

Voice Recording and Analysis: Tasks include sustained vowel (3-5 seconds), standard test phrases, and 30-second spontaneous speech sample. In-person recordings in sound-treated room (<40 dB ambient noise, high-quality mic 44.1 kHz, 16-bit). Remote recordings in quiet room (<50 dB, noise-canceling headset, stable internet >= 5 Mbps). Acoustic analysis includes Fourier analysis focusing on 4-12 Hz band for tremor frequency/amplitude, quantifying amplitude modulation depth, jitter, and shimmer. Outcome variables: voice tremor frequency (Hz), tremor amplitude (dB), patient self-rated voice severity using Voice Handicap Index (VHI) and Quality of Life in ET Questionnaire (QUEST).

Imaging and VTA Analysis (retrospective): High-quality neuroimaging from existing patient data. Pre-operative MRI with T1-weighted imaging (1mm isotropic resolution) and T2-weighted sequences. Post-operative CT within 24-48 hours of implantation. CT-MRI co-registration using rigid registration with mutual information metrics. Brain extraction using FSL BET protocols. Normalization to MNI space using ANTs SyN algorithm. VTA modeling incorporates detailed tissue conductivity models (gray matter 0.2 S/m, white matter 0.14 S/m, CSF 1.7 S/m). Finite element model to compute electric field distribution. Voxel-wise statistical methods to analyze correlations between VTA characteristics and voice outcomes.

Statistical Analysis: Repeated measures ANOVA for primary outcomes. Mixed-effects models for longitudinal data. Missing data (<20%) handled through multiple imputation. Bonferroni corrections for multiple comparisons. All analyses documented using standardized protocols with regular quality control checks.

Safety Monitoring: Qualified clinician present for all DBS adjustments. Immediate adverse event reporting. Independent safety monitoring board reviews. Individual stopping criteria: severe dysarthria, intolerable sensory symptoms, significant gait changes, or patient withdrawal request. Study-wide stopping criteria: >30% participants experiencing adverse effects or pattern of serious adverse events.

Timeline: Months 1-2: IRB approval, staff training, pilot testing. Months 3-8: Active recruitment. Months 4-12: Data collection, interim safety reviews. Months 13-15: Data analysis, manuscript preparation, conference abstracts.

Required Software (to be provided by lab/mentor):

- Acoustic analysis software for voice recording processing and Fourier analysis (e.g., Praat, MATLAB with Signal Processing Toolbox)

- Neuroimaging software: FSL (FMRIB Software Library) for brain extraction, ANTs (Advanced Normalization Tools) for image registration and normalization

- Statistical analysis software: R or SPSS for repeated measures ANOVA and mixed-effects models

- VTA modeling software: Finite element modeling software (e.g., COMSOL Multiphysics or custom MATLAB scripts)

- Image co-registration software for CT-MRI alignment

- Telemedicine platform: HIPAA-compliant video conferencing for remote sessions

- Randomization software for computer-generated assignment of stimulation conditions

Conferences Available for Participation:

- Movement Disorder Society (MDS) Annual Congress

- American Academy of Neurology (AAN) Annual Meeting

- Society for Neuroscience (SfN) Annual Meeting

- North American Neuromodulation Society (NANS) Annual Meeting

- American Speech-Language-Hearing Association (ASHA) Convention

- International Parkinson and Movement Disorder Society

- Neurology research-focused conferences at University of Chicago and local institutions