Knowledge Discovery from Activity Monitoring to Support Independent Living of People with Early Dementia

Hoda Nikamalfard, Huiru Zheng, Haiying Wang, Paul Jeffers, Maurice Mulvenna, PJ McCullagh, Mathieu Suzanne, Jonathan Wallace, Juan Carlos Augusto, William Carswell, Barbara Taylor, Kevin McSorley

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Altered activity patterns are often the general symptoms experienced by people with dementia. The quantity and quality of patient’s daily activities such as their sleeping may be a reflection of their dementia condition and affect their quality of life. Monitoring patient’s activity patterns over different periods of time may help healthcare professionals with determining the patient’s cognitive impairment stage. In this research, we describe an activity pattern detection and visualization system developed to support the monitoring and assessment of activity patterns for people diagnosed with dementia, at the early stages of the disease. Analysis shows that rich information embedded in sensory data can provide useful knowledge for understanding patients’ activity patterns, detect unusual events and may also be useful for examining cognitive status.

Conference

Conferencethe IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI 2012) in conjunction with the 8th International Symposium on Medical Devices and Biosensors and the 7th International Symposium on Biomedical and Health Engineering
Period1/01/12 → …

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Independent Living
Dementia
Physiologic Monitoring
Quality of Life
Delivery of Health Care
Research

Cite this

Nikamalfard, Hoda ; Zheng, Huiru ; Wang, Haiying ; Jeffers, Paul ; Mulvenna, Maurice ; McCullagh, PJ ; Suzanne, Mathieu ; Wallace, Jonathan ; Augusto, Juan Carlos ; Carswell, William ; Taylor, Barbara ; McSorley, Kevin. / Knowledge Discovery from Activity Monitoring to Support Independent Living of People with Early Dementia. Unknown Host Publication. 2012. pp. 910-913
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title = "Knowledge Discovery from Activity Monitoring to Support Independent Living of People with Early Dementia",
abstract = "Altered activity patterns are often the general symptoms experienced by people with dementia. The quantity and quality of patient’s daily activities such as their sleeping may be a reflection of their dementia condition and affect their quality of life. Monitoring patient’s activity patterns over different periods of time may help healthcare professionals with determining the patient’s cognitive impairment stage. In this research, we describe an activity pattern detection and visualization system developed to support the monitoring and assessment of activity patterns for people diagnosed with dementia, at the early stages of the disease. Analysis shows that rich information embedded in sensory data can provide useful knowledge for understanding patients’ activity patterns, detect unusual events and may also be useful for examining cognitive status.",
author = "Hoda Nikamalfard and Huiru Zheng and Haiying Wang and Paul Jeffers and Maurice Mulvenna and PJ McCullagh and Mathieu Suzanne and Jonathan Wallace and Augusto, {Juan Carlos} and William Carswell and Barbara Taylor and Kevin McSorley",
year = "2012",
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language = "English",
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Nikamalfard, H, Zheng, H, Wang, H, Jeffers, P, Mulvenna, M, McCullagh, PJ, Suzanne, M, Wallace, J, Augusto, JC, Carswell, W, Taylor, B & McSorley, K 2012, Knowledge Discovery from Activity Monitoring to Support Independent Living of People with Early Dementia. in Unknown Host Publication. pp. 910-913, the IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI 2012) in conjunction with the 8th International Symposium on Medical Devices and Biosensors and the 7th International Symposium on Biomedical and Health Engineering, 1/01/12.

Knowledge Discovery from Activity Monitoring to Support Independent Living of People with Early Dementia. / Nikamalfard, Hoda; Zheng, Huiru; Wang, Haiying; Jeffers, Paul; Mulvenna, Maurice; McCullagh, PJ; Suzanne, Mathieu; Wallace, Jonathan; Augusto, Juan Carlos; Carswell, William; Taylor, Barbara; McSorley, Kevin.

Unknown Host Publication. 2012. p. 910-913.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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T1 - Knowledge Discovery from Activity Monitoring to Support Independent Living of People with Early Dementia

AU - Nikamalfard, Hoda

AU - Zheng, Huiru

AU - Wang, Haiying

AU - Jeffers, Paul

AU - Mulvenna, Maurice

AU - McCullagh, PJ

AU - Suzanne, Mathieu

AU - Wallace, Jonathan

AU - Augusto, Juan Carlos

AU - Carswell, William

AU - Taylor, Barbara

AU - McSorley, Kevin

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N2 - Altered activity patterns are often the general symptoms experienced by people with dementia. The quantity and quality of patient’s daily activities such as their sleeping may be a reflection of their dementia condition and affect their quality of life. Monitoring patient’s activity patterns over different periods of time may help healthcare professionals with determining the patient’s cognitive impairment stage. In this research, we describe an activity pattern detection and visualization system developed to support the monitoring and assessment of activity patterns for people diagnosed with dementia, at the early stages of the disease. Analysis shows that rich information embedded in sensory data can provide useful knowledge for understanding patients’ activity patterns, detect unusual events and may also be useful for examining cognitive status.

AB - Altered activity patterns are often the general symptoms experienced by people with dementia. The quantity and quality of patient’s daily activities such as their sleeping may be a reflection of their dementia condition and affect their quality of life. Monitoring patient’s activity patterns over different periods of time may help healthcare professionals with determining the patient’s cognitive impairment stage. In this research, we describe an activity pattern detection and visualization system developed to support the monitoring and assessment of activity patterns for people diagnosed with dementia, at the early stages of the disease. Analysis shows that rich information embedded in sensory data can provide useful knowledge for understanding patients’ activity patterns, detect unusual events and may also be useful for examining cognitive status.

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