Statistical performance evaluation of ECG transmission using wireless networks.

Area of Science:

• Biomedical Engineering
• Wireless Communications
• Signal Processing

Background:

• Biomedical signal transmission over wireless networks is crucial for remote patient monitoring.
• Ensuring the diagnostic quality of transmitted signals like electrocardiograms (ECG) is vital.

Purpose of the Study:

• To simulate and analyze the transmission of biomedical signals (ECG) over wireless networks.
• To investigate the impact of channel and network impairments on ECG signal diagnosability.

Main Methods:

• Simulated transmission of ECG signals using two protocols: IEEE 802.15.4 (ZigBee) and IEEE 802.11b.
• Evaluated impairments including signal-to-noise ratio (SNR), path loss exponent, path delay, and packet loss probability.
• Assessed signal quality using higher-order statistics (kurtosis, Negative Entropy) and common metrics (PRD, RMS, Cross Correlation).

Main Results:

• Channel impairments like SNR and path loss significantly affect ECG signal diagnosability.
• Network impairments, particularly packet loss probability, degrade the diagnostic quality of the received ECG signal.
• Both ZigBee and Wi-Fi protocols showed varying sensitivities to different types of impairments.

Conclusions:

• Wireless transmission of ECG signals is feasible but susceptible to degradation from channel and network impairments.
• Careful consideration of network protocols and impairment mitigation strategies is necessary for reliable remote ECG monitoring.
• Higher-order statistics provide valuable insights into signal distortion beyond traditional metrics.