Papers A Clinically Interpretable Computer-Vision Based Method for Quantifying Gait in Parkinson’s Disease Published: 12 Aug 2021 Posters Maximising UPDRS information while minimising assessment time Presented at the MDS Congress 2021 A Computer-Vision Based Method for Quantifying Parkinsonian Gait Presented at the MDS Congress 2021 Evidence of possible bias in pre-surgical assessment of Parkinson’s disease using levodopa challenges Presented at the ESSFN Congress 2021 Bayesian Estimation of Gait Cadence from Monocular Video Presented at the MDS Congress 2020 Real Time Quality Control for Subjective Endpoints in Clinical Trials Presented at the MDS Congress 2020 Assessment of Parkinson’s Disease Severity using Machine Learning Presented at the CNS Summit 2019 Master Theses *Awarded Distinction A Machine Learning Approach to Human Activity Recognition in Parkinson's Disease Assessments* Published: 1 Sep 2021 Efficient remote assessment in Parkinson's Disease: maximizing information from simplified assessment procedures* Published: 1 Sep 2020 Extracting neuromotor biomarkers of Parkinson’s Disease from video data* Published: 22 Aug 2018 Mr Joshua Ong Shun You University College London Mr Jingxuan Tang The University of Warwick Ms Tanmaiyii Rao Queen Mary, University of London
