DocumentCode
2120397
Title
Emergency psychiatric state prediction for ambient assisted living
Author
Rabiul Alam, Md Golam ; Rim Haw ; Choong Seon Hong
Author_Institution
Kyung Hee Univ., Yongin, South Korea
fYear
2015
fDate
9-12 Jan. 2015
Firstpage
220
Lastpage
221
Abstract
Mental healthcare can be the smart home service for ambient assisted living. In this paper, a web of objects embedded smart home architecture is presented for mental healthcare. Patients´ psychiatric symptoms are collected through lightweight bio-sensors and web based psychiatric screening scales and then analyzed using machine learning algorithms.
Keywords
assisted living; biomedical measurement; biosensors; learning (artificial intelligence); medical computing; medical disorders; psychology; ambient assisted living; emergency psychiatric state prediction; lightweight biosensors; machine learning algorithms; mental healthcare; patient psychiatric symptoms; smart home service; web based psychiatric screening scales; web of objects embedded smart home architecture; Biological system modeling; Computer architecture; Hidden Markov models; Medical services; Monitoring; Service-oriented architecture; Smart homes;
fLanguage
English
Publisher
ieee
Conference_Titel
Consumer Electronics (ICCE), 2015 IEEE International Conference on
Conference_Location
Las Vegas, NV
Print_ISBN
978-1-4799-7542-6
Type
conf
DOI
10.1109/ICCE.2015.7066388
Filename
7066388
Link To Document