ECG Signal Reconstruction on the IoT-Gateway and Efficacy of Compressive Sensing Under Real-time Constraints

Mohammed Al Disi, Hamza Djelouat, Christos Kotronis, Elena Politis, Abbes Amira, Faycal Bensaali, George Dimitrakopoulos, Guillaume Alinier

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)
36 Downloads (Pure)


Remote health monitoring is becoming indispensable, though, Internet of Things (IoTs)-based solutions have many implementation challenges, including energy consumption at the sensing node, and delay and instability due to cloud computing. Compressive sensing (CS) has been explored as a method to extend the battery lifetime of medical wearable devices. However, it is usually associated with computational complexity at the decoding end, increasing the latency of the system. Meanwhile, mobile processors are becoming computationally stronger and more efficient. Heterogeneous multicore platforms (HMPs) offer a local processing solution that can alleviate the limitations of remote signal processing. This paper demonstrates the real-time performance of compressed ECG reconstruction on ARM's big.LITTLE HMP and the advantages they provide as the primary processing unit of the IoT architecture. It also investigates the efficacy of CS in minimizing power consumption of a wearable device under real-time and hardware constraints. Results show that both the orthogonal matching pursuit and subspace pursuit reconstruction algorithms can be executed on the platform in real time and yield optimum performance on a single A15 core at minimum frequency. The CS extends the battery life of wearable medical devices up to 15.4% considering ECGs suitable for wellness applications and up to 6.6% for clinical grade ECGs. Energy consumption at the gateway is largely due to an active internet connection; hence, processing the signals locally both mitigates system's latency and improves gateway's battery life. Many remote health solutions can benefit from an architecture centered around the use of HMPs, a step toward better remote health monitoring systems.

Original languageEnglish
Article number8502753
Pages (from-to)69130-69140
Number of pages11
JournalIEEE Access
Publication statusPublished - 23 Oct 2018


  • Biomedical monitoring
  • compressed sensing
  • Connected health
  • Electrocardiography
  • Energy consumption
  • energy efficiency
  • heterogeneous multicore platforms
  • internet of things
  • Logic gates
  • mobile real-time health monitoring
  • Monitoring
  • multicore processing
  • Real-time systems
  • remote monitoring
  • Sensors
  • wearable sensors


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