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Cardoso, R., Postolache, O. & Coutinho, C. (2022). Remote health monitoring system for the elderly based on mobile computing and IoT. In Proceedings of the 3rd International Symposium on Sensing and Instrumentation in 5G and IoT Era (ISSI2022). (pp. 132-137). Shanghai, China: IEEE.

R. Cardoso et al.,  "Remote health monitoring system for the elderly based on mobile computing and IoT", in Proc. of the 3rd Int. Symp. on Sensing and Instrumentation in 5G and IoT Era (ISSI2022), Shanghai, China, IEEE, 2022, pp. 132-137

@inproceedings{cardoso2022_1734891453601,
	author = "Cardoso, R. and Postolache, O. and Coutinho, C.",
	title = "Remote health monitoring system for the elderly based on mobile computing and IoT",
	booktitle = "Proceedings of the 3rd International Symposium on Sensing and Instrumentation in 5G and IoT Era (ISSI2022)",
	year = "2022",
	editor = "",
	volume = "",
	number = "",
	series = "",
	doi = "10.1109/ISSI55442.2022.9963430",
	pages = "132-137",
	publisher = "IEEE",
	address = "Shanghai, China",
	organization = "IEEE",
	url = "https://ieeexplore.ieee.org/xpl/conhome/9962816/proceeding"
}

TY  - CPAPER
TI  - Remote health monitoring system for the elderly based on mobile computing and IoT
T2  - Proceedings of the 3rd International Symposium on Sensing and Instrumentation in 5G and IoT Era (ISSI2022)
AU  - Cardoso, R.
AU  - Postolache, O.
AU  - Coutinho, C.
PY  - 2022
SP  - 132-137
DO  - 10.1109/ISSI55442.2022.9963430
CY  - Shanghai, China
UR  - https://ieeexplore.ieee.org/xpl/conhome/9962816/proceeding
AB  - Due to the increasing technological innovation over the last decades, the average life expectancy of a human being has been increasing exponentially. Although this is an excellent step forward for humanity, it has led older population to being more prone to illness, making them more vulnerable to accidents such as falls. In this article a study is made on the existing literature in non-intrusive remote health monitoring systems, towards the design and implementation of an IoT system capable of identifying fall situations and monitor cardiac data. A Systematic Literature Review (SLR) method was considered in this work, focused on reviewing the existing literature on remote health monitoring systems, having fall detection algorithms, based in IoT. The Design Science Research (DSR) methodology was used to seek to enhance technology and science knowledge about this paper's topic, through the creation of an innovative artifact.The system includes a smart watch (Lily-Go T-Watch-2020 V2), programmable in C under Arduino IDE to detect falls and a photoplethysmography monitoring unit (PPG) based on a Onyx 9560 Bluetooth oximeter, capable of measuring the user's blood oxygen percentage (SpO2) and heart rate, in real time. It also provides remote monitoring through a user-friendly website to visualize live data about the status of the user. The system was tested in volunteers to show the effectiveness of remote health monitoring systems for the elderly population.
ER  -