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An adaptive framework for real-time ECG transmission in mobile environments.

Kang K - ScientificWorldJournal (2014)

Bottom Line: According to this observation, we have devised a simple and efficient real-time scheduling algorithm based on the earliest deadline first (EDF) policy, which decides the order of transmitting or retransmitting packets that contain ECG data at any given time for the delivery of scalable ECG data over a lossy channel.The algorithm takes into account the differing priorities of packets in each layer, which prevents the perceived quality of the reconstructed ECG signal from degrading abruptly as channel conditions worsen, while using the available bandwidth efficiently.Extensive simulations demonstrate this improvement in perceived quality.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Engineering, Hanyang University, Ansan 426-791, Republic of Korea.

ABSTRACT
Wireless electrocardiogram (ECG) monitoring involves the measurement of ECG signals and their timely transmission over wireless networks to remote healthcare professionals. However, fluctuations in wireless channel conditions pose quality-of-service challenges for real-time ECG monitoring services in a mobile environment. We present an adaptive framework for layered coding and transmission of ECG data that can cope with a time-varying wireless channel. The ECG is segmented into layers with differing importance with respect to the quality of the reconstructed signal. According to this observation, we have devised a simple and efficient real-time scheduling algorithm based on the earliest deadline first (EDF) policy, which decides the order of transmitting or retransmitting packets that contain ECG data at any given time for the delivery of scalable ECG data over a lossy channel. The algorithm takes into account the differing priorities of packets in each layer, which prevents the perceived quality of the reconstructed ECG signal from degrading abruptly as channel conditions worsen, while using the available bandwidth efficiently. Extensive simulations demonstrate this improvement in perceived quality.

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Related in: MedlinePlus

Results for MSEs when a patient moves at around 5 km/h.
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Related In: Results  -  Collection


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fig9: Results for MSEs when a patient moves at around 5 km/h.

Mentions: Figures 8 and 9 show the performance of our framework in comparison with that of the conventional transmission framework (CTF), which serially packetizes consecutive symbols in order (which is denoted by serial representation (SR) in the figures) and employs first-in-first-out (FIFO) scheduler with priority-unaware error control based on ARQ. We also applied the RI method to the CTF to enable its direct comparison with our framework. The results are shown in terms of MSE for PER values ranging from 0 to 0.1. In general, MSE is relatively high in the case of slow-moving patients, where packet errors tend to occur in bursts separated by relatively long error-free intervals. This has an unfavorable effect on error recovery. It is also plausible that the MSE value increases with the PER.


An adaptive framework for real-time ECG transmission in mobile environments.

Kang K - ScientificWorldJournal (2014)

Results for MSEs when a patient moves at around 5 km/h.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4109261&req=5

fig9: Results for MSEs when a patient moves at around 5 km/h.
Mentions: Figures 8 and 9 show the performance of our framework in comparison with that of the conventional transmission framework (CTF), which serially packetizes consecutive symbols in order (which is denoted by serial representation (SR) in the figures) and employs first-in-first-out (FIFO) scheduler with priority-unaware error control based on ARQ. We also applied the RI method to the CTF to enable its direct comparison with our framework. The results are shown in terms of MSE for PER values ranging from 0 to 0.1. In general, MSE is relatively high in the case of slow-moving patients, where packet errors tend to occur in bursts separated by relatively long error-free intervals. This has an unfavorable effect on error recovery. It is also plausible that the MSE value increases with the PER.

Bottom Line: According to this observation, we have devised a simple and efficient real-time scheduling algorithm based on the earliest deadline first (EDF) policy, which decides the order of transmitting or retransmitting packets that contain ECG data at any given time for the delivery of scalable ECG data over a lossy channel.The algorithm takes into account the differing priorities of packets in each layer, which prevents the perceived quality of the reconstructed ECG signal from degrading abruptly as channel conditions worsen, while using the available bandwidth efficiently.Extensive simulations demonstrate this improvement in perceived quality.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Engineering, Hanyang University, Ansan 426-791, Republic of Korea.

ABSTRACT
Wireless electrocardiogram (ECG) monitoring involves the measurement of ECG signals and their timely transmission over wireless networks to remote healthcare professionals. However, fluctuations in wireless channel conditions pose quality-of-service challenges for real-time ECG monitoring services in a mobile environment. We present an adaptive framework for layered coding and transmission of ECG data that can cope with a time-varying wireless channel. The ECG is segmented into layers with differing importance with respect to the quality of the reconstructed signal. According to this observation, we have devised a simple and efficient real-time scheduling algorithm based on the earliest deadline first (EDF) policy, which decides the order of transmitting or retransmitting packets that contain ECG data at any given time for the delivery of scalable ECG data over a lossy channel. The algorithm takes into account the differing priorities of packets in each layer, which prevents the perceived quality of the reconstructed ECG signal from degrading abruptly as channel conditions worsen, while using the available bandwidth efficiently. Extensive simulations demonstrate this improvement in perceived quality.

Show MeSH
Related in: MedlinePlus