A Pose-Based Feature Fusion and Classification Framework for the Early Prediction of Cerebral Palsy in Infants

  title={A Pose-Based Feature Fusion and Classification Framework for the Early Prediction of Cerebral Palsy in Infants},
  author={Kevin D. McCay and Pengpeng Hu and Hubert P. H. Shum and Wai Lok Woo and Claire Marcroft and Nicholas D. Embleton and Adrian Munteanu and Edmond S. L. Ho},
  journal={IEEE Transactions on Neural Systems and Rehabilitation Engineering},
The early diagnosis of cerebral palsy is an area which has recently seen significant multi-disciplinary research. Diagnostic tools such as the General Movements Assessment (GMA), have produced some very promising results. However, the prospect of automating these processes may improve accessibility of the assessment and also enhance the understanding of movement development of infants. Previous works have established the viability of using pose-based features extracted from RGB video sequences… 

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    2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
  • 2018
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