Body channel powering (BCP) has emerged as a promising method for wirelessly powering the Internet of Implanted Things (IoIT). However, current galvanic-coupling (GC-BCP) and capacitive-coupling (CC-BCP) techniques are limited by short transmission distance and restricted applicability to fully implantable devices, respectively. To address these issues, this paper proposes a tissue-coupling BCP (TC-BCP) technique that employs a floated transmitter (TX) ground electrode to enhance coupling with remote implant-site tissue, thereby enabling more power delivery to the fully implanted receiver (RX). A lumped circuit model is first developed to theoretically analyze three fundamental transmission properties. Experimental validation using a prototype system demonstrates that TC-BCP outperforms conventional BCP in long-range power transfer achieving 8.63 dB higher path gain at a lateral distance of 24 cm, and expands single RX to at least three simultaneous RX nodes with minimal interference. Moreover, the optimization of stacked-up TX electrode configuration, considering three key geometric parameters, yields a path gain enhancement of up to 7.58 dB. These investigations confirm that the proposed TC-BCP can effectively extend the transmission range while supporting multi-node and integrated-TX powering of fully implantable IoIT.

Intra-Body power transfer (IBPT) holds significant potential for powering neural stimulators due to its flexible transmitter placement and extended transmission range. However, the fluctuating transmission channel, varying stimulus demands, and implantation applications pose challenges for the rectifier chip to expand its dynamic range (DR) at high power conversion efficiency (PCE). This paper proposes an NMOS-sided biased rectifier with feedback transistors to clamp the gate voltage at high input power. By properly balancing the forward conduction and reverse leakage current, DR is significantly extended. The chip is fabricated in the 0.18 μm CMOS technology, occupying an area of 444 μm × 403 μm. The post-simulation results confirm that with the frequency and load fixed at 10 MHz and 2 kΩ respectively, the NMOS-sided biased rectifier achieves a DR of 7.5 dB with PCE> 80%.

The implantable body-coupled channel (IBCC) method, which utilizes high-conductivity biological tissue as the medium for transferring power or data to implants, offers several distinct advantages over traditional methods. However, the current research on its model remains limited. In this paper, we propose a lumped circuit model of the implantable body-coupled channel to analyze its transmission mechanism. To evaluate the model, the channel loss is measured using a vector network analyzer (VNA) for different receiver electrode types and transmission distances. The simulated results have been validated to be consistent with the measured results across the various experimental conditions. Furthermore, the proposed model demonstrates higher accuracy compared to the existing circuit model, which can provide enhanced guidance for IBCC’s further application in the field of implantable bioelectronics.

In this work, we introduce a compact, bidirectional, wireless intracortical Brain-Computer Interface (iBCI) system. The system incorporates various functionalities, including stimulation, high sampling rate (30 kS/s) recording, online spike detection and signal compression, wireless power transfer, and communication. Specifically, to optimize data bandwidth utilization and ensure scalability for an increased number of channels, an efficient spike detection operator and an algorithm for signal compression are implemented on the chip. In addition, the proposed system supports customizable configuration of in total 16 recording and stimulation channels in a flexible way. The system’s functionalities and performance have been validated by acquiring both simulated signals and real neural signals in rats. Overall, this design takes an important step towards forming a compact system using low-cost components for closed-loop BCI applications.

This paper proposes a multi-sensor nodes communication system using the human body channel as the transmission medium. First, the transceiver is highly integrated with adjustable input and output impedance and adjustable gain. Second, in order to make better use of the characteristics of the human body channel, Manchester code is used for signal transmission between sensor nodes. In third, multi-sensor node communication is realized by adopting a master-multi-slave structure and time-division multiplexing. The master sends instructions to the slave nodes by broadcasting, sets the system in different modes, and receives the data from slave sensors. The transceiver is implemented with a 65nm CMOS process and Manchester codecs are implemented in Field-Programmable Gate Arrays (FPGA). As a result, the proposed transceiver can achieve the highest data rates of 60 Mbps and the measured RX sensitivity is −64dBm. And the multi-sensor nodes communication system realizes the data interaction between one hub and eight slave sensors.

Implantable bioelectronics are becoming more widespread for biomedical applications. To avoid frequent surgical operations, self-powered implantable bioelectronics are more attractive. Traditional wireless power transfer (WPT) methods suffer from limitations that include bulky size, short transfer distance or flexibility limitation. In this paper, we present a new body channel based wireless power transfer (BC-WPT) method which uses the human body as power transfer medium to transfer power. In this way, the power receiver is only needed to be implanted in body tissue and the power transmitter can be applied on any part of the human body surface. Since the power transmitter and power receiver do not need a transmitting coil/antenna and a receiving coil/antenna, BC-WPT has the advantages of lower size, long transfer distance, and flexibility. A simulation platform and a prototype BC-WPT system are built to validate the availability of the proposed method.

This paper proposes a novel auto loss compensation (ALC) system to enable non-contact operations for capacitive coupled body channel communication (CC-BCC). The system employs a time-division compensation mismatch indicator (CMI) to continuously monitor the compensation error, and dynamically adjust the compensation inductor through a PI controller. With the close-loop topology, the proposed ALC system has three advantages: First, the path loss induced by non-contact status and backward coupling effect can be compensated simultaneously; Second, this system can dynamically attenuate the path losses, even when the channel characteristics vary with time; Third, this system has high robustness, which is insusceptible to channel variations; The simulation results show that the loss reduction of the proposed ALC system is 18 dB higher than the conventional compensation technique in the worst case.

Body channel communication (BCC) is one of the best candidates for communications in wireless body sensor networks as it uses the human body as transmission media to minimize transmission loss resulting better energy efficiency. The main issue of BCC is the loss in its backward path, which is formed by the capacitive coupling between two floated GND electrodes (GEs) of transmitter (TX) and receiver (RX). To mitigate the backward path loss, an off-chip inductor could be used to resonate with the backward capacitance to reduce the impedance of the backward path. However, this method is not suitable for wearable applications as the off-chip inductor only works for fixed communication distance. In this paper, we present a novel self-adaptive capacitive compensation (SACC) scheme to reduce the capacitive loss of the backward path. The proposed system automatically estimates the distance between GEs of TX and RX with the help of received signal strength indicator (RSSI). The backward capacitance is then calculated based on the estimated distance. And then the capacitance is compensated by a digitally controlled active inductor to reduce the backward path loss. Simulation shows that the proposed scheme achieves more than 15 dB channel enhancement at the IEEE 802.15.6 standard frequency.

Human body communication (HBC) has significant advantage over wireless communication schemes in wireless body area networks (WBANs) in terms of power efficiency due to the high conductivity of human body. An accurate circuit model for transmission channel is necessary for optimizing the HBC transceiver performance. Conventional models achieve limited accuracy because of incomplete body tissue model or the use of tranmission-line at circuit level. In this paper, we proposed a comprehensive HBC circuit model which is based on 5 human-surface tissue layers representing the physiological characteristics of living tissues and the frequency dependence of their dielectric properties. Instead of using transmission-line, our model is based on lumped-element analysis, which is more accurate at the 21 MHz frequency band specified by the IEEE 802.15.6 HBC standard. We verified the proposed model by actual measurement on human body at various of communication distances. Experimental results show that the proposed model achieved the minimum error among all the modeling works, i.e., 1.80% minimum error and 2.24% maximal error at various communication distances.