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Characterization of the human body as a transmission medium for electrical signals is a necessity for using intrabody communication (IBC) technique into connecting wearable electronic sensors and devices. In this paper, we propose a novel multilayer distributed circuit model for galvanic-coupling type IBC, which is emphasized on the propagation characteristics in contrast with other IBC models. Based on the model, a program is written in MATLAB to investigate the propagation characteristics of a human body channel with the frequency of 10 MHz to 20 MHz and the distance of 5 cm to 10 cm. Finally, a galvanic coupling IBC measurement is implemented to verify the proposed model. The outcome proves that the model is valid and correct.

Intrabody communication (IBC) is a promising wireless communication technology which was first mentioned by Zimmerman in 1995 [

Consequently, with the objective of high-speed short-range communication in wireless body area network (WBAN), in this paper, we propose a novel multilayer distributed circuit model to investigate the propagation mechanisms of galvanic coupling-type IBC. For the human forearm, we write a program in MATLAB to calculate the voltage gains of a body channel based on the proposed model with the frequency of 10 MHz to 20 MHz and propagation distance of 5 cm to 10 cm. At the same time, we have also carried out some experimental measurements using harmonized galvanic coupling setups to validate the proposed model. It should be noted that the frequency range in our study is much higher than any other existing galvanic coupling IBC research. Therefore, this model will be quite valuable for the galvanic coupling IBC in high-speed communication which is the limitation of the current galvanic coupling IBC.

This paper is organized as follows: Section

In this paper, the human forearm is simplified as a multilayer cylinder formed by five different concentric layers, each of which simulates a different tissue: skin, fat, muscle, cortical bone, and cancellous bone. The detailed geometry is shown in Figure _{e} and _{s}. The AC signal is applied on TX and is transmitted to RX along the

Geometry of the proposed model. (a) Transverse section of the arm composed of five concentric layers of tissues: skin, fat, muscle, cortical bone, and cancellous bone. (b) Longitudinal view of the arm with electrodes, depicting parameters such as channel length (_{s}), interelectrode distance (_{e}), and arm length (_{arm}).

Geometry parameters of the human forearm.

Parameter | Value | Description |
---|---|---|

_{a} (cm) |
5 | Arm radius |

_{arm} (cm) |
60 | Arm length |

_{s} (mm) |
1.5 | Skin thickness |

_{f} (mm) |
8.5 | Fat thickness |

_{m} (mm) |
27.5 | Muscle thickness |

_{cb} (mm) |
6 | Cortical bone thickness |

_{e} (mm) |
4 | Electrode side length |

_{e} (cm) |
8 | Interelectrode distance |

_{s} (cm) |
5, 6.5, 8, 10 | Signal channel length |

The human forearm can be seen as a lossy multilayer transmission line consisted of multilayer distributed circuits, because the signal from TX to RX propagates in a multipath channel composed of the different tissue layers of skin, fat, muscle, and bones. Each of the human tissue layer is equivalent to a distributed circuit consisted of the periodic insertion of basic cells formed by the impedance _{e} is the equivalent impedance of the electrode and _{s} and _{s} are the distributed impedance and admittance of skin, respectively. We can see that the distributed parameter elements _{s} and _{s} shown in the dotted box are repeated with the longitudinal direction to represent the propagation characteristics of the signal in the skin tissue. The other tissue layers, such as fat and muscle, are modeled as well, and the final detail model scheme is shown in Figure _{s} and _{s}, _{f} and _{f}, and _{m} and _{m} are, respectively, the per-unit-distance impedances and admittances of the skin, fat, and muscle. _{sf} and _{fm} are, respectively, the per-unit-distance admittances of skin to fat and fat to muscle.

Equivalent distributed circuit of the skin layer. (a) Galvanic coupling-type IBC. (b) Distributed circuit of the skin layer. (c) Impedance of the skin (_{s}). (d) Conductance of the skin (_{s}).

Multilayer distributed circuit model of galvanic coupling IBC for the human forearm.

The frequency behavior of dielectric properties of tissues, such as conductivity and permittivity, is derived from the parametric modes of Gabriel et al. [

Once

Then, the relative permittivity

Next, the conductance and capacitance of each tissue are easily written as follows:

Finally, the per-unit-distance impedances of basic cell on each tissue layer with propagation direction are easily calculated from

and the per-unit-distance admittances of basic cell on each tissue layer between two points on the same plane are obtained by the following:

It should be noted that the inductive element

We assume that the signal propagates along the

Our objective is to determine the manner and extent to which the output voltage and current are changed from their input values in the limit as the length

Now, in the limit, as

Once the equations of multilayer distributed circuit are obtained, the final solution of voltage and current distribution with respect to

With the help of Laplace transformation, (8) is transformed as follows:

When the source voltage is imposed on TX at the moment of

Substituting

Finally, the inverse Laplace transforms of

These are the solutions of the multilayer distributed circuit model. With these solutions, the received voltage and current by RX electrodes at any distance _{o} is the received voltage.

The proposed model is carried out by writing a program in MATLAB to study the gain of the received voltage with the distance

Gain of the received voltage corresponding to the distance

In order to validate the results of the proposed model, a galvanic coupling IBC measurement on a human forearm is carried out. The setup is consisted of a signal generator DG4162 and a balun FTB-1-6 at the transmitter side (TX), a digital isolation oscilloscope TPS2024 at the receiver side (RX), and four 4 cm × 4 cm medical electrodes LT-1 attached to the skin in a differential configuration in Figure _{s}, 5 cm, 6.5 cm, and 8 cm, are tested.

Galvanic coupling measurement setup. (a) Measurement circuit. (b) Measurement scene.

Figure

Comparison of the results between the IBC measurement and model.

Comparison of the gain values between the IBC measurement and model corresponding to the distance

Frequency (MHz) | Value of model (dB) | Averaged value of measurement (dB) | Difference (dB) |
---|---|---|---|

10 | −16.45 | −18.77 | 2.32 |

11 | −16.12 | −18.52 | 2.40 |

12 | −15.85 | −17.94 | 2.09 |

13 | −15.62 | −18.62 | 3.00 |

14 | −15.42 | −17.30 | 1.88 |

15 | −15.25 | −17.46 | 2.21 |

16 | −15.1 | −16.28 | 1.18 |

17 | −14.96 | −16.16 | 1.20 |

18 | −14.84 | −16.01 | 1.17 |

19 | −14.72 | −14.69 | 0.03 |

20 | −14.62 | −14.41 | 0.21 |

In this paper, a novel multilayer distributed circuit model for galvanic coupling IBC on a human forearm has been proposed to investigate the propagation characteristics of a body channel. Based on the model, we find that a human body channel presents as a high band-pass characteristic with the frequency from 10 MHz to 20 MHz, and the signal is exponentially attenuating with the increasing of propagation distance along the body. It illustrates that the human forearm is like a multilayer lossy transmission line which has some similar characteristics with respect to the general transmission line. To validate the accuracy of the model, an IBC experiment on a human forearm has been carried out, and the results demonstrate that the proposed model based on multilayer distributed circuit meets the actual situation of high-frequency galvanic coupling IBC which other models do not focus. Though the model is fulfilled at the frequency of 10 MHz to 20 MHz, it may be applied to a higher frequency, for example, 400 MHz, and the experimental probe will be done in our next important work. Considering that a body channel may be affected by the sizes and types of different electrodes, we will take a deep study on the electrodes and account it into modeling in the next step. Moreover, we will also focus on extending the model to other parts of the human body and the possible application of these findings to the design of wireless medical healthcare devices in the future.

The authors declare that there is no conflict of interest regarding the publication of this paper.

This work was supported by the National Natural Science Foundation of China under Grant no. U1505251, the Chinese Ministry of Science and Technology, Project no. 2016YFE0122700, and the New Century Excellent Talents Program of the Department of Education, Fujian Province, China.