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

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

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...

وصف كامل

التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Kevin D. McCay, Pengpeng Hu, Hubert P. H. Shum, Wai Lok Woo, Claire Marcroft, Nicholas D. Embleton, Adrian Munteanu, Edmond S. L. Ho
التنسيق: مقال
اللغة:English
منشور في: IEEE 2022-01-01
سلاسل:IEEE Transactions on Neural Systems and Rehabilitation Engineering
الموضوعات:
Cerebral palsy
early diagnosis
explainable AI
general movements assessment
machine learning
motion analysis
الوصول للمادة أونلاين:https://ieeexplore.ieee.org/document/9662301/

الانترنت

https://ieeexplore.ieee.org/document/9662301/

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