SERG ONE DBS – Sensor DBS Parametrisation to treat Parkinson’s Disease
Research type
Research Study
Full title
SERG ONE DBS - An Intelligent Mechanomyography Sensor Platform for Precise Deep Brain Stimulation Parametrisation to Treat Parkinson's Disease
IRAS ID
338550
Contact name
Christos Kapatos
Contact email
Sponsor organisation
SERG Technologies
Duration of Study in the UK
0 years, 3 months, 31 days
Research summary
Parkinson's is the fastest-growing progressive neurodegenerative disease and, even to this day, has no cure. Oral therapy with dopamine replacement drugs may be initially successful, however, as the disease progresses, more complex and advanced treatment is usually required. Deep Brain Stimulation (DBS), an advanced surgical therapy, in combination with oral therapy, can be offered to treat advanced Parkinson’s symptoms.
DBS is a highly sophisticated therapy that addresses the debilitating movement symptoms of Parkinson’s. A pulse generator is implanted under the skin around the chest area that is connected to electrodes inserted into targeted areas of the brain. The pulse generator delivers high-frequency electrical stimulation, altering some of the electrical signals in the brain causing the symptoms of Parkinson’s.
The settings on DBS devices require adjustment over time as the condition advances. Technical improvements are very much limited by the complexity of tuning the device for each specific patient. Additionally, current tuning strategies are not based on a structured approach and rely heavily on the clinician remembering symptom presentation and previous settings.
In this study, we will validate a new, continuous scale for rating symptom severity that will use objective data gathered from the SERG-ONE sensor suite. This includes a combination of inertial (movement) sensors and mechanomyography (muscle activity) sensors for scoring the symptoms of Parkinson’s Disease. This information, along with clinical observations, will be entered into the StimSearch algorithm, developed by Boston Scientific. This maps the parameter space for each patient and will provide recommendations to the clinician to aid in their parameter search.
We aim to demonstrate a new method of objectively recording symptom severity during a tuning session, allowing the parameter space to be accurately mapped with a continuous scale. This will allow optimisation to be performed and reduce the time spent to find the best parameters.
REC name
Yorkshire & The Humber - Leeds West Research Ethics Committee
REC reference
24/YH/0216
Date of REC Opinion
25 Oct 2024
REC opinion
Favourable Opinion