EM-Psychiatry: An Ambient Intelligent System for Psychiatric Emergency
The proliferation of the market in patient care services is attracting attention in the healthcare industry; however, a remote mental healthcare system is still unattainable. In this paper, an ambient intelligent system of in-home psychiatric care service for emergency psychiatry (EM-psychiatry) is...
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| Format: | Article |
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Institute of Electrical and Electronics Engineers (IEEE)
2016
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| _version_ | 1796947205893914624 |
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| author | Alam, M.G.R. Haw, R. Kim, S.S. Azad, A.K. Abedin, S.F. Hong, C.S. |
| author_facet | Alam, M.G.R. Haw, R. Kim, S.S. Azad, A.K. Abedin, S.F. Hong, C.S. |
| author_sort | Alam, M.G.R. |
| collection | UM |
| description | The proliferation of the market in patient care services is attracting attention in the healthcare industry; however, a remote mental healthcare system is still unattainable. In this paper, an ambient intelligent system of in-home psychiatric care service for emergency psychiatry (EM-psychiatry) is proposed for the remote monitoring of psychiatric emergency patients. The emergency psychiatric states of patients are modeled as the states of the maximum-entropy Markov model (MEMM), in which sensor observations, psychiatric screening scores, and patients' histories are considered as the observations of MEMM. A modified Viterbi, a machine-learning algorithm, is used to generate the most probable psychiatric state sequence based on such observations; then, from the most likely psychiatric state sequence, the emergency psychiatric state is predicted through the proposed algorithm. The ambient EM-psychiatry model is implemented and the performance of the proposed prediction model is analyzed using the receiver operator characteristics curves, which demonstrates that the use of the EM-psychiatric screening questionnaire with biosensor observations enhances the prediction accuracy. |
| first_indexed | 2024-03-06T05:43:23Z |
| format | Article |
| id | um.eprints-17737 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:43:23Z |
| publishDate | 2016 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | um.eprints-177372017-09-07T05:37:10Z http://eprints.um.edu.my/17737/ EM-Psychiatry: An Ambient Intelligent System for Psychiatric Emergency Alam, M.G.R. Haw, R. Kim, S.S. Azad, A.K. Abedin, S.F. Hong, C.S. T Technology (General) TA Engineering (General). Civil engineering (General) The proliferation of the market in patient care services is attracting attention in the healthcare industry; however, a remote mental healthcare system is still unattainable. In this paper, an ambient intelligent system of in-home psychiatric care service for emergency psychiatry (EM-psychiatry) is proposed for the remote monitoring of psychiatric emergency patients. The emergency psychiatric states of patients are modeled as the states of the maximum-entropy Markov model (MEMM), in which sensor observations, psychiatric screening scores, and patients' histories are considered as the observations of MEMM. A modified Viterbi, a machine-learning algorithm, is used to generate the most probable psychiatric state sequence based on such observations; then, from the most likely psychiatric state sequence, the emergency psychiatric state is predicted through the proposed algorithm. The ambient EM-psychiatry model is implemented and the performance of the proposed prediction model is analyzed using the receiver operator characteristics curves, which demonstrates that the use of the EM-psychiatric screening questionnaire with biosensor observations enhances the prediction accuracy. Institute of Electrical and Electronics Engineers (IEEE) 2016 Article PeerReviewed Alam, M.G.R. and Haw, R. and Kim, S.S. and Azad, A.K. and Abedin, S.F. and Hong, C.S. (2016) EM-Psychiatry: An Ambient Intelligent System for Psychiatric Emergency. IEEE Transactions on Industrial Informatics, 12 (6). pp. 2321-2330. ISSN 1551-3203, DOI https://doi.org/10.1109/TII.2016.2610191 <https://doi.org/10.1109/TII.2016.2610191>. http://dx.doi.org/10.1109/TII.2016.2610191 doi:10.1109/TII.2016.2610191 |
| spellingShingle | T Technology (General) TA Engineering (General). Civil engineering (General) Alam, M.G.R. Haw, R. Kim, S.S. Azad, A.K. Abedin, S.F. Hong, C.S. EM-Psychiatry: An Ambient Intelligent System for Psychiatric Emergency |
| title | EM-Psychiatry: An Ambient Intelligent System for Psychiatric Emergency |
| title_full | EM-Psychiatry: An Ambient Intelligent System for Psychiatric Emergency |
| title_fullStr | EM-Psychiatry: An Ambient Intelligent System for Psychiatric Emergency |
| title_full_unstemmed | EM-Psychiatry: An Ambient Intelligent System for Psychiatric Emergency |
| title_short | EM-Psychiatry: An Ambient Intelligent System for Psychiatric Emergency |
| title_sort | em psychiatry an ambient intelligent system for psychiatric emergency |
| topic | T Technology (General) TA Engineering (General). Civil engineering (General) |
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