Symptom Biomarkers in Ambulatory Neurobehavioral Data in Parkinson's Disease

Masterthesis / Biomedical Engineering
Written By Kai Peter

Type of Research: Masterthesis / Biomedical Engineering

Status: Open

Time frame: December 2023 - September 2024

Description: Background
Deep brain stimulation (DBS) is an established therapy for patients with Parkinson’s disease (PD). While for the last 30 years, neurostimulators were only capable of delivering stimulation to the brain, new available neurostimulators (Percept™ PC Medtronic PLC, USA) are also enabled to record brain signals chronically. This technological advancement is important as it helps to better understand the neurophysiological basis of disease-related symptoms and physiological activity states in the daily life of patients. Furthermore, it is also key to develop closed-loop adaptive DBS, in which stimulation is not delivered continuously, but in response to individually fluctuating brain symptom biomarkers. In the context of an on-going research protocol with the goal to study the neurophysiological basis of symptom and behavioural fluctuations, we collect brain signal, motion-, symptom- and behavioural data over consecutive weeks in patient with PD.

Aim
The goal of this project is to identify potential symptom and behavioural biomarker in ambulatory multimodal data in PD patients by studying the link between intracranial local field potentials (LFPs) and the patient reported symptom state, activity state, the circadian profile and medication state.

Materials and Methods
Ambulatory long-term recordings over 4 consecutive weeks are available for several PD patients. These long-term data streams include bilateral, intracranial brain signals, accelerometer and heart rate data, symptom severity logs, circadian states and medication schedules. All data streams will be managed and pre-processed using a MATLAB based platform. The student will apply classical and advanced computational analyses to investigate relationships and predictive value of neurophysiological brain recordings for symptom and behavioural states.

Supervisor: Gerd Tinkhauser

Departement / Research Group: Departement of Neurology, Tinkhauser Group

Language: English

ECTS: 30

Further Details: Thesis Proposal_Colombo.pdf

Kai Peter
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