Abstract
As the age profile of many societies continues to increase, supporting health, both mental and physical, is of increasing importance if independent living is to be maintained. Sensing and, ultimately, recognising activities of daily living has been perceived as a prerequisite for detecting tasks that people avoid or find increasingly difficult to perform, as well as being indicators of certain illnesses. To date, extensive research efforts have been made in activity monitoring, recognition and assistance in indoor scenarios, frequently through smart home initiatives. Moreover, certain behaviours and activities may indicate certain disease especially for elderly people, such as sleep disorder. Thus this paper advocates a need for platforms that enable activity monitoring, in particularly, this sleep disorder, in home environment, thereby enabling the construction of more complex yet realistic activity models and behaviours patterns.
This work is supported by NanTong Science and Technology Bureau under grant JC2018132 and National Natural Science Foundation of China under grant 62002179 within Nantong University China.
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This work is supported by NanTong Science and Technology Bureau under grant JC2018132 and National Natural Science Foundation of China under grant 62002179 within Nantong University China.
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Zhang, L., Chen, S., Jin, X., Wan, J. (2021). Smart Home Based Sleep Disorder Recognition for Ambient Assisted Living. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2021. Lecture Notes in Computer Science(), vol 12737. Springer, Cham. https://doi.org/10.1007/978-3-030-78612-0_37
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