Intra-Body Communication (IBC), which modulates ionic currents over the human body as the communication medium, offers a low power and reliable signal transmission method for information exchange across the body. This paper first briefly reviews the quasi-static electromagnetic (EM) field modeling for a galvanic-type IBC human limb operating below 1 MHz and obtains the corresponding transfer function with correction factor using minimum mean square error (MMSE) technique. Then, the IBC channel characteristics are studied through the comparison between theoretical calculations via this transfer function and experimental measurements in both frequency domain and time domain. High pass characteristics are obtained in the channel gain analysis versus different transmission distances. In addition, harmonic distortions are analyzed in both baseband and passband transmissions for square input waves. The experimental results are consistent with the calculation results from the transfer function with correction factor. Furthermore, we also explore both theoretical and simulation results for the bit-error-rate (BER) performance of several common modulation schemes in the IBC system with a carrier frequency of 500 kHz. It is found that the theoretical results are in good agreement with the simulation results.

In recent years, the increasing number of wearable devices on human has been witnessed as a trend. These devices can serve for many purposes: personal entertainment, communication, emergency mission, health care supervision, delivery, etc. Sharing information among the devices scattered across the human body requires a body area network (BAN) and body sensor network (BSN). However, implementation of the BAN/BSN with the conventional wireless technologies cannot give optimal result. It is mainly because the high requirements of light weight, miniature, energy efficiency, security, and less electromagnetic interference greatly limit the resources available for the communication modules. The newly developed intra-body communication (IBC) can alleviate most of the mentioned problems. This technique, which employs the human body as a communication channel, could be an innovative networking method for sensors and devices on the human body. In order to encourage the research and development of the IBC, the authors are favorable to lay a better and more formal theoretical foundation on IBC. They propose a multilayer mathematical model using volume conductor theory for galvanic coupling IBC on a human limb with consideration on the inhomogeneous properties of human tissue. By introducing and checking with quasi-static approximation criteria, Maxwell's equations are decoupled and capacitance effect is included to the governing equation for further improvement. Finally, the accuracy and potential of the model are examined from both in vitro and in vivo experimental results.

Recent technical advancements in neural engineering allow for precise recording and control of neural circuits simultaneously, opening up new opportunities for closed-loop neural control. In this work, a rapid spike sorting system was developed based on template matching to rapidly calculate instantaneous firing rates for each neuron in a multi-unit extracellular recording setting. Cluster templates were first generated by a desktop computer using a non-parameter spike sorting algorithm (Super-paramagnetic clustering) and then transferred to a field-programmable gate array digital circuit for rapid sorting through template matching. Two different matching techniques–Euclidean distance (ED) and correlational matching (CM)–were compared for the accuracy of sorting and the performance of calculating firing rates. The performance of the system was first verified using publicly available artificial data and was further confirmed with pre-recorded neural spikes from an anesthetized Mongolian gerbil. Real-time recording and sorting from an awake mouse were also conducted to confirm the system performance in a typical behavioral neuroscience experimental setting. Experimental results indicated that high sorting accuracies were achieved for both template-matching methods, but CM can better handle spikes with non-Gaussian spike distributions, making it more robust for in vivo recording. The technique was also compared to several other off-line spike sorting algorithms and the results indicated that the sorting accuracy is comparable but sorting time is significantly shorter than these other techniques. A low sorting latency of under 2 ms and a maximum spike sorting rate of 941 spikes/second have been achieved with our hybrid hardware/software system. The low sorting latency and fast sorting rate allow future system developments of neural circuit modulation through analyzing neural activities in real-time.

Among the biomedical imaging modalities, photoacoustic computed tomography (PACT) was one of the emerging hybrid techniques in recent years. In designing the PACT imaging system, a finite-bandwidth transducer is one of the limited factors for the overall performance. As the target size is inversely proportional to the dominant frequency components of the generated photoacoustic (PA) signal, a broad bandwidth transducer is desired for different scales' imaging. In this paper, a monolithic multiband capacitive micromachined ultrasonic transducer (CMUT) array was designed and fabricated for the reception of the wideband PA signals so as to provide high-resolution images with high-frequency CMUT arrays and present the high signal-to-noise-ratio major structure with low-frequency CMUT arrays. To demonstrate its performance, a phantom experiment was conducted to show and evaluate the various qualities of multiresolution images. In addition, an in vivo mouse model experiment was also carried out for revealing the multiscale PA imaging capability with the multiband CMUTs on biological tissues. From the obtained results, the images from different CMUT arrays could show the structures of the mouse brain in different scales. In addition, the images from the high-frequency CMUT arrays were able to reveal the major blood vasculatures, whereas the images from low-frequency CMUT arrays showed the gross macroscopic anatomy of the brain with higher contrast.