Employing multi-modal sensors for personalised smart home health monitoring.
As the prevalence of IoT sensor equipment in smart homes continues to rise, long term monitoring for personalised and more representative health tracking has become more accessible. The estimation of physiological health factors such as gait and heart rate can be captured using a range of diverse sensor equipment, while behavioural changes are now being monitored using simple binary sensors through activity classification and profiling. Combining both physiological and behavioural monitoring in fixed layout properties has already allowed us to effectively consider fall risk. However, expanding application of the system to new layouts and conditions requires consideration of differing retro fit home layouts and sensor configurations. A wider selection of sensors in varying configurations could potentially allow for the identification of other health conditions such as heart disease and stroke.
FORBES, G. 2019. Employing multi-modal sensors for personalised smart home health monitoring. In Kapetanakis, S. and Borck, H. (eds.) Proceedings of the 27th International conference on case-based reasoning workshop (ICCBR-WS19), co-located with the 27th International conference on case-based reasoning (ICCBR19), 8-12 September 2019, Otzenhausen, Germany. CEUR Workshop proceedings, 2567. Aachen: CEUR-WS [online], paper 19, pages 185-190. Available from: http://ceur-ws.org/Vol-2567/paper19.pdf
|Conference Name||27th International conference on case-based reasoning workshop (ICCBR-WS19), co- located with the 27th International conference 27th International conference on case-based reasoning (ICCBR19)|
|Start Date||Sep 8, 2019|
|End Date||Sep 12, 2019|
|Acceptance Date||Jul 23, 2019|
|Online Publication Date||Mar 4, 2020|
|Publication Date||Mar 4, 2020|
|Deposit Date||Apr 7, 2020|
|Publicly Available Date||Apr 7, 2020|
|Publisher||CEUR Workshop Proceedings|
|Keywords||Smart homes; Sensors; Time-series; Data; Human activity recognition; Long term health monitoring|
FORBES 2019 Employing multi-modal
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