Démence et perte cognitive

Broutart, Jean-Claude; Robert, P.; Balas, D; Broutart, Nicole; Cahors, Julien

doi:10.3917/dbu.vande.2017.01.0331

Questions De Personne

2017

DOI: 10.3917/dbu.vande.2017.01.0331

|View full text |Cite

Démence et perte cognitive

Jean-Claude Broutart¹,

P. Robert²,

D Balas³

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2019

Publication Types

Select...

Book1

Relationship

Self Cite1

Independent0

Authors

Journals

Cited by 1 publication

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Comparing Methods for Assessment of Facial Dynamics in Patients with Major Neurocognitive Disorders

Wang

Dantcheva

Broutart³

et al. 2019

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

Assessing facial dynamics in patients with major neurocognitive disorders and specifically with Alzheimers disease (AD) has shown to be highly challenging. Classically such assessment is performed by clinical staff, evaluating verbal and non-verbal language of AD-patients, since they have lost a substantial amount of their cognitive capacity, and hence communication ability. In addition, patients need to communicate important messages, such as discomfort or pain. Automated methods would support the current healthcare system by allowing for telemedicine, i.e., lesser costly and logistically inconvenient examination. In this work we compare methods for assessing facial dynamics such as talking, singing, neutral and smiling in AD-patients, captured during music mnemotherapy sessions. Specifically, we compare 3D Con-vNets, Very Deep Neural Network based Two-Stream ConvNets, as well as Improved Dense Trajectories. We have adapted these methods from prominent action recognition methods and our promising results suggest that the methods generalize well to the context of facial dynamics. The Two-Stream ConvNets in combination with ResNet-152 obtains the best performance on our dataset, capturing well even minor facial dynamics and has thus sparked high interest in the medical community.

show abstract

Comparing Methods for Assessment of Facial Dynamics in Patients with Major Neurocognitive Disorders

Wang

Dantcheva

Broutart³

et al. 2019

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Démence et perte cognitive

Cited by 1 publication

References 0 publications

Comparing Methods for Assessment of Facial Dynamics in Patients with Major Neurocognitive Disorders

Comparing Methods for Assessment of Facial Dynamics in Patients with Major Neurocognitive Disorders

Contact Info

Product

Resources

About