Low power CMOS IC, biosensor and wireless power transfer techniques for wireless sensor network application

The emerging field of wireless sensor network (WSN) is receiving great attention due to the interest in healthcare. Traditional battery-powered devices suffer from large size, weight and secondary replacement surgery after the battery life-time which is often not desired, especially for an implantable application. Thus an energy harvesting method needs to be investigated. In addition to energy harvesting, the sensor network needs to be low power to extend the wireless power transfer distance and meet the regulation on RF power exposed to human tissue (specific absorption ratio). Also, miniature sensor integration is another challenge since most of the commercial sensors have rigid form or have a bulky size. The objective of this thesis is to provide solutions to the aforementioned challenges

A Low-Power BFSK/OOK Transmitter for Wireless Sensors

In recent years, significant improvements in semiconductor technology have allowed consistent development of wireless chipsets in terms of functionality and form factor. This has opened up a broad range of applications for implantable wireless sensors and telemetry devices in multiple categories, such as military, industrial, and medical uses. The nature of these applications often requires the wireless sensors to be low-weight and energy-efficient to achieve long battery life. Among the various functions of these sensors, the communication block, used to transmit the gathered data, is typically the most power-hungry block. In typical wireless sensor networks, transmission range is below 10 meters and required radiated power is below 1 milliwatt. In such cases, power consumption of the frequency-synthesis circuits prior to the power amplifier of the transmitter becomes significant. Reducing this power consumption is currently the focus of various research endeavors. A popular method of achieving this goal is using a direct-modulation transmitter where the generated carrier is directly modulated with baseband data using simple modulation schemes. Among the different variations of direct-modulation transmitters, transmitters using unlocked digitally-controlled oscillators and transmitters with injection or resonator-locked oscillators are widely investigated because of their simple structure. These transmitters can achieve low-power and stable operation either with the help of recalibration or by sacrificing tuning capability. In contrast, phase-locked-loop-based (PLL) transmitters are less researched. The PLL uses a feedback loop to lock the carrier to a reference frequency with a programmable ratio and thus achieves good frequency stability and convenient tunability. This work focuses on PLL-based transmitters. The initial goal of this work is to reduce the power consumption of the oscillator and frequency divider, the two most power-consuming blocks in a PLL. Novel topologies for these two blocks are proposed which achieve ultra-low-power operation. Along with measured performance, mathematical analysis to derive rule-of-thumb design approaches are presented. Finally, the full transmitter is implemented using these blocks in a 130 nanometer CMOS process and is successfully tested for low-power operation

Design and modeling of wireless link for biomedical implantable applications

Ph.DDOCTOR OF PHILOSOPH

Compressive Sensing with Low-Power Transfer and Accurate Reconstruction of EEG Signals

Tele-monitoring of EEG in WBAN is essential as EEG is the most powerful physiological parameters to diagnose any neurological disorder. Generally, EEG signal needs to record for longer periods which results in a large volume of data leading to huge storage and communication bandwidth requirements in WBAN. Moreover, WBAN sensor nodes are battery operated which consumes lots of energy. The aim of this research is, therefore, low power transmission of EEG signal over WBAN and its accurate reconstruction at the receiver to enable continuous online-monitoring of EEG and real time feedback to the patients from the medical experts. To reduce data rate and consequently reduce power consumption, compressive sensing (CS) may be employed prior to transmission. Nonetheless, for EEG signals, the accuracy of reconstruction of the signal with CS depends on a suitable dictionary in which the signal is sparse. As the EEG signal is not sparse in either time or frequency domain, identifying an appropriate dictionary is paramount. There are a plethora of choices for the dictionary to be used. Wavelet bases are of interest due to the availability of associated systems and methods. However, the attributes of wavelet bases that can lead to good quality of reconstruction are not well understood. For the first time in this study, it is demonstrated that in selecting wavelet dictionaries, the incoherence with the sensing matrix and the number of vanishing moments of the dictionary should be considered at the same time. In this research, a framework is proposed for the selection of an appropriate wavelet dictionary for EEG signal which is used in tandem with sparse binary matrix (SBM) as the sensing matrix and ST-SBL method as the reconstruction algorithm. Beylkin (highly incoherent with SBM and relatively high number of vanishing moments) is identified as the best dictionary to be used amongst the dictionaries are evaluated in this thesis. The power requirements for the proposed framework are also quantified using a power model. The outcomes will assist to realize the computational complexity and online implementation requirements of CS for transmitting EEG in WBAN. The proposed approach facilitates the energy savings budget well into the microwatts range, ensuring a significant savings of battery life and overall system’s power. The study is intended to create a strong base for the use of EEG in the high-accuracy and low-power based biomedical applications in WBAN

LOW-POWER FREQUENCY SYNTHESIS BASED ON INJECTION LOCKING

Ph.DDOCTOR OF PHILOSOPH

A self-powered single-chip wireless sensor platform

Internet of things” require a large array of low-cost sensor nodes, wireless connectivity, low power operation and system intelligence. On the other hand, wireless biomedical implants demand additional specifications including small form factor, a choice of wireless operating frequencies within the window for minimum tissue loss and bio-compatibility This thesis describes a low power and low-cost internet of things system suitable for implant applications that is implemented in its entirety on a single standard CMOS chip with an area smaller than 0.5 mm2. The chip includes integrated sensors, ultra-low-power transceivers, and additional interface and digital control electronics while it does not require a battery or complex packaging schemes. It is powered through electromagnetic (EM) radiation using its on-chip miniature antenna that also assists with transmit and receive functions. The chip can operate at a short distance (a few centimeters) from an EM source that also serves as its wireless link. Design methodology, system simulation and optimization and early measurement results are presented

Recent Advances on Implantable Wireless Sensor Networks

Implantable electronic devices are undergoing a miniaturization age, becoming more efficient and yet more powerful as well. Biomedical sensors are used to monitor a multitude of physiological parameters, such as glucose levels, blood pressure and neural activity. A group of sensors working together in the human body is the main component of a body area network, which is a wireless sensor network applied to the human body. In this chapter, applications of wireless biomedical sensors are presented, along with state-of-the-art communication and powering mechanisms of these devices. Furthermore, recent integration methods that allow the sensors to become smaller and more suitable for implantation are summarized. For individual sensors to become a body area network (BAN), they must form a network and work together. Issues that must be addressed when developing these networks are detailed and, finally, mobility methods for implanted sensors are presented

Microwave Antennas Suggested for Biomedical Implantation

In the twenty-first century, there is an enormous development in various areas: microwave sensors have played an important role in medical devices, because of population growth and public awareness of the health of medical devices, they have become an ever-increasing technology. Microwave antenna sensors can be used to monitor human body temperature, implantable defibrillators, pacemakers, continuous glucose monitoring, heart failure detection, and so on. Antennas are also used as flexible sensors to monitor physiological parameters. Therefore, microwave sensors are used for wireless communication in various biomedical applications. The design of such antennas has gained considerable attention for dealing with issues such as miniaturization, biocompatibility, patient safety, improvement in communication quality, etc. The objective of this paper is to prove an overview of the requirements, design steps, and testing of a microwave antenna used in biomedical implantation. In this chapter, various antennas used in medical applications are described in detail. Also, antenna designing and testing requirements are discussed

Recent Advances in Neural Recording Microsystems

The accelerating pace of research in neuroscience has created a considerable demand for neural interfacing microsystems capable of monitoring the activity of large groups of neurons. These emerging tools have revealed a tremendous potential for the advancement of knowledge in brain research and for the development of useful clinical applications. They can extract the relevant control signals directly from the brain enabling individuals with severe disabilities to communicate their intentions to other devices, like computers or various prostheses. Such microsystems are self-contained devices composed of a neural probe attached with an integrated circuit for extracting neural signals from multiple channels, and transferring the data outside the body. The greatest challenge facing development of such emerging devices into viable clinical systems involves addressing their small form factor and low-power consumption constraints, while providing superior resolution. In this paper, we survey the recent progress in the design and the implementation of multi-channel neural recording Microsystems, with particular emphasis on the design of recording and telemetry electronics. An overview of the numerous neural signal modalities is given and the existing microsystem topologies are covered. We present energy-efficient sensory circuits to retrieve weak signals from neural probes and we compare them. We cover data management and smart power scheduling approaches, and we review advances in low-power telemetry. Finally, we conclude by summarizing the remaining challenges and by highlighting the emerging trends in the field