An IoT-Based Framework for Elderly Remote Monitoring
| Autor: | Faycal Bensaali, Abbes Amira, Issam Boukhennoufa, Dimosthenis Anagnostopoulos, Elena Politis, George Dimitrakopoulos, Chris Kotronis, Maria Nikolaidou |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Multi-core processor
Edge device business.industry Firmware Computer science 010401 analytical chemistry 0206 medical engineering Real-time computing Internet of Things Latency (audio) compressive sensing Cloud computing 02 engineering and technology Energy consumption computer.software_genre 020601 biomedical engineering 01 natural sciences 0104 chemical sciences Secure communication Default gateway Heterogeneous Multicore Platforms business computer Remote Elderly Monitoring |
| Zdroj: | DSD |
| Popis: | This Paper presents an Internet of Things (IoT) based framework to monitor ECG for biometric recognition and acceleration for fall detection. To this end, an-IoT based Remote Elderly Monitoring System (REMS) platform is described. REMS consists of a Shimmer3TM device transmitting physiological signal wirelessly to a nearby gateway which routes the data to a remote IoT-platform, able to accommodate dynamically changing configurations. The Shimmer firmware has been modified to send data based on the compressive sensing theory in order to ameliorate energy consumption in addition of real data, and the analysis and processing are done locally on a heterogeneous multicore edge device in order to solve latency issues related to cloud reliance. Subsequently the framework has been designed to handle the different parameter settings and multiple scenarios in a user-friendly way. Furthermore, it allows the user to monitor physiological data and acquire some feedback related to their analysis. Depending on a scenario (energy save, secure communication) the system can be configured manually or automatically to monitor ECG or acceleration data and displays them, it can also identify the subject based on ECG recognition and detect fall if it occurs. - 2019 IEEE. This paper was made possible by National Priorities Research Program (NPRP) grant No. 9-114-2-055 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. Scopus |
| Databáze: | OpenAIRE |
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