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|Title: ||Developing a sensor based homecare system: The role of bluetooth low-energy in activity monitoring|
|Authors: ||Power, Luke|
Jackson, Lisa M.
Dunnett, Sarah J.
Indoor positioning system
|Issue Date: ||2018|
|Publisher: ||© ScitePress|
|Citation: ||POWER, L., JACKSON, L.M. and DUNNETT, S.J., 2018. Developing a sensor based homecare system: The role of bluetooth low-energy in activity monitoring. IN: Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, Funchal, Madeira, Portugal, 19-21st January, pp.598-606.|
|Abstract: ||Home healthcare systems have become a focus of research due to the shifting care requirements of the elderly. Malnourishment, independence and activity are becoming vital metrics when monitoring in patient’s illness. Monitoring devices described in research however express issues in the consistent remote capture of these metrics. This work presents the role of Bluetooth Low-Energy Beacons (BLE) in community based healthcare by examining how passive activity monitoring can assist patients coping with independence and disease management within their homes as an Indoor Proximity System (IPS). BLE sensors will be placed on the patient, in their home and on objects of interest (OOI) such as water bottles, kettles and microwaves. Research described in this paper will focus on accuracy of BLE beacons as an IPS for lifestyle monitoring and its application to intelligent healthcare. This is achieved by creating a model of patient care requirements structured using activities of daily living (ADL) which is evaluated using patient activity pattern recognition in captured sensor data. Pattern analysis uses the changing distance values between BLE sensors to determine movement, motion and location which contribute to the activity, sensor based care model. Results support efficacy when using BLE beacons as an IPS with patient activity patterns becoming observable through monitoring with a consistent ability to distinguish interactions in activity patterns captured. Future experiments will focus on analysing captured sensor metrics to determine care outcomes.|
|Description: ||This is a conference paper.|
|Publisher Link: ||https://doi.org/10.5220/0006722305980606|
|Appears in Collections:||Conference Papers and Presentations (Aeronautical and Automotive Engineering)|
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