Facial Point Graphs for Amyotrophic Lateral Sclerosis Identification

Nicolas Gomes, Arissa Yoshida, Mateus Roder, Guilherme Camargo de Oliveira, Guilherme Camargo de Oliveira, João Paulo Papa

2024

Abstract

Identifying Amyotrophic Lateral Sclerosis (ALS) in its early stages is essential for establishing the beginning of treatment, enriching the outlook, and enhancing the overall well-being of those affected individuals. However, early diagnosis and detecting the disease’s signs is not straightforward. A simpler and cheaper way arises by analyzing the patient’s facial expressions through computational methods. When a patient with ALS engages in specific actions, e.g., opening their mouth, the movement of specific facial muscles differs from that observed in a healthy individual. This paper proposes Facial Point Graphs to learn information from the geometry of facial images to identify ALS automatically. The experimental outcomes in the Toronto Neuroface dataset show the proposed approach outperformed state-of-the-art results, fostering promising developments in the area.

Paper Citation

in Harvard Style

Gomes N., Yoshida A., Roder M., Camargo de Oliveira G. and Paulo Papa J. (2024). Facial Point Graphs for Amyotrophic Lateral Sclerosis Identification. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP; ISBN 978-989-758-679-8, SciTePress, pages 207-214. DOI: 10.5220/0012428400003660

in Bibtex Style

@conference{visapp24,
author={Nicolas Gomes and Arissa Yoshida and Mateus Roder and Guilherme Camargo de Oliveira and João Paulo Papa},
title={Facial Point Graphs for Amyotrophic Lateral Sclerosis Identification},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP},
year={2024},
pages={207-214},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012428400003660},
isbn={978-989-758-679-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP
TI - Facial Point Graphs for Amyotrophic Lateral Sclerosis Identification
SN - 978-989-758-679-8
AU - Gomes N.
AU - Yoshida A.
AU - Roder M.
AU - Camargo de Oliveira G.
AU - Paulo Papa J.
PY - 2024
SP - 207
EP - 214
DO - 10.5220/0012428400003660
PB - SciTePress