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Über dieses Buch

This book provides the most comprehensive and consistent survey of the field of IC design for Biological Sensing and Processing. The authors describe a multitude of applications that require custom CMOS IC design and highlight the techniques in analog and mixed-signal circuit design that potentially can cross boundaries and benefit the very wide community of bio-medical engineers.



Chapter 1. CMOS Nano-Pore Technology

In this chapter the principles of nano-pore sensing are discussed with a focus on CMOS interfacing requirements and solutions. The goal is to understand basic functionality of nano-pores, understand the conditions that would enable proper interfacing of nano-pore structures, and define the CMOS readout approaches that overcome limiting factors such as noise performance and area. Section 1 outlines nano-pore sensing, defines unique characteristics of nano-pore-enabled sensing, and describes varieties of nano-pores and their operation principles. Section 2 defines the challenges in interfacing with nano-pores using electrochemical methods and highlights some of the CMOS solutions available in literature. Section 2 also discusses the use of nano-pores in an array format for parallel sensing and characterization, outlines the challenges in nano-pore-facilitated sensing, and describes unique CMOS-based solutions.
Sina Parsnejad, Andrew J. Mason

Chapter 2. Metabolomics on CMOS for Personalised Medicine

The emergence of personalised and precision healthcare requires detailed knowledge of human molecular pathology. Genomics has been transformed by sequencing technologies that can unravel the human genome in 1 day for less than a thousand dollars. Recently, metabolomics, the quantitative measurement of small molecules, has emerged as a field to study an individual’s molecular profile. This is very important because a genome can only give a prediction of an individual’s propensity to a disease – genotyping, while a metabolome can provide immediate diagnosis of biochemical activity in human body – phenotyping. However, the present approach of measuring metabolites depends on large and expensive equipment such as NMR spectroscopy and mass spectroscopy. More importantly, this equipment does not provide a single analytical platform to measure the entire metabolome. CMOS technology has made a major impact in personal mobile computing, digital imaging and communications as part of everyday life. CMOS provides a single integrated platform for sensing technologies, low-cost manufacturing and miniaturisation of microelectronic systems. CMOS has been used successfully to create an all-electronic sequencing technology. We anticipate that CMOS has the potential to allow multiple biomarkers to be monitored in parallel, thus paving the way for metabolome profiling. This review will provide a background to personalised medicine, in terms of genomics and metabolomics, to show the importance for future healthcare delivery. A theoretical background of enzymes for metabolite quantification will also be discussed. A description of DNA microarray technologies will be provided. A background of CMOS chemical sensor systems will be presented for DNA sequencing and metabolite quantification. Finally, a discussion of future CMOS sensor systems, microelectronics and integration technologies that could lead to new “omics” technologies, will be given.
Boon Chong Cheah, David R. S. Cumming

Chapter 3. Flexible Single-Photon Image Sensors

Photon-counting imaging technology has applications in many fields such as fluorescence lifetime imaging microscopy (FLIM), time-resolved Raman spectroscopy, 3D imaging, and even space communications. The requirement to detect single photons with picosecond temporal resolution makes single-photon avalanche photodiode (SPAD) a popular choice. Advanced biomedical imaging applications such as pill cameras, retinal prosthesis, and implantable biocompatible monitoring sensors require a compact image system, which can be implanted into a living body. To meet these requirements, novel single-photon image sensor solution needs to be developed, in which new substrate post-processing and backside illumination or even dual-side illumination are core technologies, with inherent CMOS compatibility as a prerequisite. This chapter proposed and demonstrated the world’s first flexible CMOS single-photon avalanche diode image sensor, providing a suitable solution for implantable biomedical imaging or monitoring applications, and wherever a curved imaging plane is essential.
Pengfei Sun, Ryoichi Ishihara, Edoardo Charbon

Chapter 4. CMOS Multimodal Sensor Array for Biomedical Sensing

Multimodal sensor arrays with potentiometric, amperometric, impedimetric, and photometric sensors have been designed and fabricated by standard CMOS process and post-CMOS process to form gold electrodes and microfluidics. Three types of sensor arrays, 64 × 64 potentiometric and photometric sensor array, 64 × 64 ASSP (application-specific standard product) sensor array, and 512 × 512 high-density sensor array, are implemented in 7 × 7.5 mm2 chip and total power consumption 10 mW using 0.6 μm CMOS technology. In potentiometric and photometric sensor array, electric potential is sensed and outputted as an analog signal by a cascode source-drain follower, and photocurrent is converted to digital signal by current-mode ADC (analog-to-digital converter). In ASSP sensor array, potentiometric, amperometric, impedimetric, and photometric sensors output electric currents which are processed by current mixers and current-mode ADCs in array peripheral circuits. In high-density sensor array, submicron gold electrodes are formed by electroless plating. These sensors are applied to enzyme sensor with redox mediator and counting bacteria/viruses one by one. Stand-alone portable diagnostic inspection system is constructed with 18 × 10 × 5.5 cm3 and 850 g. Power is 5 V 220 mA supplied from USB adapter.
Kazuo Nakazato

Chapter 5. Micro-NMR on CMOS for Biomolecular Sensing

In this chapter, we reported several portable nuclear magnetic resonance (NMR) systems implemented with silicon integrated circuits (IC). Being the initial researchers in the NMR on IC field, we firstly proposed to integrate the complex NMR electronics with the customized IC for portable NMR application with a palm size magnet. Moreover, to manage the samples inside the narrow opening of the portable magnet, we proposed the integration of the digital microfluidic device with the portable NMR system to attain electronic-automated multi-sample management scheme. With the capacitive sensing module of the droplets, the samples can be guided to the NMR sensing site sequentially to reduce labor and experimental time, which facilitates the detection and supports high-throughput sensing. Lastly, we demonstrates a NMR system with magnetic field calibration. This calibration culminates in a robust NMR sensing scheme by modulating the actual magnetic field to a steady value. Thus, the Larmor frequency can be stabilized, and the NMR sensing can work at different environment.
Ka-Meng Lei, Nan Sun, Pui-In Mak, Rui Paulo Martins, Donhee Ham

Chapter 6. Microelectronics for Muscle Fatigue Monitoring Through Surface EMG

Electromyogram (EMG), the recording of the electrical impulses of the muscles, is a rich source of information, which can facilitate such an insight into our muscles and especially their activation and fatigue level. Muscle fatigue has been shown to be one of the most important biofeedback parameters of EMG in rehabilitation, ergonomics and training, by using measured results from the body to change the way we behave, improve our performance and achieve better compliance to rehabilitation. This chapter addresses the challenge of reliably and efficiently estimating a muscle’s fatigue state through monitoring surface EMG signals, with the use of low power integrated circuits. CMOS technology facilitates localised real-time processing to achieve complete miniaturisation, resulting in an information driven system rather than conventionally data driven system. Thus, reducing requirements on data transmission, saving power and increasing the degree of freedom for the user. Several EMG properties progressively change during muscle fatigue and can be quantified in the time and frequency domains using different processing techniques, however this chapter focuses on the measurement of muscle fibre conduction velocity as an indicator of fatigue. A novel bit-stream cross-correlator design that greatly simplifies the sEMG signal without any loss of information is presented for the estimation of the EMG conduction velocity, which is associated with the physiological changes of the muscle during fatigue. The proposed approach is scalable, as several muscle fatigue monitoring SoCs can operate in parallel and periodically relay key information about the muscle, thus reducing data transmission costs and bandwidth requirements.
Pantelis Georgiou, Ermis Koutsos

Chapter 7. Design and Optimization of ICs for Wearable EEG Sensors

In modern clinical practice, scalp electroencephalography (EEG) recording is one of the most important noninvasive procedures to measure the electrical activity of the human brain. EEG has a wide range of applications from brain disorder diagnosis, stroke rehabilitation, brain-computer interface (BCI), and gaming. Conventionally, EEG signal is obtained by placing electrodes on the scalp along with conductive gel to reduce the electrode-tissue contact impedance. The recorded EEG signal between two electrodes is a differential voltage representing the average intensity and spontaneous activities of a group of neurons underlying the skull. In time domain, EEG response with peaks and valleys indicates the power spectrum associate with brain activities. In frequency domain, most of the signal falls within a narrow band of 0.5–100 Hz. Some of the prominent frequency bands are called alpha (7–14 Hz), beta (15–30 Hz), theta (4–7 Hz), and delta (1–4 Hz), each having characteristic neurophysiological traits.
Jiawei Xu, Rachit Mohan, Nick Van Helleputte, Srinjoy Mitra

Chapter 8. Circuits and Systems for Biosensing with Microultrasound

Ultrasound imaging is a well-established, noninvasive imaging modality used in many clinical procedures. New developments in high-resolution microultrasound are well suited to biosensing, including applications such as material characterisation, biometrics and chemical sensing. Electronic system design for ultrasound and microultrasound is most commonly associated with the use of piezoelectric transducers to generate and sense the ultrasonic pressure waves. This chapter covers the basics of ultrasound physics and piezoelectric transducers as well as their context within the larger field of biosensing. An example of an ultrasound imaging system is presented, and the availability and suitability of commercial solutions are discussed in comparison to individual approaches seen in the research domain. Finally, possible variations in ultrasound device characteristics are discussed, and the impact of these and overall system concerns on ASIC development is considered.
Holly Susan Lay, Sandy Cochran

Chapter 9. High-Density CMOS Neural Probes

Silicon neural probes for high-density neural recording have become the preferred tool for a number of electrophysiologists around the world. Even though it has a great promise, the technology is still in its infancy. It has now become possible to integrate high-performance CMOS circuits right on the silicon probes, thus increasing the signal quality and going beyond the geometrical limits posed by the shape of the probe. Here we do a systematic review of various trade-offs associated with designing a monolithic CMOS neural probe and providing examples of some of the state-of-the-art solutions.
Bogdan Raducanu, Carolina Mora Lopez, Srinjoy Mitra

Chapter 10. Photonic Interaction with the Nervous System

Optogenetics is a technique to genetically photosensitize neural tissue for both sensing and stimulus. Since its discovery in 2003, it has led to numerous scientific discoveries in basic neuroscience. Now, various groups are attempting to utilise the technique for neuroprosthetic therapies. This chapter explores the background of the technique and engineering approaches to its utilisation.
Patrick Degenaar

Chapter 11. Implantable Microsystems for Personalised Anticancer Therapy

The Implantable Microsystems for Personalised Anti-Cancer Therapy (IMPACT) project aims to produce an implantable wireless sensor device for monitoring tumour physiology. Real-time measurements will be used to improve radiotherapy by allowing treatment to be responsively delivered at the most effective time and location. We are developing miniaturised microfabricated sensors for measuring local oxygen concentration and pH within the tumour, using technologies that are amenable to integration on CMOS. In addition, we have established proof of concept for a range of electrochemical biosensors that can respond to enzyme biomarkers. Together these sensors will allow comprehensive monitoring of tissue physiology before and after radiotherapy treatment. For clinical use, the complete system will be equipped with circuits for wireless power and communications and packaged in biocompatible materials. This is a very challenging application for sensors integrated on CMOS. Here we provide a brief background to medical aspects of the work and describe our progress towards solving the engineering challenges it has presented.
Jamie R. K. Marland, Ewen O. Blair, Brian W. Flynn, Eva González-Fernández, Liyu Huang, Ian H. Kunkler, Stewart Smith, Matteo Staderini, Andreas Tsiamis, Carol Ward, Alan F. Murray

Chapter 12. Compressed Sensing for High Density Neural Recording

One of the major challenges in large scale electrophysiology recording devices is the volume of data generated. Typically, each electrode samples the neural signal at 30 KHz with 10 bits digital resolution, a typical speed for neural action potentials acquisition. Hence, a 1000 channel neural probe generates data on the order of 300 Mbits per second. For neuroscientists, this presents an enormous problem in both data transmission and data analysis. Recently, as the demand for high density and distributed neural recording devices grows, tackling the problem of data compression and transmission has become extremely urgent. In this chapter, we first summarize a number of techniques used for neural signal compression. We then focus on the recent development on the use of compressed sensing theory to design more efficient high density neural recording circuits.
Jie Zhang, Tao Xiong, Srinjoy Mitra, Ralph Etienne-Cummings

Chapter 13. Very Large-Scale Neuromorphic Systems for Biological Signal Processing

This chapter is a white paper describing a platform for scaled-up neuromorphic systems to ‘human brain size’ complexity. Such a system will be necessary for massive search and analysis tasks while interacting with biological data. This system would consist of similar number of neurons and synapses as in an adult human brain. One of the largest bottlenecks is the huge synaptic complexity that would result from connecting billions of neurons. The purpose of this chapter is to describe a feasible architecture that could handle the enormous communication bandwidth necessary for such a large-scale neuromorphic system. The proposed approach is grounded in the assumption that we would only be able to appreciate the utility of a neuromorphic system when it is somewhat similar to the human brain in terms of energy consumption and size. Inspired by the recent advancements in SoC architecture, a novel scalable intercluster communication network is proposed here. A particularly useful instantiation of this occurs for the global synaptic communication, interconnecting the local clusters of synapse arrays. The core of the proposed solution is a novel switching architecture in the CMOS back end of line (BEOL) that is expected to be extremely power efficient. In contrast to a fixed predefined bus that is shared over all connected local clusters, the proposed solution will allow a multitude of dedicated point-to-point connections that can be switched dynamically.
Francky Catthoor, Srinjoy Mitra, Anup Das, Siebren Schaafsma

Erratum to: CMOS Nano-Pore Technology

Without Abstract
Sina Parsnejad, Andrew J. Mason


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