Smart Sensor Networks For Sensor-Neural Interface

One in every fifty Americans suffers from paralysis, and approximately 23% of paralysis cases are caused by spinal cord injury. To help the spinal cord injured gain functionality of their paralyzed or lost body parts, a sensor-neural-actuator system is commonly used. The system includes: 1) sensor nodes, 2) a central control unit, 3) the neural-computer interface and 4) actuators. This thesis focuses on a sensor-neural interface and presents the research related to circuits for the sensor-neural interface. In Chapter 2, three sensor designs are discussed, including a compressive sampling image sensor, an optical force sensor and a passive scattering force sensor. Chapter 3 discusses the design of the analog front-end circuit for the wireless sensor network system. A low-noise low-power analog front-end circuit in 0.5μm CMOS technology, a 12-bit 1MS/s successive approximation register (SAR) analog-to-digital converter (ADC) in 0.18μm CMOS process and a 6-bit asynchronous level-crossing ADC realized in 0.18μm CMOS process are presented. Chapter 4 shows the design of a low-power impulse-radio ultra-wide-band (IR-UWB) transceiver (TRx) that operates at a data rate of up to 10Mbps, with a power consumption of 4.9pJ/bit transmitted for the transmitter and 1.12nJ/bit received for the receiver. In Chapter 5, a wireless fully event-driven electrogoniometer is presented. The electrogoniometer is implemented using a pair of ultra-wide band (UWB) wireless smart sensor nodes interfacing with low power 3-axis accelerometers. The two smart sensor nodes are configured into a master node and a slave node, respectively. An experimental scenario data analysis shows higher than 90% reduction of the total data throughput using the proposed fully event-driven electrogoniometer to measure joint angle movements when compared with a synchronous Nyquist-rate sampling system. The main contribution of this thesis includes: 1) the sensor designs that emphasize power efficiency and data throughput efficiency; 2) the fully event-driven wireless sensor network system design that minimizes data throughput and optimizes power consumption

Bioelectronic Sensor Nodes for Internet of Bodies

Energy-efficient sensing with Physically-secure communication for bio-sensors on, around and within the Human Body is a major area of research today for development of low-cost healthcare, enabling continuous monitoring and/or secure, perpetual operation. These devices, when used as a network of nodes form the Internet of Bodies (IoB), which poses certain challenges including stringent resource constraints (power/area/computation/memory), simultaneous sensing and communication, and security vulnerabilities as evidenced by the DHS and FDA advisories. One other major challenge is to find an efficient on-body energy harvesting method to support the sensing, communication, and security sub-modules. Due to the limitations in the harvested amount of energy, we require reduction of energy consumed per unit information, making the use of in-sensor analytics/processing imperative. In this paper, we review the challenges and opportunities in low-power sensing, processing and communication, with possible powering modalities for future bio-sensor nodes. Specifically, we analyze, compare and contrast (a) different sensing mechanisms such as voltage/current domain vs time-domain, (b) low-power, secure communication modalities including wireless techniques and human-body communication, and (c) different powering techniques for both wearable devices and implants.Comment: 30 pages, 5 Figures. This is a pre-print version of the article which has been accepted for Publication in Volume 25 of the Annual Review of Biomedical Engineering (2023). Only Personal Use is Permitte

BATTERY LESS, WSN-BASED HEALTH CARE UNIT THAT DRIVES A BACKSCATTERING TRANSMITTER

A potential means to fix minimize power consumption is using asynchronous sensor architectures that sample and transmit data only if a celebration is detected. A celebration-driven sensor consumes minimal power unless of course a celebration is detected. This paper presents the style of asynchronous ECG monitoring and knowledge transmission that cuts down on the circuitry power use of the sensor node without using power gating and requiring neither exterior energy storage devices nor a very like a time reference. The offset calibration is really a typical foreground calibration that's enabled during system startup or manual resetting. The sensor node that is remotely operated by the hub is really a peripheral device from the network that transmits data towards the hub in the recognition of the event. The information processing and memory allocation will be performed through the hub. Therefore, the sensor node can operate from hardly any power. The Two-output items of the ADC are combined and transmitted concurrently, otherwise information could be lost. Employing pulse duration modulation (PDM), the two-bit data stream is combined to create pulses with various time duration for upward conversion and downward conversion. Which means that the transmitter creates a pulse when LT signifies a conversion and U/D defines the time period of this pulse? Within the circuit created for backscattering data transmission, the pulsed signal modulates the 402 MHz RF signal received within the LC network, applying ON-OFF-Keying modulation through transistor. The LC-ADC has both magnitude resolution and time resolution. As time resolution is incorporated within the measurement, the general SNDR is degraded when compared to standalone LNA SNDR

Data Conversion Within Energy Constrained Environments

Within scientific research, engineering, and consumer electronics, there is a multitude of new discrete sensor-interfaced devices. Maintaining high accuracy in signal quantization while staying within the strict power-budget of these devices is a very challenging problem. Traditional paths to solving this problem include researching more energy-efficient digital topologies as well as digital scaling.;This work offers an alternative path to lower-energy expenditure in the quantization stage --- content-dependent sampling of a signal. Instead of sampling at a constant rate, this work explores techniques which allow sampling based upon features of the signal itself through the use of application-dependent analog processing. This work presents an asynchronous sampling paradigm, based off the use of floating-gate-enabled analog circuitry. The basis of this work is developed through the mathematical models necessary for asynchronous sampling, as well the SPICE-compatible models necessary for simulating floating-gate enabled analog circuitry. These base techniques and circuitry are then extended to systems and applications utilizing novel analog-to-digital converter topologies capable of leveraging the non-constant sampling rates for significant sample and power savings

On Application of Wireless Sensor Networks for Healthcare Monitoring

With the recent advances in embedded systems and very low power ,wireless tech­ nologies, there has been a great interest in the development and application of a new class of distributed Wireless body area network for health monitoring. The first part of the thesis presents a remote patient monitoring system within the scope of Body Area Network standardization. In this regime, wireless sensor networks are used to continuously acquire the patient’s Electrocardiogram signs and transmit data to the base station via IEEE.802.15. The personal Server (PS) which is responsible to provide real-time displaying, storing, and analyzing the patient’s vital signs is developed in MATLAB. It also transfers ECG streams in real-time to a remote client such as a physician or medical center through internet. The PS has the potential to be integrated with home or hospital computer systems. A prototype of this system has been developed and implemented. Tlie developed system takes advantage of two important features for healthcare monitoring: (i) ECG data acqui­ sition using wearable sensors and (ii) real-time data remote through internet. The fact that our system is interacting with sensor network nodes using MATLAB makes it distinct from other previous works. The second part is devoted to the study of indoor body-area channel model for 2.4 GHz narrowband communications. To un­ derstand the narrowband radio propagation near the body, several measurements are carried out in two separate environments for different on body locations. On the basis of these measurements, we have characterized the fading statistics on body links and we have provided a physical interpretation of our results

ULTRA LOW POWER CIRCUITS FOR WEARABLE BIOMEDICAL SENSORS

Ph.DDOCTOR OF PHILOSOPH

FPGA based reconfigurable body area network using Nios II and uClinux

This research is focused on identifying an appropriate design for a reconfigurable Body Area Network (BAN). In order to investigate the benefits and drawbacks of the proposed design, a BAN system prototype was built. This system consists of two distinct node types: a slave node and a master node. These nodes communicate using ZigBee radio transceivers. The microcontroller-based slave node acquires sensor data and transmits digitized samples to the master node. The master node is FPGA-based and runs uClinux on a soft-core microcontroller. The purpose of the master node is to receive, process and store digitized sensor data. In order to verify the operation of the BAN system prototype and demonstrate reconfigurability, a specific application was required. Pattern recognition in electrocardiogram (ECG) data was the application used in this work and the MIT-BIH Arrhythmia Database was used as the known data source for verification. A custom test platform was designed and built for the purpose of injecting data from the MIT-BIH Arrhythmia Database into the BAN system. The BAN system designed and built in this work demonstrates the ability to record raw ECG data, detect R-peaks, calculate and record R-R intervals, detect premature ventricular and atrial contractions. As this thesis will identify, many aspects of this BAN system were designed to be highly reconfigurable allowing it to be used for a wide range of BAN applications, in addition to pattern recognition of ECG data

Performance evaluation of wake-up radio based wireless body area network

Abstract. The last decade has been really ambitious in new research and development techniques to reduce energy consumption especially in wireless sensor networks (WSNs). Sensor nodes are usually battery-powered and thus have very limited lifetime. Energy efficiency has been the most important aspect to discuss when talking about wireless body area network (WBAN) in particular, since it is the bottleneck of these networks. Medium access control (MAC) protocols hold the vital position to determine the energy efficiency of a WBAN, which is a key design issue for battery operated sensor nodes. The wake-up radio (WUR) based MAC and physical layer (PHY) have been evaluated in this research work in order to contribute to the energy efficient solutions development. WUR is an on-demand approach in which the node is woken up by the wake-up signal (WUS). A WUS switches a node from sleep mode to wake up mode to start signal transmission and reception. The WUS is transmitted or received by a secondary radio transceiver, which operates on very low power. The energy benefit of using WUR is compared with conventional duty-cycling approach. As the protocol defines the nodes in WUR based network do not waste energy on idle listening and are only awakened when there is a request for communication, therefore, energy consumption is extremely low. The performance of WUR based MAC protocol has been evaluated for both physical layer (PHY) and MAC for transmission of WUS and data. The probabilities of miss detection, false alarm and detection error rates are calculated for PHY and the probabilities of collision and successful data transmission for channel access method Aloha is evaluated. The results are obtained to compute and compare the total energy consumption of WUR based network with duty cycling. The results prove that the WUR based networks have significant potential to improve energy efficiency, in comparison to conventional duty cycling approach especially, in the case of low data-reporting rate applications. The duty cycle approach is better than WUR approach when sufficiently low duty cycle is combined with highly frequent communication between the network nodes

Smart Devices and Systems for Wearable Applications

Wearable technologies need a smooth and unobtrusive integration of electronics and smart materials into textiles. The integration of sensors, actuators and computing technologies able to sense, react and adapt to external stimuli, is the expression of a new generation of wearable devices. The vision of wearable computing describes a system made by embedded, low power and wireless electronics coupled with smart and reliable sensors - as an integrated part of textile structure or directly in contact with the human body. Therefore, such system must maintain its sensing capabilities under the demand of normal clothing or textile substrate, which can impose severe mechanical deformation to the underlying garment/substrate. The objective of this thesis is to introduce a novel technological contribution for the next generation of wearable devices adopting a multidisciplinary approach in which knowledge of circuit design with Ultra-Wide Band and Bluetooth Low Energy technology, realization of smart piezoresistive / piezocapacitive and electro-active material, electro-mechanical characterization, design of read-out circuits and system integration find a fundamental and necessary synergy. The context and the results presented in this thesis follow an “applications driven” method in terms of wearable technology. A proof of concept has been designed and developed for each addressed issue. The solutions proposed are aimed to demonstrate the integration of a touch/pressure sensor into a fabric for space debris detection (CApture DEorbiting Target project), the effectiveness of the Ultra-Wide Band technology as an ultra-low power data transmission option compared with well known Bluetooth (IR-UWB data transmission project) and to solve issues concerning human proximity estimation (IR-UWB Face-to-Face Interaction and Proximity Sensor), wearable actuator for medical applications (EAPtics project) and aerospace physiology countermeasure (Gravity Loading Countermeasure Skinsuit project)