Movement State-Dependent Adaptive Deep Brain Stimulation for Parkinson's Disease

This study will allow the investigators to evaluate the efficacy of a movement state-dependent adaptive deep brain stimulation paradigm to treat gait dysfunction in individuals with Parkinson's disease (PD).

While current DBS therapy improves the appendicular symptoms of PD, such as tremor and bradykinesia, it is less effective for advanced gait symptoms, which manifest as hypokinetic gait patterns, increased gait variability, asymmetry, and disturbed balance. These symptoms are debilitating and represent a major source of morbidity for patients with PD. Studies have suggested that while conventional high-frequency stimulation settings are good at treating appendicular symptoms, they may not be as effective for axial symptoms such as gait disorders. Modulating stimulation parameters, by using lower frequencies, for instance, has been shown to improve gait kinematics such as symmetry and rhythmicity. However, these settings are less effective for other symptoms and therefore come at the expense of appendicular symptom control. The overall objective of this study is to identify personalized electrophysiological signatures of movement state and gait-optimized stimulation parameters in PD patients to enable adaptive control algorithms that automatically switch from identified 'gait-optimized' settings during walking to 'other PD symptom-optimized' settings during non-walking.

This is a small, double-blinded trial, six patients with idiopathic PD and motor fluctuations who have already been implanted with the RC+S devices. The investigators will compare the overall efficacy of closed-loop (adaptive DBS) and open-loop (continuous clinical DBS) paradigms in terms of behavioral performance improvements. During this chronic movement state-dependent adaptive DBS phase, adaptive DBS and open-loop stimulation settings will be randomized for 7-day periods, and motor and gait-related measurements will be obtained from wearable devices that track movement kinematics. Patients will participate in daily, if possible, motor and gait tasks at home and are asked to fill out motor diary questionnaires to share their feedback from both motor and non-motor perspectives.

The investigators expect to successfully develop a prototype movement state-dependent adaptive DBS algorithm. They hypothesize that the embedded closed-loop, movement state-dependent adaptive DBS paradigm will improve gait function compared to the conventional open-loop approach, in which stimulation parameters remain constant, while maintaining the standard therapeutic benefits of DBS.