Web of Objects Based Ambient Assisted Living Framework for Emergency Psychiatric State Prediction.
Ambient assisted living can facilitate optimum health and wellness by aiding physical, mental and social well-being. In this paper, patients' psychiatric symptoms are collected through lightweight biosensors and web-based psychiatric screening scales in a smart home environment and then analyzed through machine learning algorithms to provide ambient intelligence in a psychiatric emergency. The psychiatric states are modeled through a Hidden Markov Model (HMM), and the model parameters are estimated using a Viterbi path counting and scalable Stochastic Variational Inference (SVI)-based training algorithm. The most likely psychiatric state sequence of the corresponding observation sequence is determined, and an emergency psychiatric state is predicted through the proposed algorithm. Moreover, to enable personalized psychiatric emergency care, a service a web of objects-based framework is proposed for a smart-home environment. In this framework, the biosensor observations and the psychiatric rating scales are objectified and virtualized in the web space. Then, the web of objects of sensor observations and psychiatric rating scores are used to assess the dweller's mental health status and to predict an emergency psychiatric state. The proposed psychiatric state prediction algorithm reported 83.03 percent prediction accuracy in an empirical performance study.
Computer Science and Engineering, Kyung Hee University, 1732 Deokyoungdaero, Gilheung-gu, Yongin-si 446-701, Korea. robi@khu.ac.kr.
Md Golam Rabiul
MG
Alam
Computer Science and Engineering, Kyung Hee University, 1732 Deokyoungdaero, Gilheung-gu, Yongin-si 446-701, Korea. saab0015@khu.ac.kr.
Sarder Fakhrul
SF
Abedin
Computer Science and Engineering, Kyung Hee University, 1732 Deokyoungdaero, Gilheung-gu, Yongin-si 446-701, Korea. ameen@khu.ac.kr.
Moshaddique
M
Al Ameen
Computer Science and Engineering, Kyung Hee University, 1732 Deokyoungdaero, Gilheung-gu, Yongin-si 446-701, Korea. cshong@khu.ac.kr.
Choong Seon
CS
Hong
D000328:Adult; D000368:Aged; D000465:Algorithms; D019540:Area Under Curve; D040561:Assisted Living Facilities; D015374:Biosensing Techniques; D016002:Discriminant Analysis; D005260:Female; D006801:Humans; D020407:Internet; D008297:Male; D008390:Markov Chains; D008603:Mental Health; D008875:Middle Aged; D018670:Monitoring, Ambulatory; D016017:Odds Ratio; D025341:Principal Component Analysis; D012372:ROC Curve; D055815:Young Adult
ambient assisted living; emergency psychiatry; mental healthcare; smart home; web of objects