Clinical rating scales are the traditional gold standard in tracking the progression of neurological disorders. However, they are subjective and include inter-rater reliability and noise. This is epitomised by Progressive Supranuclear Palsy (PSP) that is difficult to diagnose and follow its progression, impacting the ability to find an effective therapy. Advances in digital technology provide the potential to find objective biomarkers that more accurately and reliably track the progression of PSP. Previous work validated the use of wearable sensors to successfully distinguish PSP from Parkinson’s disease. The Oxford Quantification in Parkinsonism Study used a six-sensor wearable array to monitor PSP patients performing a battery of tasks across a period of two-three years, three months between each hospital visit. This project used the data obtained from these patients to find objective measures of PSP progression. A process of dimensionality reduction was necessary to reduce the large number of parameters extracted from the sensors to a small list of relevant features for statistical analysis. A set of parameters were found to reflect PSP progression by visit 4/5 (12/15 months) of the study. Most of these features were associated with gait. This was compared to common clinical rating scales for PSP; the clinical rating scales found fewer parameters associated with PSP progression at this early stage. The ability of the wearable sensors to successfully find objective biomarkers at this early stage of PSP progression means these features could be tracked in clinical studies to determine the efficacy of potential therapeutics.