Facial Paralysis

Facial paralysis, a condition affecting facial muscle movement and expression, is a focus of intense research aiming to improve diagnosis and treatment. Current efforts leverage deep learning models, including convolutional neural networks (ResNet) and recurrent neural networks (BiLSTM), often incorporating multimodal data fusion (images, facial landmarks, expression features) to achieve more accurate and objective assessments than traditional clinical methods. These advancements are crucial for developing automated diagnostic tools and improving the effectiveness of rehabilitation strategies, ultimately enhancing patient care and reducing the burden on healthcare professionals. The development of user-friendly toolboxes is also improving accessibility for clinicians.