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    Iot-based fall and ecg monitoring system: Wireless communication system based firebase realtime database

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    Date
    2019
    Author
    Al-Kababji, Ayman
    Shidqi, Lisan
    Boukhennoufa, Issam
    Amira, Abbes
    Bensaali, Faycal
    Gastli, Mohamed Sadok
    Jarouf, Abdulah
    Aboueata, Walid
    Abdalla, Alhusain
    ...show more authors ...show less authors
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    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.
    DOI/handle
    http://dx.doi.org/10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00267
    http://hdl.handle.net/10576/37821
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    • Electrical Engineering [‎2840‎ items ]

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