Abstract
Human body communications (HBCs) have recently emerged as an innovative alternative to the current radio frequency communications for realizing wireless body area networks (WBANs) using the human body as a transmission channel without wired or wireless connections. This article addresses the provision of reliable modeling of the human body as a passage of the electric signal delivery based on the impulse response measurement through the proposal of a measurement setup and signal processing techniques applicable to wearable devices for healthcare and biosignal acquisition. In the experiments, customized impulse signals were applied to the body using battery-powered devices isolated to the earth ground for the operating environments of wearable devices. The impulse responses passed through the body were measured by considering 52 measurement conditions determined by the device locations from the head to ankle and the body postures. Body channel transfer functions (BCTFs) for the respective conditions were derived by an adaptive filter approach using an iterative algorithm to minimize the mean squared error between the measured and modeled impulse responses. The channel analysis parameters, such as mean path loss, root-mean-square delay spread, and mean and maximum excess delays, were analyzed based on the measured body impulse responses. In addition, the practical bit-error-rate performance for HBC based on the BCTFs reproducing intersymbol interference effects caused by the delay spreads of the body channels was explored to verify communication reliability in terms of the transmitter structures adopting digital transmission, sorts of human body channels, data rates, and operating frequencies.
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