ECG Signal Reconstruction on the IoT-Gateway and Efficacy of Compressive Sensing Under Real-Time Constraints
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 ext...
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IEEE
2018-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8502753/ |
| _version_ | 1818428944826761216 |
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| author | Mohammed Al Disi Hamza Djelouat Christos Kotroni Elena Politis Abbes Amira Faycal Bensaali George Dimitrakopoulos Guillaume Alinier |
| author_facet | Mohammed Al Disi Hamza Djelouat Christos Kotroni Elena Politis Abbes Amira Faycal Bensaali George Dimitrakopoulos Guillaume Alinier |
| author_sort | Mohammed Al Disi |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-14T15:09:40Z |
| format | Article |
| id | doaj.art-3bc4129e605947bdabb25f3b623552bc |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T15:09:40Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-3bc4129e605947bdabb25f3b623552bc2022-12-21T22:56:36ZengIEEEIEEE Access2169-35362018-01-016691306914010.1109/ACCESS.2018.28776798502753ECG Signal Reconstruction on the IoT-Gateway and Efficacy of Compressive Sensing Under Real-Time ConstraintsMohammed Al Disi0https://orcid.org/0000-0001-5095-4070Hamza Djelouat1Christos Kotroni2Elena Politis3Abbes Amira4Faycal Bensaali5George Dimitrakopoulos6Guillaume Alinier7Department of Computer Science and Engineering, College of Engineering, Qatar University, Doha, QatarDepartment of Computer Science and Engineering, College of Engineering, Qatar University, Doha, QatarDepartment of Informatics and Telematics, Harokopio University of Athens, Athens, GreeceDepartment of Informatics and Telematics, Harokopio University of Athens, Athens, GreeceDepartment of Computer Science and Engineering, College of Engineering, Qatar University, Doha, QatarDepartment of Electrical Engineering, College of Engineering, Qatar University, Doha, QatarDepartment of Informatics and Telematics, Harokopio University of Athens, Athens, GreeceAmbulance Service, Hamad Medical Corporation, Doha, QatarRemote 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.https://ieeexplore.ieee.org/document/8502753/Connected healthcompressed sensingenergy efficiencyheterogeneous multicore platformsinternet of thingsmobile real-time health monitoring |
| spellingShingle | Mohammed Al Disi Hamza Djelouat Christos Kotroni Elena Politis Abbes Amira Faycal Bensaali George Dimitrakopoulos Guillaume Alinier ECG Signal Reconstruction on the IoT-Gateway and Efficacy of Compressive Sensing Under Real-Time Constraints IEEE Access Connected health compressed sensing energy efficiency heterogeneous multicore platforms internet of things mobile real-time health monitoring |
| title | ECG Signal Reconstruction on the IoT-Gateway and Efficacy of Compressive Sensing Under Real-Time Constraints |
| title_full | ECG Signal Reconstruction on the IoT-Gateway and Efficacy of Compressive Sensing Under Real-Time Constraints |
| title_fullStr | ECG Signal Reconstruction on the IoT-Gateway and Efficacy of Compressive Sensing Under Real-Time Constraints |
| title_full_unstemmed | ECG Signal Reconstruction on the IoT-Gateway and Efficacy of Compressive Sensing Under Real-Time Constraints |
| title_short | ECG Signal Reconstruction on the IoT-Gateway and Efficacy of Compressive Sensing Under Real-Time Constraints |
| title_sort | ecg signal reconstruction on the iot gateway and efficacy of compressive sensing under real time constraints |
| topic | Connected health compressed sensing energy efficiency heterogeneous multicore platforms internet of things mobile real-time health monitoring |
| url | https://ieeexplore.ieee.org/document/8502753/ |
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