br Implement methods of IBC Sensor

Implement methods of IBC Sensor used for signal detection is very important for achieving reliable signal transmission based on human body. Recently, two kinds of sensors, electrical SB431542 manufacturer and EO sensor, have been chosen. However, since the electrical sensor has comparatively low input impedance and is easy to be interfered by electromagnetic noise, the typical signal transmission distance based on this kind of sensor is only approximately 30 cm and the corresponding signal transmission rate is limited in 40 kbps [3]. The influence of then electrical noise can be greatly decreased due to then extremely high input impedance of electro-optical sensor. Moreover, the ground electrode of the EO sensor is electrically isolated from the electronic circuits, which eliminates the influence of the floating ground potential [6]. As a result, both the noise and the distortion of the receiving signal are decreased greatly, thereby high signal transmission rate can be achieved [3]. Therefore, EO sensor is believed as a suitable sensor for detecting signal transmitting within human body. On the other hand, the previous research on the electro-optical modulation method used in IBC mainly focused on the sensor based on a bulk electro-optical modulator [3,6], which have several unsolved issues. In this paper, an IBC system based on Mach–Zehnder electro-optical sensor is introduced. Compared with the IBC based on a bulk electro-optical sensor, the proposed method has good temperature characteristic. Moreover, it can also help to decrease the size and power consumption of the IBC system.
Conclusion The modeling, simulation and implement of intra-body communication are reviewed in this paper. Firstly, the transfer function of the galvanic coupling IBC was deduced, while both the in vivo measurements and the corresponding mathematical simulations based on the proposed transfer function were carried out along different signal transmission paths. The experiment results show that the signal attenuations of simulation results coincided with the corresponding in vivo measurement results. Secondly, a finite-element method for modeling the whole human body is introduced, while both the simulations of the galvanic coupling IBC based on the whole human body and the corresponding in vivo measurements have been carried out, and some important conclusions have been achieved. Thirdly, the implement methods of the intra-body communication as well as a novel IBC system based on Mach–Zehnder EO modulator have been discussed. We demonstrated that, compared with the IBC based on an electrical sensor, the electrostatic coupling IBC based on Mach–Zehnder electro-optical modulation has a steady frequency response. Moreover, compared with the IBC based on a bulk electro-optical sensor, the IBC based on Mach–Zehnder modulation has good temperature characteristic.
From nature swarm to swarm intelligence
Definition and features
Modeling swarm robotics
Entity projects and simulations
Cooperative algorithms
Conclusions
Introduction As the core of the signal processing community, the signal processing technology plays an important role in modern society. Almost all of the breakthroughs in signal processing were taken with the emergence of new signal processing tools and technologies [1]. These breakthroughs include various advances and extensions from old techniques to new techniques. For example, the signal processing techniques have moved from single-rate to multirate processing, from time-invariant to adaptive processing [2], from frequency-domain (the traditional Fourier transform domain) to time-frequency analysis [3] or the fractional Fourier domain analysis [4], and from linear to non-linear signal processing. The recent developments in these areas have not only renovated the theory of signal processing, but also resulted in new tools that find applications in various domains. For instance, the multirate signal processing has triggered the recent advances in modern technology and speech/audio coding, and the fractional Fourier transform in time-frequency analysis has found applications in the radar and medical signal processing areas [5–8].