A data driven approach towards understanding deficits in olfactory and motor function and identifying applications of smartphone motor testing in prodromal and manifest Parkinson’s

Thesis

Background:

Significant disease heterogeneity in Parkinson’s means that identifying ways of applying observations made at a group level, to specific individuals, remains challenging. Standardised clinical assessments, critical for capturing the scientific evidence that informs clinical practice, are rarely used outside of research due to the time required for their administration.

Methods:

Since 2010, the Oxford Discovery longitudinal cohort study has re...

Expand abstract

Authors: Lo, C

• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: Outcome measures; Machine learning; REM sleep behaviour disorder; Smartphone; Parkinson's disease
• Subjects: Rapid eye movement sleep; Parkinson's disease; Medicine