Paper Info
Title
Rehabilitation Of Traumatic Brain Injured Patients: Patient Mood Analysis From Multimodal Video
Abstract
Rehabilitation after traumatic brain injury (TBI) is very critical as it is largely unpredictable depending upon the nature of the injury. Rehabilitation process and recovery time also varies, as it takes months and years, depending upon the assessment of treatment, mental and physical conditions and strategies. Due to non-cooperative behaviour of patients, and increase in negative emotional expressions it is very beneficial to evaluate these expressions in a contactless way, and perform a rehabilitation physiotherapy, cognitive or other behavioral activities when the patient is in a positive mood. In this paper we have analyzed the methods for facial features extraction for TBI patients to determine optimal time to have aforementioned rehabilitation process on the basis of positive and negative facial expressions. We have employed a deep learning architecture based on convolutional neural network and long short term memory on RGB and thermal data that were collected in challenging scenarios from real patients. It automatically identifies the patient's facial expressions, and inform experts or trainers that "it is the time" to start rehabilitation session.
Year
Venue
Field
2018
2018 25TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)
Rehabilitation,Mood,Expression (mathematics),Pattern recognition,Computer science,Emotional expression,Facial expression,Artificial intelligence,Physical medicine and rehabilitation,Deep learning,Cognition,Traumatic brain injury
DocType
ISSN
Citations 
Conference
1522-4880
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Chaudhary Muhammad Aqdus Ilyas101.35
Kamal Nasrollahi233034.11
Matthias Rehm315721.98
Thomas Moeslund42721186.08