Neuromodulation as a Therapeutic Strategy to Enhance Motor Function After Spinal Cord Injury
Locomotor Training for individuals with Incomplete Spinal Cord Injury (iSCI) is grounded in the principle that the spinal cord can relearn walking when provided with appropriate sensory inputs. While emerging evidence highlights the important role of Arm Swing in modulating Leg Muscle Activity, its integration into rehabilitation strategies remains underexplored. In this Feasibility Study, we aim to leverage our combined expertise in Biomechanics and Neuromodulation to investigate the effects of Transcutaneous Spinal Stimulation on Brain and Leg Muscle Activity within the context of Gait Rehabilitation. Our goal is to inform the development of more effective, holistic training protocols that support functional recovery in individuals with iSCI.
Neural Correlates of Chronic Pain and Objective Pain Assessment
Chronic Pain affects over 50 million adult Americans and remains one of the most common reasons for seeking medical care. Spinal Cord Stimulation (SCS) is an FDA-approved neuromodulation therapy used to treat chronic, refractory pain. While SCS is widely utilized, there are currently no objective tools to measure its effectiveness in patients with chronic pain. Moreover, Patient Responses to SCS Vary Significantly, and there is no established consensus on optimal stimulation parameters or device selection. To address these challenges, our research integrates Perioperative Electrophysiology—including EEG, ECG, eye tracking, and wearable sensors—with Advanced Signal Processing, Machine Learning, and neuromodulation techniques. Our goal is to identify Neural Correlates of Chronic Pain and develop Quantitative, Objective Measures for its assessment. This work aims to transform chronic pain management and support the development of Next-Generation Medical Technologies that personalize and optimize treatment.
Distinguishing Parkinson’s Disease Phenotypes & Personalized Neuromodulation
Parkinson’s Disease (PD) is the second most common neurodegenerative disorder, yet significant Heterogeneity remains in how the disease is subtyped using both clinical and data-driven methods. Most commonly, patients are grouped based on Motor Symptom Profiles into categories such as Tremor-Dominant (TD), Akinesia-Rigidity (AR), and Postural Instability and Gait Disorder (PIGD). Each phenotype is associated with distinct Disease Progression, Symptom Severity, and Clinical Characteristics, and emerging evidence suggests that response to Deep Brain Stimulation (DBS) may also vary by phenotype. To address this variability, our research integrates peri-operative electrophysiology (e.g., local field potentials [LFP], single-unit activity [SUA], EEG), Neuroimaging (e.g., fMRI), advanced Signal Processing, Machine Learning, and Neuromodulation techniques. Our goal is to Characterize the Neural Signatures of PD phenotypes and to support the development of more Personalized and Adaptive DBS Therapies, ultimately improving clinical outcomes and quality of life for individuals with PD.
Biomarker Discovery, Development of Novel Tools & Advancing Technology
Studying the Pathophysiology and Functional Circuitry of neurological diseases plays a critical role in shaping Electrode Technology, where advances in Electrode Design can reveal new dimensions of neural activity, enabling more precise targeting and improved therapeutic outcomes. Leveraging Perioperative Electrophysiology (e.g., EEG, EMG, peripheral field potentials [PF], local field potentials [LFP], and single-unit activity [SUA]), along with Signal Processing, Machine Learning Decoding, Wearable Sensors, and Neuromodulation Techniques (e.g., SCS and DBS), our research focuses on developing a suite of innovative tools. These include High-Resolution Functional Brain and Spinal Mapping, Electrophysiology-Guided Target Localization, improved Electrode Placement, Clinical Programming Guided by Real-Time Neural Data, Robust and Rapid Data Visualization Platforms, and Diagnostic and Prognostic Tools. We are also working to Integrate Smart Health Wearables into clinical decision-making frameworks and Optimize Neuromodulation Therapy to enhance patient-specific outcomes.
Assessment of Chronic Pain in Alzheimer’s Disease
More than Six Million Americans are living with Alzheimer’s Disease and Related Dementias (ADRD), conditions marked by cognitive and behavioral impairments. Alarmingly, over 50% of Community-Dwelling Older Adults with ADRD experience Daily Chronic Pain, which often goes untreated due to their limited ability to Communicate Pain Verbally. As verbal expression declines, pain is frequently Under-Recognized and Poorly Managed, leading to diminished quality of life. To address this critical gap, we aim to develop Reliable and Objective Biomarkers for chronic pain. Leveraging Electrophysiological Tools such as Wearable EEG, EMG, and Eye Tracking, along with advanced Signal Processing and Machine Learning, our research seeks to identify Neural Signatures of Chronic Pain in older adults with early-stage ADRD, compared to healthy controls. This work has the potential to transform Pain Assessment and Treatment in a highly vulnerable population.
