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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

Simulation structure for QoS evaluation.
© Copyright Policy - open-access
Related In: Results  -  Collection


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fig6: Simulation structure for QoS evaluation.

Mentions: We used the MIT-BIH [31] arrhythmia database, which contains two-channel ambulatory ECG recordings obtained from 47 subjects studied by the BIH Arrhythmia Laboratory. The recordings were digitized at 360 samples per second for each channel, with 11-bit resolution; thus, the data-rate μs of each channel is 3960 b/s. Because we used two-channel ambulatory ECG recordings, data packets from both channels are multiplexed alternately before transmission, as shown in Figure 6(a), and the resulting total data-rate μecg from the ECG sensor is 7920 b/s. We selected the data-stream 100.dat from the database. In this record, the upper signal is a modified limb II (MLII) lead and the lower signal is a modified V5 lead, which is one of the precordial leads.


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

Kang K - ScientificWorldJournal (2014)

Simulation structure for QoS evaluation.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

fig6: Simulation structure for QoS evaluation.
Mentions: We used the MIT-BIH [31] arrhythmia database, which contains two-channel ambulatory ECG recordings obtained from 47 subjects studied by the BIH Arrhythmia Laboratory. The recordings were digitized at 360 samples per second for each channel, with 11-bit resolution; thus, the data-rate μs of each channel is 3960 b/s. Because we used two-channel ambulatory ECG recordings, data packets from both channels are multiplexed alternately before transmission, as shown in Figure 6(a), and the resulting total data-rate μecg from the ECG sensor is 7920 b/s. We selected the data-stream 100.dat from the database. In this record, the upper signal is a modified limb II (MLII) lead and the lower signal is a modified V5 lead, which is one of the precordial leads.

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