17th International Conference on Computational Intelligence Methods for Bioinformatics and Biostatistics

CIBB 2021

You should be logged in to see the presentation

Technical Session

CIBB 2021 - Neurodegenrative Diseases Session

End-to-end facial landmark detection to characterise oro-facial impairments in neurological patients: towards innovative techniques for the assessment of dysarthria

  Lucia Migliorelli

  • ABSTRACT

Patients suffering from neurodegenerative diseases (e.g., amyotrophic lateral sclerosis (ALS) and stroke) may develop dysarthria, a neurological disorder that causes pervasive and unrelenting speech troubles. Dysarthria-evolution monitoring, via the assessments of oro-facial musculature, is crucial for allowing clinicians to promptly implement corrective and compensatory strategies to tackle communicative disability. To support clinicians, we propose a deep learning-based approach to facial landmarks detection as useful prior for assessing the oro-facial muscles impairments caused by ALS and stroke. When tested on the Toronto NeuroFace dataset, which is the largest publicly available annotated dataset in the field, the proposed approach reached a normalized mean error equal to 1.79, promptly the possibility of translating such technology in the actual clinical practice.

  • PRESENTER

Lucia Migliorelli
  Università Politecnica delle Marche, Italy

  • QUESTIONS & ANSWERS

There are still no questions. Be the first to post one!

  • SEND YOUR QUESTION