Digital tracking of Parkinson’s disease symptoms
Lead supervisor: Professor Michele Hu
Co-supervisor: Dr Ashwini Oswal
Commercial partner: NeuHealth
Parkinson’s disease (PD) is the neurological condition with the fastest growing incidence. It is estimated that 153,000 people are currently living with PD in the UK, with approximately 70 new diagnoses being made daily. Limitations on NHS resources mean that face-to-face clinic appointments are often short and infrequent, necessitating approaches that allow for effective remote monitoring of clinical status and disease progression.
The goal of this project is to develop and to validate the effectiveness of a smartphone and wearable technology-based platform for remotely monitoring the symptoms and progression of patients with PD. Our commercial partner, NeuHealth (https://neu.health/) has developed a smartphone app that uses accelerometry and task-based assessments to remotely monitor motor, cognitive and neuropsychiatric symptoms in PD. These data are then summarised for healthcare providers. There is currently a large existing cohort of NHS patients who are using this platform to collect measurements that are shared securely with clinical teams.
The NeuHealth platform aims to translate digital measures into interpretable metrics which can be used to:
1. classify disease subtypes based on patterns of motor and cognitive involvement
2. predict rates of progression
3. select personalised therapies for patients including medication dosage, timing and suitability for advanced therapies (such as Deep Brain Stimulation)
This project will offer the possibility to both contribute to the development of the NeuHealth platform and to analyse large existing datasets to address the goals listed above. The student will leverage signal processing approaches and machine learning for data analyses. There will also be opportunities to integrate measurements from the NeuHealth app with blood-based biomarkers and electroencephalography (EEG) – to provide complimentary information about disease progression and brain network dynamics.
This collaboration benefits NeuHealth, Oxford University and the MRC:
NeuHealth: The technical team at NeuHealth will benefit from our expertise in data analytics, signal processing and the clinical care of patients with PD. These capabilities will assist them with their product development roadmap, in terms of both algorithm development/validation and refinement of existing user interfaces.
Oxford: We will have unique access to extensive longitudinal datasets collected from the NeuHealth monitoring platform. These data will allow us to address important questions relevant to the classification, progression and treatment of PD. We will also bring expertise in fluid biomarker assessments and neurophysiology that will compliment data from the NeuHealth platform, enabling us to develop robust multimodal biomarkers.
MRC: This project aligns with the MRC objectives of building high quality capacity in precision medicine including data analytics and data science at the interface of human health and biology.
The success of this research could allow for improved diagnosis and monitoring of PD, as well as informing the development of personalised therapeutic strategies.
Apply using course: DPhil in Clinical Neuroscience
