AIMC Topic: Facial Paralysis

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The Auto-eFACE: Machine Learning-Enhanced Program Yields Automated Facial Palsy Assessment Tool.

Plastic and reconstructive surgery
BACKGROUND: Facial palsy assessment is nonstandardized. Clinician-graded scales are limited by subjectivity and observer bias. Computer-aided grading would be desirable to achieve conformity in facial palsy assessment and to compare the effectiveness...

Using Artificial Intelligence to Measure Facial Expression following Facial Reanimation Surgery.

Plastic and reconstructive surgery
Social interactions are largely dependent on the interpretation of information conveyed through facial expressions. Although facial reanimation seeks restoration of the facial expression of emotion, outcome measures have not addressed this directly. ...

Toward an Automatic System for Computer-Aided Assessment in Facial Palsy.

Facial plastic surgery & aesthetic medicine
Quantitative assessment of facial function is challenging, and subjective grading scales such as House-Brackmann, Sunnybrook, and eFACE have well-recognized limitations. Machine learning (ML) approaches to facial landmark localization carry great cl...

Design of Soft Robotic Actuation for Supporting Eyelid Closure Movement.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
We have been developing a facial wearable robot to support the eyelid movements of patients with facial paralysis, especially on one side of the face [1]. This robot has a mechanism for supporting eyelid movements, made from a soft material, which is...