Artificial Intelligence-Based Facial Palsy Evaluation: A Survey - Yating Zhang; Weixiang Gao; Hui Yu; Junyu Dong; Yifan Xia (IEEE, 2024)
Facial palsy evaluation (FPE) aims to assess facial palsy severity of patients, which plays a vital role in facial functional treatment and rehabilitation. The traditional manners of FPE are based on subjective judgment by clinicians, which may ultimately depend on individual experience. Compared with subjective and manual evaluation, objective and automated evaluation using artificial intelligence (AI) has shown great promise in improving traditional manners and recently received significant attention. The motivation of this survey paper is mainly to provide a systemic review that would guide researchers in conducting their future research work and thus make automatic FPE applicable in real-life situations. In this survey, we comprehensively review the state-of-the-art development of AI-based FPE. First, we summarize the general pipeline of FPE systems with the related background introduction. Following this pipeline, we introduce the existing public databases and give the widely used objective evaluation metrics of FPE. In addition, the preprocessing methods in FPE are described. Then, we provide an overview of selected key publications from 2008 and summarize the state-of-the-art methods of FPE that are designed based on AI techniques. Finally, we extensively discuss the current research challenges faced by FPE and provide insights about potential future directions for advancing state-of-the-art research in this field.