Development of real-time cellular impedance analysis system

The cell impedance analysis technique is a label-free, non-invasive method, which simplifies sample preparation and allows applications requiring unmodified cell retrieval. However, traditional impedance measurement methods suffer from various problems (speed, bandwidth, accuracy) for extracting the cellular impedance information. This thesis proposes an improved system for extracting precise cellular impedance in real-time, with a wide bandwidth and satisfactory accuracy. The system hardware consists of five main parts: a microelectrode array (MEA), a stimulation circuit, a sensing circuit, a multi-function card and a computer. The development of system hardware is explored. Accordingly, a novel bioimpedance measurement method coined digital auto balancing bridge method, which is improved from the traditional analogue auto balancing bridge circuitry, is realized for real-time cellular impedance measurement. Two different digital bridge balancing algorithms are proposed and realized, which are based on least mean squares (LMS) algorithm and fast block LMS (FBLMS) algorithm for single- and multi-frequency measurements respectively. Details on their implementation in FPGA are discussed. The test results prove that the LMS-based algorithm is suitable for accelerating the measurement speed in single-frequency situation, whilst the FBLMS-based algorithm has advantages in stable convergence in multi-frequency applications. A novel algorithm, called the All Phase Fast Fourier Transform (APFFT), is applied for post-processing of bioimpedance measurement results. Compared with the classical FFT algorithm, the APFFT significantly reduces spectral leakage caused by truncation error. Compared to the traditional FFT and Digital Quadrature Demodulation (DQD) methods, the APFFT shows excellent performance for extracting accurate phase and amplitude in the frequency spectrum. Additionally, testing and evaluation of the realized system has been performed. The results show that our system achieved a satisfactory accuracy within a wide bandwidth, a fast measurement speed and a good repeatability. Furthermore, our system is compared with a commercial impedance analyzer (Agilent 4294A) in biological experiments. The results reveal that our system achieved a comparable accuracy to the commercial instrument in the biological experiments. Finally, conclusions are given and the future work is proposed

Impedance Spectroscopy

This book covers new advances in the field of impedance spectroscopy including fundamentals, methods and applications. It releases selected extended and peer reviewed scientific contributions from the International Workshop on Impedance Spectroscopy (IWIS 2017) focussing on detailed information about recent scientific research results in electrochemistry and battery research, bioimpedance measurement, sensors, system design, signal processing

Design, implementation and test of a fast impedance spectroscopy measurement system for biomedical applications

This project offers a detailed explanation on the design, implementation, and measures to characterize the hardware and firmware programmed for the acquisition of the electrical impedance spectra. It includes from the signal generation, which is based on the use of a multifrequency signal, to the acquisition and signal processing. All have been implemented using the development board RedPitaya. Moreover, all the process of signal generation, signal acquisition and processing so as the results calculation is done inside the commented RedPitaya board. The communication between the board and the computer is handled through SSH via ethernet port. Finally, this project also includes a brief script implemented in MatLab which objective is just to represent the acquired results from the board. To conclude, characterization measures are made to verify the system specifications

Bioimpedance sensors: a tutorial

Electrical bioimpedance entails the measurement of the electrical properties of tissues as a function of frequency. It is thus a spectroscopic technique. It has been applied in a plethora of biomedical applications for diagnostic and monitoring purposes. In this tutorial, the basics of electrical bioimpedance sensor design will be discussed. The electrode/electrolyte interface is thoroughly described, as well as methods for its modelling with equivalent circuits and computational tools. The design optimization and modelling of bipolar and tetrapolar bioimpedance sensors is presented in detail, based on the sensitivity theorem. Analytical and numerical modelling approaches for electric field simulations based on conformal mapping, point electrode approximations and the finite element method (FEM) are also elaborated. Finally, current trends on bioimpedance sensors are discussed followed by an overview of instrumentation methods for bioimpedance measurements, covering aspects of voltage signal excitations, current sources, voltage measurement front-end topologies and methods for computing the electrical impedance

A comparison of front-end amplifiers for tetrapolar bioimpedance measurements

Many commercial benchtop impedance analyzers are incapable of acquiring accurate tetrapolar measurements, when large electrode contact impedances are present, as in bioimpedance measurements using electrodes with micrometer-sized features. External front-end amplifiers can help overcome this issue and provide high common-mode rejection ratio (CMRR) and input impedance. Several discrete component-based topologies are proposed in the literature. In this article, these are compared with new alternatives with regard to their performance in measuring known loads in the presence of electrode contact impedance models, to emulate tetrapolar bioimpedance measurements. These models are derived from bipolar impedance measurements taken from the electrodes of a tetrapolar bioimpedance sensor. Comparison with other electrode models used in the literature established that this is a good and challenging model for bioimpedance front-end amplifier evaluation. Among the examined amplifiers, one of the best performances is achieved with one of the proposed topologies based on a custom front-end with no external resistors (AD8066/AD8130). Under the specific testing conditions, it achieved an uncalibrated worst-case absolute measurement deviation of 4.4% magnitude and 4° at 20 Hz, and 2.2% and 7° at 1 MHz accordingly with loads between 10 Ω and 10 kg. Finally, the practical use of the front-end with the impedance analyzer is demonstrated in the characterization of the bioimpedance sensor, in saline solutions of varying conductivities (2.5-20 mS/cm) to obtain its cell constant. This article serves as a guide for evaluating and choosing front-end amplifiers for tetrapolar bioimpedance measurements both with and without impedance analyzers for practical/clinical applications and material/sensor characterization

Design and implementation of a multi-modal sensor with on-chip security

With the advancement of technology, wearable devices for fitness tracking, patient monitoring, diagnosis, and disease prevention are finding ways to be woven into modern world reality. CMOS sensors are known to be compact, with low power consumption, making them an inseparable part of wireless medical applications and Internet of Things (IoT). Digital/semi-digital output, by the translation of transmitting data into the frequency domain, takes advantages of both the analog and digital world. However, one of the most critical measures of communication, security, is ignored and not considered for fabrication of an integrated chip. With the advancement of Moore\u27s law and the possibility of having a higher number of transistors and more complex circuits, the feasibility of having on-chip security measures is drawing more attention. One of the fundamental means of secure communication is real-time encryption. Encryption/ciphering occurs when we encode a signal or data, and prevents unauthorized parties from reading or understanding this information. Encryption is the process of transmitting sensitive data securely and with privacy. This measure of security is essential since in biomedical devices, the attacker/hacker can endanger users of IoT or wearable sensors (e.g. attacks at implanted biosensors can cause fatal harm to the user). This work develops 1) A low power and compact multi-modal sensor that can measure temperature and impedance with a quasi-digital output and 2) a low power on-chip signal cipher for real-time data transfer