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| Title | Iot-Based Fall And Ecg Monitoring System: Wireless Communication System Based Firebase Realtime Database |
|---|---|
| ID_Doc | 33969 |
| Authors | Al-Kababji A.; Shidqi L.; Boukhennoufa I.; Amira A.; Bensaali F.; Gastli M.S.; Jarouf A.; Aboueata W.; Abdalla A. |
| Year | 2019 |
| Published | Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019 |
| DOI | http://dx.doi.org/10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00267 |
| Abstract | Monitoring elderlies living alone has been a rising issue that caregivers are interested in solving since many elderlies are at risk of experiencing a fall. In the absence of urgent help, serious consequences may occur. This paper presents a complete communication system to monitor elderlies by checking their Electrocardiogram (ECG) and accelerometer data through a cloud-based server anytime on a mobile application ensuring that they are unharmed. This has been implemented by having a Multi-core Processing Unit (MPU), acting as a gateway, at the elderly's side monitoring signals coming from a wearable sensing device. It will classify ECG and accelerometer data using Machine Learning algorithms, stream the data upon request, alert caregivers through a mobile application and store the data on the database for further analysis in case of a fall. Fall detection had an accuracy of 95% using Extended Nearest Neighbor (E-NN) learning algorithm. © 2019 IEEE. |
| Author Keywords | Ecg monitoring; Fall detection; Internet of things (iot); Mobile application; Multi-core processing unit (mpu); Wearable sensing device |
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