Dynamic Electrical Impedance Tomography with Known Internal Structures

A Smart Wireless Ear-Worn Device for Cardiovascular and Sweat Parameter Monitoring During Physical Exercise: Design and Performance Results

Wearable biomedical technology has gained much support lately as devices have become more affordable to the general public and they can easily interact with mobile phones and other platforms. The feasibility and accuracy of the data generated by these devices so as to replace the standard medical methods in use today is still under scrutiny. In this paper, we present an ear-worn device to measure cardiovascular and sweat parameters during physical exercise. ECG bipolar recordings capture the electric potential around both ears, whereas sweat rate is estimated by the impedance method over one segment of tissue closer to the left ear, complemented by the measurement of the lactate and pH levels using amperiometric and potentiometric sensors, respectively. Together with head acceleration, the acquired data is sent to a mobile phone via BLE, enabling extended periods of signal recording. Results obtained by the device have shown a SNR level of 18 dB for the ECG signal recorded around the ears, a THD value of −20.46 dB for the excitation signal involved in impedance measurements, sweat conductivity of 0.08 S/m at 1 kHz and sensitivities of 50 mV/pH and 0.8 μA/mM for the pH and lactate acquisition channels, respectively. Testing of the device was performed in human subjects during indoors cycling with characteristic level changes.

Impedance-based real-time position sensor for lab-on-a-chip devices

This paper presents the theoretical and experimental development of an integrated position sensor for lab-on-a-chip devices. The interest for single cell analysis is growing. However, this requires monitoring and controlling cell displacements in real time during their journey in the chip. Due to the high number of cells that must be monitored at the same time, classical vision-based sensors are not suitable. This paper aims to present an alternative based on impedance measurement. The position of the cells is obtained from the variation of impedance measured between two electrodes. This technique presents several advantages: the sensor is integrated into the chip, the measurement electrodes are compatible with the fabrication process of actuation electrodes for dielectrophoresis, the sampling time of the sensor is high and the position of the cells can be obtained in real time. This article highlights the concept of position-sensitive impedance sensing. The design of the chip, and in particular of the electrodes, is discussed to improve the sensitivity and repeatability of the measurement. The issue of real-time detection in a noisy environment is solved by using an extended Kalman filter. As a first proof of concept, this article presents experimental validation on a 1D case to determine the longitudinal position of 8.7 μm diameter beads in a channel.

Dynamic electrical impedance imaging with the interacting multiple model scheme

In this paper, an effective dynamical EIT imaging scheme is presented for on-line monitoring of the abruptly changing resistivity distribution inside the object, based on the interacting multiple model (IMM) algorithm. The inverse problem is treated as a stochastic nonlinear state estimation problem with the time-varying resistivity (state) being estimated on-line with the aid of the IMM algorithm. In the design of the IMM algorithm multiple models with different process noise covariance are incorporated to reduce the modeling uncertainty. Simulations and phantom experiments are provided to illustrate the proposed algorithm.