Pose-Based Tremor Type and Level Analysis for Parkinson’s Disease from Video
Haozheng Zhang, Edmond S. L. Ho, Francis Xiatian Zhang, Silvia Del Din and Hubert P. H. Shum
International Journal of Computer Assisted Radiology and Surgery (IJCARS), 2024
Impact Factor: 2.3†
Abstract
Purpose: Current methods for diagnosis of PD rely on clinical examination. The accuracy of diagnosis ranges between 73\% and 84\%, and is influenced by the experience of the clinical assessor. Hence, an automatic, effective and interpretable supporting system for PD symptom identification would support clinicians in making more robust PD diagnostic decisions.
Cite This Research
Supporting Grants
Northern Health Futures Hub (NortHFutures)
EPSRC Digital Health Hub Pilot Scheme (Ref: EP/X031012/1): £4.17 million, Co-Investigator (PI: Prof. Abigail Durrant)
Received from The Engineering and Physical Sciences Research Council, UK, 2023-2026
Project Page
EPSRC Digital Health Hub Pilot Scheme (Ref: EP/X031012/1): £4.17 million, Co-Investigator (PI: Prof. Abigail Durrant)
Received from The Engineering and Physical Sciences Research Council, UK, 2023-2026
Project Page
Similar Research
Haozheng Zhang, Edmond S. L. Ho, Francis Xiatian Zhang and Hubert P. H. Shum, "Pose-Based Tremor Classification for Parkinson’s Disease Diagnosis from Video", Proceedings of the 2022 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022
Haozheng Zhang, Hubert P. H. Shum and Edmond S. L. Ho, "Cerebral Palsy Prediction with Frequency Attention Informed Graph Convolutional Networks", Proceedings of the 2022 International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2022
Manli Zhu, Qianhui Men, Edmond S. L. Ho, Howard Leung and Hubert P. H. Shum, "Interpreting Deep Learning Based Cerebral Palsy Prediction with Channel Attention", Proceedings of the 2021 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), 2021
Haozheng Zhang, Edmond S. L. Ho and Hubert P. H. Shum, "CP-AGCN: Pytorch-Based Attention Informed Graph Convolutional Network for Identifying Infants at Risk of Cerebral Palsy", Software Impacts (SIMPAC), 2022
Kevin D. McCay, Pengpeng Hu, Hubert P. H. Shum, Wai Lok Woo, Claire Marcroft, Nicholas D. Embleton, Adrian Munteanu and Edmond S. L. Ho, "A Pose-Based Feature Fusion and Classification Framework for the Early Prediction of Cerebral Palsy in Infants", IEEE Transactions on Neural Systems and Rehabilitation Engineering (TNSRE), 2022