-Knowledge of the propagation media is a key step toward a successful transceiver design. Such information is typically gathered by conducting physical experiments, measuring and processing the corresponding data to obtain channel characteristics. In case of medical implants, this could be extremely difficult, if not impossible. In this paper, an immersive visualization environment is presented, which is used as a scientific instrument that gives us the ability to observe RF propagation from medical implants inside a human body. This virtual environment allows for more natural interaction between experts with different backgrounds, such as engineering and medical sciences. Here, we show how this platform has been used to determine a statistical path loss model for medical implant communication systems.
Direct-sequence spread-spectrum signals collected from the TREX04 experiment are analyzed to determine the bit-error-rate (BER) as a function of the input signal-to-noise ratio (SNR) for a single receiver. A total of 1160 packets of data are generated by adding ambient noise data collected at sea to the signal data (in postprocessing) to create signals with different input-SNR, some as low as -15 dB. Two methods are analyzed in detail, both using a time-updated channel impulse-response estimate as a (matched) filter to mitigate the multipath-induced interferences. The first method requires an independent estimate of the time-varying channel impulse-response function; the second method uses the channel impulse-response estimated from the previous symbol as the matched filter. The first method yields an average BER <10(-2) for input-SNR as low as -12 dB and the second method yields a similar performance for input-SNR as low as -8 dB. The measured BERs are modeled using the measured signal amplitude fluctuation statistics and processing gain obtained by de-spreading the received signal with the transmitted code sequence. Performance losses caused by imprecise symbol synchronization at low input-SNR, uncertainty in channel estimation, and signal fading are quantitatively modeled and compared with data.
Information regarding the propagation media is typically gathered by conducting physical experiments, measuring and processing the corresponding data to obtain channel characteristics. When this propagation media is human body, for example in case of medical implants, then this approach might not be practical. In this paper, an immersive visualization environment is presented, which is used as a scientific instrument that gives us the ability to observe RF propagation from medical implants inside a human body. This virtual environment allows for more natural interaction between experts with different backgrounds, such as engineering and medical sciences. Here, we show how this platform has been used to determine channel models for medical implant communication systems.
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