Human body communications (HBC) has recently emerged as an innovative alternative to the current radio frequency communications for realizing wireless body area networks (WBAN) using the human body as a transmission channel without wired or wireless connections. This study 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 bio-signal 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 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 inter-symbol interference effects caused by the delay spreads of the body channels were explored to verify communication reliability in terms of the transmitter structures adopting digital transmission, sorts of human body channels, data rates, and operating frequencies.

Human body communications (HBCs), employing the human body as a signal transmission medium, can provide efficient and intuitive methods to form a network in the body. This article presents a comprehensive study for a highly reliable HBC system, including body channel modeling, transceiver design, and performance evaluation through implementation, in consideration of practical sensor network environments for wearable and implantable devices applicable to healthcare and biosignal acquisition. Body channel characteristics based on capacitive couplings, such as root mean square delay spread and mean path gain (MPG), were explored by measuring the body impulse responses under 12 experimental conditions, determined by the variation in body postures and device locations between the wrist and positions assumed under the scalp through a customized experimental setup with micropig-derived biomembranes (MBMs) used for wrapping the devices to emulate an implantable environment. The proposed transceiver design for digital transmission, including a preamble structure and signal modulation method supporting a maximum data rate of 1 Mb/s, was verified through the performance evaluations conducted for examining the frame detection probability and bit error rate (BER) in the body channel model at multiple operating frequencies of 32, 42, and 64 MHz. The proposed system reliability was demonstrated by the achievement of a BER of below ${4.7\,\times \, }{10}^{-8}$ through battery-powered implemented devices with dimensions of ${30\times 30 }\,\,{\text {mm}}^{2}$ , comprising a digital signal processing module (DSPM) for signal generation and detection processes, and an analog front-end module (AFEM) for recovering the received signal from signal deterioration by severe path loss and time-dispersive effect in the body channel.

For a small shielding enclosure, its shielding effectiveness (SE) is measured using the frequency-domain method that is defined in the IEEE 299.1 standard. The frequency-domain method, however, has a reduced dynamic range so that a high level of SE is measured inaccurately. Such dynamic range reduction in SE measurement is caused by cable coupling of transmitting signal during measurement. This article proposes a time-domain method that measures even a high level of SE accurately. Unlike the frequency-domain method, the proposed method does not experience dynamic range reduction. Instead of a continuous wave signal, a pulse signal is transmitted in a nested reverberation chamber for SE measurement. After the pulse transmission, a receiving signal is measured and sampled for the SE calculation. The receiving signal is sampled only after the transmitting pulse signal dissipates completely in the nested reverberation chamber. As a result, the cable coupling and dynamic range reduction do not occur in proposed time-domain method. The proposed time-domain method extends a dynamic range over 30 dB in comparison with the frequency-domain method. The proposed method can measure a high level of SE over 120 dB accurately without being affected by the cable coupling.