This work presents a novel interaction method using bioimpedance (Bio-Z) to enhance virtual reality (VR) experience. The platform consists of two electrode bands (with 4 and 5 electrodes), a high-performance bioimpedance measurement system, a recurrent neural network deployed on a laptop and a VR headset. The system captures the Bio-Z features from muscle contraction and bone movement in the wrist and upper arm. After training, the regression model can predict hand grasp angle and forearm motion in both horizontal and vertical directions. This system can be used as a VR human-computer interaction (HCI) peripheral. Visitors will experience VR games using this demonstration platform.

The current generator is one of the most essential parts in electrical impedance tomography (EIT) systems. State-of-art current generators suffer from the trade-off between current efficiency, linearity, output impedance and well-controlled output current level. To address these challenges, a current DAC based current generator with a fourth-order current-mode filter is proposed. The current generator was designed and simulated in a 65 nm CMOS process. By utilizing the proposed current-mode filter and the master and slave current DAC, the current generator achieves a well-controlled output current leveling with 255 tunning steps, 83.9% current efficiency, 0.11% THD at 1 mAppoutput current and 2 MΩ output impedance at 500 kHz.

The purpose of lung recruitment is to improve and optimize the air exchange flow in the lungs by adjusting the respiratory settings during mechanical ventilation. Electrical impedance tomography (EIT) is a monitoring tool that permits measurement of regional pulmonary filling characteristics or filling index (FI) during ventilation. The conventional EIT system has limitations which compromise the accuracy of the FI. This paper proposes a novel and automated methodology for accurate FI estimation based on EIT images of recruitable regional collapse and hyperdistension during incremental positive end-expiratory pressure. It identifies details of the airway tree (AT) to generate a correction factor to the FIs providing an accurate measurement. Multi-scale image enhancement followed by identification of the AT skeleton with a robust and self-exploratory tracing algorithm is used to automatically estimate the FI. AT tracing was validated using phantom data on a ground-truth lung. Based on generated phantom EIT images, including an established reference, the proposed method results in more accurate FI estimation of 65% in all quadrants compared with the current state-of-the-art. Measured regional filling characteristics were also examined by comparing regional and global impedance variations in clinically recorded data from ten different subjects. Clinical tests on filling characteristics based on extraction of the AT from the resolution enhanced EIT images indicated a more accurate result compared with the standard EIT images.

This paper presents an antenna-based RF wireless power and data transfer system for wireless neonate lung function monitoring in an intensive care unit using electrical impedance tomography (EIT). The proposed dual-band system comprises a directional slotted patch transmit antenna and a slotted flexible omnidirectional monopole antenna operating at 2.51 GHz and 5.1 GHz. A slotting technique unique to each antenna is proposed to achieve dual-band operation and size miniaturization for each antenna. Also, the arraying technique combined with parasitic elements is employed to increase the receive antenna gain and in turn the received power level. Both transmit and receive antennas were simulated and fabricated. Following FCC safety regulations, measurements show 20 mW received power when the receiver and the transmitter are spaced 19 cm apart.

A 32 channel wearable torso shape detection belt will be demonstrated. The belt is designed to measure the torso shape of a neonate and provide real-time boundary information to assist the electrical impedance tomography (EIT) system to produce high quality lung respiration images. The system is fully integrated on a flexible printed circuit board which is encapsulated in a silicon wearable cover. During the live demonstration, while EIT images are reconstructed, the boundary shape can be changed to improve the image.

This paper describes the design of fully differential sine pulse-width-modulation (SPWM) wave current generator for bioimpedance measurement applications. The current generator has been designed in a 0.18-μm CMOS technology. Its analog front-end operates from ±1.65 V and has a current consumption of Iout+ 22 μA + (fclk× 1.7 pA) where Ioutis the output current and fclkis the operating frequency. It can provide outputs from 50 μAppto 1 mAppof SPWM current up to 98 kHz with a maximum voltage compliance of ±1.25 V. Using linear current feedback, the current generator has a designed transconductance of 1 mA/V. Feedback also enables cancellation of common mode signals and a high output impedance.

A wearable electrical impedance tomography (EIT) system for hand prosthesis motion control is demonstrated. The system captures the user's hand motion by measuring the impedance alterations caused by muscle and bone movement inside the forearm. These impedance data are sent to an artificial neural network for motion classification which is then used to manipulate a hand prosthesis. During the live demonstration, a sensor band is put on a volunteers' forearm for data acquisition. After signal processing, hand gestures learnt by the neural network can be recognized and the same hand motion can be recreated through the hand prosthesis in real-time.

This paper presents a high accuracy hand gesture recognition system based on electrical impedance tomography (EIT). The system interfaces the forearm using a wrist wrap with embedded electrodes. It measures the inner conductivity distributions caused by bone and muscle movement of the forearm in real-time and passes the data to a deep learning neural network for gesture recognition. The system has an EIT bandwidth of 500 kHz and a measured sensitivity in excess of 6.4 Ω per frame. Nineteen hand gestures are designed for recognition, and with the proposed round robin sub-grouping method, an accuracy of over 98% is achieved.

A wearable electrical impedance tomography system for lung respiratory monitoring will be demonstrated. The system features an active electrode integrated circuit (IC) fabricated in 0.35-μm CMOS technology. The IC is mounted on a flexible printed circuit board which is then embedded in a textile belt. During the live demonstration, the belt can be put on the volunteers' chest, and through a back-end signal processing hub, the system is able to provide real-time lung respiratory images on a remote computer.

This paper describes the design of an active electrode integrated circuit (IC) for a wearable electrical impedance tomography (EIT) system required for real time monitoring of neonatal lung function. The IC comprises a wideband high power current driver (up to 6 mAp-poutput current), a low noise voltage amplifier and two shape sensor buffers. The IC has been designed in a 0.35-μm CMOS technology. It operates from ±9 V power supplies and occupies a total die area of 5 mm2. Post-layout simulations are presented.

Impedance detection plays a crucial role in the development of Lab-on-a-Chip (LOAC) technologies. Various types of impedance biosensors have been developed over the years, with the main focus being centered on interdigital sensors. Optimization of impedance sensors has only recently attracted interest. In this paper we present a conformal mapping approach to the optimization of bipolar and tetrapolar impedance sensors. This technique enables an analytic equation for the sensitivity of the sensors to impedance changes to be obtained. Optimization of these sensors using this analytic equation was performed and a number of optimized sensor designs are presented in this paper.

Deep brain stimulation (DBS) is a widely accepted clinical tool adopted for the treatment of a number of motor disorders. Despite its clinical efficacy, its underlying mechanisms have not been yet fully understood. One major issue that we identify as partly responsible for this lack of understanding is related to the poor control over the size, shape and location of the distribution of the depolarizing field around the electrode. With this and a parallel work the authors are proposing to develop and implement techniques that would allow for some degree of control over the distribution of the potential fields. This paper presents the application to DBS of a technique based on a tripolar current source configuration, with adjustable current flow through the lateral (anodic) branches of the tripole. The behavior of potential fields in the tissue were simulated by adopting FEM models of DBS electrode implanted in brain tissue. The profiles of simulated and measured fields were in agreement and they have shown how a dynamic tripolar current source can be adopted to obtain increase the focus and control the location of distribution of the fields around the electrode.

Electrical bioimpedance spectroscopy is a fast and relatively easily applicable method for tissue characterization. This paper describes a CMOS instrumentation amplifier based on the principle of current feedback for use in this application. The amplifier was designed in a 0.35 /spl mu/m CMOS technology and dissipates 420 /spl mu/W from /spl plusmn/1.5 V power supplies. Simulations showed that it has a bandwidth of 2 kHz-1 MHz, a mid-band gain of 20 dB, a CMRR of 101 dB at 1 MHz, and an input-referred noise voltage floor of 11.5 nV//spl radic/Hz.

In electrical impedance tomography, errors due to stray capacitance may be reduced by optimization of the reference phase of the demodulator. Two possible methods, maximization of the demodulator output and minimization of reciprocity error have been assessed, applied to each electrode combination individually, or to all combinations as a whole. Using an EIT system with a single impedance measuring circuit and multiplexer to address the 16 electrodes, the methods were tested on resistor-capacitor networks, saline-filled tanks and humans during variation of the saline concentration of a constant fluid volume in the stomach. Optimization of each channel individually gave less error, particularly on humans, and maximization of the output of the demodulator was more robust. This method is, therefore, recommended to optimize systems and reduce systematic errors with similar EIT systems.

The author presents a machine designed with a two-phase approach. First, the selection of an efficient algorithm, based on the quality of the final image and on the computational efficiency, is undertaken. Second, the algorithm is realized in hardware which incorporates efficient array processing structures, with the aim of creating regular repeated structures. The design is based on the S.Y. Kung and C.E. Leiserson (1978) approach, although certain elements of the architecture deviate from a true systolic architecture. These include bidirectional communication, which allows other image processing operations to be performed. The bit-serial machine is designed to perform the image reconstruction operation known as back-projection. The machine offers significant speed improvement over the general-purpose pipeline architectures used at present.>