Integrated Low-Loss CMOS Active Rectifier for Wirelessly Powered Devices

A low-loss CMOS full-wave active rectifier is presented. It consists of two dynamically biased and symmetrically matched active diodes each realized by an nMOS switch driven by a 2-ns voltage comparator with reverse-current control. With a load of 1.8-kOmega, the rectified dc voltage is 3.22 V and 1.2 V for a 13.56 MHz ac sinusoidal input voltage of 3.5 V and 1.5 V respectively. It is fabricated in a 0.35-mum CMOS process with an active area of 0.0055 mm ², with no low-threshold devices and on-chip passive components     

Body Heat Powered Wirelessly Wearable System for Real-time Physiological and Biochemical Monitoring

Through harvesting energy from the environment or human body, self-power wearable electronics have an opportunity to break through the limitations of battery supply and achieving long-term continuous operation. Here, a wireless wearable monitoring system driven entirely by body heat is implemented. Based on the principle of maximizing heat utilization, while optimizing internal resistance and heat dissipation, the stretchable TEG improves the power density of previous similar devices from only a few microwatts per square centimeter to tens and makes it possible to continuously drive wireless wearable electronic systems. Furthermore, ceaseless self-power energy gives wearable electronics unparalleled continuous working ability, which can realize the tracking and monitoring of biochemical and physiological indicators at different time scale. A practical system demonstrates the ability to real-time monitor heart rate, sweat ingredient and body motion at a high sampling rate. This study marks an important advance of self-powered wearable electronics for wirelessly real-time healthy monitoring.     

A 5.2 mW Self-Configured Wearable Body Sensor Network Controller and a 12 $mu$ W Wirelessly Powered Sensor for a Continuous Health Monitoring System

A self-configured body sensor network controller and a high efficiency wirelessly powered sensor are presented for a wearable, continuous health monitoring system. The sensor chip harvests its power from the surrounding health monitoring band using an Adaptive Threshold Rectifier (ATR) with 54.9% efficiency, and it consumes 12 ?W to implement an electrocardiogram (ECG) analog front-end and an ADC. The ATR is implemented with a standard CMOS process for low cost. The adhesive bandage type sensor patch is composed of the sensor chip, a Planar-Fashionable Circuit Board (P-FCB) inductor, and a pair of dry P-FCB electrodes. The dry P-FCB electrodes enable long term monitoring without skin irritation. The network controller automatically locates the sensor position, configures the sensor type (self-configuration), wirelessly provides power to the configured sensors, and transacts data with only the selected sensors while dissipating 5.2 mW at a single 1.8 V supply. Both the sensor and the health monitoring band are implemented using P-FCB for enhanced wearability and for lower production cost. The sensor chip and the network controller chip occupy 4.8 mm² and 15.0 mm², respectively, including pads, in standard 0.18 ?m 1P6M CMOS technology.     

A Robust Wearable Point-of-Care CNT-Based Strain Sensor for Wirelessly Monitoring Throat-Related Illnesses

Point-of-care testing (POC) has the ability to detect chronic and infectious diseases early or at the time of occurrence and provide a state-of-the-art personalized healthcare system. Recently, wearable and flexible sensors have been employed to analyze sweat, glucose, blood, and human skin conditions. However, a flexible sensing system that allows for the real-time monitoring of throat-related illnesses, such as salivary parotid gland swelling caused by flu and mumps, is necessary. Here, for the first time, a wearable, highly flexible, and stretchable piezoresistive sensing patch based on carbon nanotubes (CNTs) is reported, which can record muscle expansion or relaxation in real-time, and thus act as a next-generation POC sensor. The patch offers an excellent gauge factor for in-plane stretching and spatial expansion with low hysteresis. The actual extent of muscle expansion is calculated and the gauge factor for applications entailing volumetric deformations is redefined. Additionally, a bluetooth-low-energy system that tracks muscle activity in real-time and transmits the output signals wirelessly to a smartphone app is utilized. Numerical calculations verify that the low stress and strain lead to excellent mechanical reliability and repeatability. Finally, a dummy muscle is inflated using a pneumatic-based actuator to demonstrate the application of the affixed wearable next-generation POC sensor.     

单光纤传输光推动便携式压力测量仪的研究

介绍了用单根光纤传输测量信号和功率信号的光功率推动液体压力测量仪及其工作原理。该仪器以电容式压力传感器的δ元件作为压力检测元件，采用低功耗前置器电路和简单直杆结构，实现了便携式测量。测量范围为O～100kPa，精度为O．01kPa。     

Optically Powered Pressure Sensor with Optical Fiber Link

An optically powered sensor for measuring pressure which is linked by optical fiber is developed in new scheme.Its pulse positio modulation(PPM)optical signal and op-tical supply power for electronics in probe are transmitted via a single optical fiber.The opti-cal power is carried by a 1300nm laser diode(LD)and the sensing data are carried by a 850nm LED.The remote ptobe uses all CMOS chips and particular modulations(PPM and PWM).Its electrical consumption including signal manipulation and LED driven current from optically converted is less than 100μW.The laser diode supplies 5mW optical power into fhe fiber.A Photodetector converts suffichently this power into electrical power to drive the whole probe operation.The optically powered distance gets up to 500m.The novel sen-sor combines optical fiber and electronies technology into a system.Because of using the prin-ciple of ratio measurement between measured and reference signals.as well as light feedback,the system is available with high reliab,outstanding accuracy and repeatability.     

基于可变阈值的无线传感网络异常值检测

定义了新的异常因子,将数据分为正常、异常、临界3种状态,并在此基础上构建了一个基于动态阈值的异常值检测模型。在修正马尔科夫假设的基础上,给出动态阈值的更新方法。算法在无需训练集的条件下,实现了在线的实时异常值检测。仿真实验表明,算法在保持较高检测精度的同时,维持了较低的误报率。     

Distributed Target Detection in Sensor Networks Using Scan Statistics

We introduce a sequential procedure to detect a target with distributed sensors in a two dimensional region. The detection is carried out in a mobile fusion center which successively counts the number of binary decisions reported by local sensors lying inside its moving field of view. This is a two-dimensional scan statistic-an emerging tool from the statistics field that has been applied to a variety of anomaly detection problems such as of epidemics or computer intrusion, but that seems to be unfamiliar to the signal processing community. We show that an optimal size of the field of view exists. We compare the sequential two-dimensional scan statistic test and two other tests. Results for system level detection are presented.     

Transcatheter Self‐Powered Ultrasensitive Endocardial Pressure Sensor

Changes in endocardial pressure (EP) have important clinical significance for heart failure patients with impaired cardiac function. As a vital parameter for evaluating cardiac function, EP is commonly monitored by invasive and expensive cardiac catheterization, which is not feasible for long‐term and continuous data collection. In this work, a miniaturized, flexible, and self‐powered endocardial pressure sensor (SEPS) based on triboelectric nanogenerator (TENG), which is integrated with a surgical catheter for minimally invasive implantation, is reported. In a porcine model, SEPS is implanted into the left ventricle and the left atrium. The SEPS has a good response both in low‐ and high‐pressure environments. The SEPS achieves the ultrasensitivity, real‐time monitoring, and mechanical stability in vivo. An excellent linearity (R ² = 0.997) with a sensitivity of 1.195 mV mmHg^?1 is obtained. Furthermore, cardiac arrhythmias such as ventricular fibrillation and ventricular premature contraction can also be detected by SEPS. The device may promote the development of miniature implantable medical sensors for monitoring and diagnosis of cardiovascular diseases.     

改进型支架压力传感器设计

为了精确测量支架压力的变化情况,给出了一种改进型支架压力传感器设计方案,分析了电阻应变式传感器的工作原理,阐述了如何采用全桥差动电路采集微弱的电阻变化信号.给出了接口电路硬件设计和部分软件流程.在使用过程中设备工作性能稳定,测量精度高,达到了预期工作目标.     

New Resonant Force Sensor Powered by Stabilized LD Source

On the basis of optically powered sensor principles,this paper introduces a practical scheme of an optically powered force sensor using a piezoelectric crystal work-ing in close-loop resonant mode.A 3 mW LD stabilixed is used as optical source.The op-tical powering distance reaches 500m while the total power consumption of the mirco-power measuring head is only 0.275mW.The key technical problems of the sensors are presented as well as experimentral results.     

利用光外差检测技术的光纤温度传感器

本文报导以频率稳定的纵向塞曼激光器为光源,高度内禀双折射偏振保持光纤为传感元件,并利用光外差检测技术而制作的温度传感器。理论分析了实验系统工作机理,并给出系统主要性能参数。     

Adaptive Sensor Fault Detection and Identification Using Particle Filter Algorithms

Sensor fault detection and identification (FDI) is a process of detecting and validating sensor's fault status. Because FDI guarantees system reliable performance, it has received much attention recently. In this paper, we address the problem of online sensor fault identification and validation. For a physical sensor validation system, it contains transitions between sensor normal and faulty states, change of system parameters, and a fusion of noisy readings. A common dynamic state-space model with continuous state variables and observations cannot handle this problem. To circumvent this limitation, we adopt a Markov switch dynamic state-space model to simulate the system: we use discrete-state variables to model sensor states and continuous variables to track the change of the system parameters. Problems in Markov switch dynamic state-space model can be well solved by particle filters, which are popularly used in solving problems in digital communications. Among them, mixture Kalman filter (MKF) and stochastic $M$-algorithm (SMA) have very good performance, both in accuracy and efficiency. In this paper, we plan to incorporate these two algorithms into the sensor validation problem, and compare the effectiveness and complexity of MKF and SMA methods under different situations in the simulation with an existing algorithm---interactive multiple models.      

Hybrid Anomaly Detection by Using Clustering for Wireless Sensor Network

Wireless Personal Communications - Performance of wireless sensor network are highly prone to network anomalies particularly to misdirection attacks and blackhole attacks. Therefor intrusion...     

基于室内无线传感器网络射频信号的老年人跌倒检测研究

利用无线信号的自然衰减,在不显著增加通信开销的基础上,提出了一种新的老年人跌倒行为的检测方法.给出阶段相关性这一概念并用以区分体域传感器网络节点与室内传感器网络节点信号在人运动与静止条件下的统计相关性.给出了最小通信决策集合的概念,通过对比最小通信决策集合的内容,提出了老年人位置估计方法和跌倒行为检测算法;利用仿真工具...     

光纤甲烷传感复用系统的研究

基于甲烷气体在近红外波段对光的吸收机理,提出一种新安全型光纤甲烷传感器系统.系统以ELED作为宽带入射光源,利用甲烷在光纤低损耗窗口波段的吸收特性,利用波分复用技术和直角棱镜吸收池,并采用提高波长检测精度的DMF(数字匹配滤波器)对微弱信号进行处理,使得系统的灵敏度达到120 ppm.实验研究表明,此系统的稳定性和检测精度还需进一步提高.     

Jammed Node Detection and Routing in a Multihop Wireless Sensor Network Using Hybrid Techniques

Wireless Personal Communications - Wireless sensor networks are susceptible to various Denial-of-Service attacks due to their open deployment. Jamming attack at the physical layer is a type of...     

Minimum Path Exposure and Detection Interval Setting for Target Detection Using Wireless Sensor Network

Sensor network generally detects target at a fixed frequency. Detection interval means time spacing between two adjacent detection attempts. While designing a sensor network for detection of target intrusion in a specific region, the interval should be carefully set with trade-off between power consumption and detection performance. This is because redundant power may be consumed if it is too short and the target may be missed if too long. In this paper, we study the determination of the maximum detection interval (MDI) with specified detection performance. Path exposure is adopted as a performance metric. For detection-oriented application, a novel method to evaluate the minimum path exposure (MPE) is developed. Then the MDI problem is formulated and its solution is presented. The factors influencing the MDI are extensively simulated.

Distributed Detection in Wireless Sensor Networks Using A Multiple Access Channel

Distributed detection in a one-dimensional (1-D) sensor network with correlated sensor observations, as exemplified by two problems-detection of a deterministic signal in correlated Gaussian noise and detection of a first-order autoregressive [AR(1)] signal in independent Gaussian noise, is studied in this paper. In contrast with the traditional approach where a bank of dedicated parallel access channels (PAC) is used for transmitting the sensor observations to the fusion center, we explore the possibility of employing a shared multiple access channel (MAC), which significantly reduces the bandwidth requirement or detection delay. We assume that local observations are mapped according to a certain function subject to a power constraint. Using the large deviation approach, we demonstrate that for the deterministic signal in correlated noise problem, with a specially chosen mapping rule, MAC fusion achieves the same asymptotic performance as centralized detection under the average power constraint (APC), while there is always a loss in error exponents associated with PAC fusion. Under the total power constraint (TPC), MAC fusion still results in exponential decay in error exponents with the number of sensors, while PAC fusion does not. For the AR signal problem, we propose a suboptimal MAC mapping rule which performs closely to centralized detection for weakly correlated signals at almost all signal-to-noise ratio (SNR) values, and for heavily correlated signals when SNR is either high or low. Finally, we show that although the lack of MAC synchronization always causes a degradation in error exponents, such degradation is negligible when the phase mismatch among sensors is sufficiently small     

Data Fault Detection in Wireless Sensor Networks Using Machine Learning Techniques

Wireless Personal Communications - Wireless Sensor Network (WSN) is a wireless network that consists of spatially distributed autonomous devices with sophisticated subsystem called sensors to...