1 Citationer (Scopus)
86 Downloads (Pure)

Abstrakt

Social signal extraction from the facial analysis is
a popular research area in human-robot interaction. However,
recognition of emotional signals from Traumatic Brain Injured
(TBI) patients with the help of robots and non-intrusive sensors
is yet to be explored. Existing robots have limited abilities to
automatically identify human emotions and respond accordingly. Their interaction with TBI patients could be even more
challenging and complex due to unique, unusual and diverse
ways of expressing their emotions. To tackle the disparity
in a TBI patient’s Facial Expressions (FEs), a specialized
deep-trained model for automatic detection of TBI patients’
emotions and FE (TBI-FER model) is designed, for robotassisted rehabilitation activities. In addition, the Pepper robot’s
built-in model for FE is investigated on TBI patients as well
as on healthy people. Variance in their emotional expressions
is determined by comparative studies. It is observed that the
customized trained system is highly essential for the deployment
of Pepper robot as a Socially Assistive Robot (SAR).
OriginalsprogEngelsk
Titel28th IEEE International Conference on Robot and Human Interactive Communication (ROMAN)
ForlagIEEE
Publikationsdato12 okt. 2019
Artikelnummer8956445
ISBN (Elektronisk)978-1-7281-2622-7
DOI
StatusUdgivet - 12 okt. 2019
BegivenhedThe 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN): Ro-man2019 - New Delhi, Indien
Varighed: 14 okt. 201918 nov. 2019
https://ro-man2019.org/

Konference

KonferenceThe 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)
LandIndien
ByNew Delhi
Periode14/10/201918/11/2019
Internetadresse
NavnIEEE RO-MAN proceedings
ISSN1944-9445

Fingeraftryk Dyk ned i forskningsemnerne om 'Teaching Pepper Robot to Recognize Emotions of Traumatic Brain Injured Patients Using Deep Neural Networks'. Sammen danner de et unikt fingeraftryk.

Citationsformater