Abstract
With the proliferation of the Internet of Things (IoT) and cloud computing technologies in various fields, remote health monitoring and fall detection are two vital applications that are expected to adopt these technologies. This is due to the fact that it not only provides efficient way for logging the patients’ health information, thus providing an electronic record for all the vital health signs that the patient is monitoring utilizing various medical IoT devices, but also it can be used to send an alert message to the healthcare personnel in case of detecting any abnormal behavior hence providing an immediate assistance. Fall detection is another important application of these technologies, where wearable sensors can be used to send an alert message to the healthcare personnel in case of detecting unpredicted fall. In this book chapter, the design and implementation of a simple and cost effective healthcare monitoring and fall detection system that utilizes of-the-shelf electronic components is provided. The system consists of a microcontroller, medical sensors and communication module that are used to collect the patients’ information and send it to the cloud for further processing and analysis. Furthermore, a fall detection system that utilizes wearable sensors is proposed where it can detect unpredicted fall. One unique feature in this system that it utilizes voice recognition technology to interact with the patient after detecting a fall, thus verifying if the patient needs an assistant or not, which in turn reduces the false alarms and improves the system accuracy.
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Acknowledgment
The authors would like to thank the German Jordanian University for funding this project through the Grant No. GP (13/2015).
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Khalifeh, A.F., Saleh, A., AL-Nuimat, M., Abou-Tair, D.e.D.I., Alnuman, N. (2019). Design and Implementation of Internet of Things and Cloud Based Platform for Remote Health Monitoring and Fall Detection. In: Fardoun, H., Hassan, A., de la Guía, M. (eds) New Technologies to Improve Patient Rehabilitation. REHAB 2016. Communications in Computer and Information Science, vol 1002. Springer, Cham. https://doi.org/10.1007/978-3-030-16785-1_7
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