Outdoor Alzheimer’s Patients Tracking Using an IoT System and a Kalman Filter Estimator
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Computer Science Applications
Link
https://link.springer.com/content/pdf/10.1007/s11277-020-07713-4.pdf
Reference33 articles.
1. Alzheimer’s, A. (2017). 2017 alzheimer’s disease facts and figures. Alzheimer’s & Dementia, 13(4), 325–373. https://doi.org/10.1016/j.jalz.2017.02.001.
2. Podhorna, J., Winter, N., Zoebelein, H., et al. (2020). Alzheimer’s treatment: Real-world physician behavior across countries. Advances in Therapy, 37, 894–905. https://doi.org/10.1007/s12325-019-01213-z.
3. Raad, M. W., Sheltami, T., & Shakshuki, E. (2015). Ubiquitous tele-health system for elderly patients with alzheimer’s. Procedia Computer Science, 52, 685–689. https://doi.org/10.1016/j.procs.2015.05.075.
4. Pratiarso, A., Imanuddin, A. I., Yuliana, M., et al. (2017). Implementation of Kalman Filter method for tracking position of Alzheimer’s patients. In International conference on smart cities, automation & intelligent computing systems (ICON-SONICS) (pp. 135–140). IEEE. https://doi.org/10.1109/icon-sonics.2017.8267836.
5. Ferreira, R., Gaspar, J., Sebastião, P., et al. (2020). Effective GPS jamming techniques for UAVs using low-cost SDR platforms. Wireless Personal Communications. https://doi.org/10.1007/s11277-020-07212-6.
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