Multilayer limb quasi-static electromagnetic modeling with experiments for Galvanic coupling type IBC.

Intra-body communication (IBC) is a new, emerging, short-range and human body based communication methodology. It is a technique to network various devices on human body, by utilizing the conducting properties of human tissues. For currently fast developed Body area network(BAN)/Body sensor network(BSN), IBC is believed to have advantages in power consumption, electromagnetic radiation, interference from external electromagnetic noise, security, and restriction in spectrum resource. In this article, the authors propose an improved mathematical model, which includes both electrical properties and proportion of human tissues, for IBC on a human limb. By solving the mathematical model analytically on four-layer system (skin, fat, muscle, and bone) and conducting in-vivo experiment, a comparison has been conducted.

Modeling for intra-body communication with bone effect.

Intra-body communication (IBC) is a new, different "wireless" communication technique based on the human tissue. This short range "wireless" communication technology provides an alternative solution to wearable sensors, home health system, telemedicine and implanted devices. The development of the IBC enables the possibilities of providing less complexity and convenient communication methodologies for these devices. By regarding human tissue as communication channel, IBC making use of the conductivities properties of human tissue to send electrical signal from transmitter to receiver. In this paper, the authors proposed a new mathematical model for galvanic coupling type IBC based on a human limb. Starting from the electromagnetic theory, the authors treat human tissue as volume conductor, which is in analogous with the bioelectric phenomena analysis. In order to explain the mechanism of galvanic coupling type technique of IBC, applying the quasi-static approximation, the governing equation can be reduced to Laplace Equation. Finally, the analytical model is evaluated with on-body measurement for testing its performance. The comparison result shows that the developed mathematical model can provide good approximation for galvanic coupling type IBC on human limb under low operating frequencies.

Simple electrical model and initial experiments for intra-body communications.

Intra-Body Communication(IBC) is a short range "wireless" communication technique appeared in recent years. This technique relies on the conductive property of human tissue to transmit the electric signal among human body. This is beneficial for devices networking and sensors among human body, and especially suitable for wearable sensors, telemedicine system and home health care system as in general the data rates of physiologic parameters are low. In this article, galvanic coupling type IBC application on human limb was investigated in both its mathematical model and related experiments. The experimental results showed that the proposed mathematical model was capable in describing the galvanic coupling type IBC under low frequency. Additionally, the calculated result and experimental result also indicated that the electric signal induced by the transmitters of IBC can penetrate deep into human muscle and thus, provide an evident that IBC is capable of acting as networking technique for implantable devices.

Beat-to-Beat ECG ventricular late potentials variance detection by filter bank and wavelet transform as beat-sequence filter.

This paper presents a novel method that employs a wavelet transform and filter bank to detect ventricular late potentials (VLPs) from beat to beat in order to keep its variance. Conventionally, three time-domain features, which are highly related to the QRS complex endpoint, are generally accepted as criteria for classifying VLPs. Signal averaging is a general and effective de-noising method in electroencephalogram late potentials detection, but it may also eliminate the beat-to-beat variance. Other types of filter applied to the time sequence may destroy the late potentials as well when trying to filter out the noise. To preserve the variance from beat to beat as well as late potentials as much as possible, the concept of a beat-sequence filter will be introduced and the wavelet transform can be directly applied to the beat sequence, as will be demonstrated in this paper. After de-noising, instead of applying the voltage comparison on the de-noised signal to determine the QRS complex endpoint, the signal will be processed by a filter bank, and the QRS complex endpoint will be determined by consideration of the correlation between two beats. Both simulation and clinical experimental results will be presented to illustrate the effectiveness of this method.