Early Cerebral Palsy Screening through Deep Learning
Utilising computer vision to aid in the early diagnosis of cerebral palsy in infants
In infants, signature movements indicating a risk of cerebral palsy (CP) are weak and therefore easily overwhelmed by more dominant but irrelevant gross body motions. Furthermore, such signatures are highly specific and subtle, making them normally only recognisable by medical experts. These intricacies pose major challenges for computer vision system to recognise and extract those movements from video signals.
However, A2I2’s computer vision research program is making significant progress in analysing videos of infants and babies for CP detection. This work is funded by the NHMRC and in collaboration with our medical partners including Cerebral Palsy Alliance and Perth Children’s Hospital. Our recently published method for CP early detection achieves highest accuracy ever reported for this problem.
Image (C) Baby Moves and VICS trials