TY - GEN
T1 - Emotional healthcare system
T2 - 2014 6th Computer Science and Electronic Engineering Conference, CEEC 2014
AU - Tivatansakul, Somchanok
AU - Ohkura, Michiko
AU - Puangpontip, Supadchaya
AU - Achalakul, Tiranee
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/11/14
Y1 - 2014/11/14
N2 - Good emotional health is one important point to improve quality of life. On the other hand, bad emotional health can lead to social or mental health problems. To cope with the bad emotional health caused by negative emotions in daily life, we design a healthcare system that focuses on emotional aspects and provides services to improve user emotions. To improve them, we need to recognize their current emotional states. Therefore, our system integrates emotion detection to suggest appropriate services and is designed as a web-based system. While users use the system, facial expressions and speech are detected and analyzed to determine their emotions. When negative emotions are detected, our system suggests that users take a break and provides appropriate services (including relaxation, amusement and excitement services) with augmented reality and Kinect to improve their emotional states. This paper focuses on feature extraction and the classification of emotion detection by facial expressions.
AB - Good emotional health is one important point to improve quality of life. On the other hand, bad emotional health can lead to social or mental health problems. To cope with the bad emotional health caused by negative emotions in daily life, we design a healthcare system that focuses on emotional aspects and provides services to improve user emotions. To improve them, we need to recognize their current emotional states. Therefore, our system integrates emotion detection to suggest appropriate services and is designed as a web-based system. While users use the system, facial expressions and speech are detected and analyzed to determine their emotions. When negative emotions are detected, our system suggests that users take a break and provides appropriate services (including relaxation, amusement and excitement services) with augmented reality and Kinect to improve their emotional states. This paper focuses on feature extraction and the classification of emotion detection by facial expressions.
KW - E-Healthcare
KW - Emotion Recognition
KW - Facial Expressions
UR - http://www.scopus.com/inward/record.url?scp=84915764282&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84915764282&partnerID=8YFLogxK
U2 - 10.1109/CEEC.2014.6958552
DO - 10.1109/CEEC.2014.6958552
M3 - Conference contribution
AN - SCOPUS:84915764282
T3 - 2014 6th Computer Science and Electronic Engineering Conference, CEEC 2014 - Conference Proceedings
SP - 41
EP - 46
BT - 2014 6th Computer Science and Electronic Engineering Conference, CEEC 2014 - Conference Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 25 September 2014 through 26 September 2014
ER -