Long-term Health Monitoring System Research Articles

Over 25-year monitoring of the Tsing Ma suspension bridge in Hong Kong

AbstractBridges in service are subjected to environmental and load actions, but their status and conditions are typically unknown. Health monitoring systems have been installed on long-span bridges to monitor their loads and the associated responses in real time. Since 1997, the Tsing Ma suspension bridge in Hong Kong has been the world’s first of the type equipped with a long-term health monitoring system. For the first time, this study reports the first-hand field monitoring data of the bridge from 1997 to 2022. The 26-year data provide an invaluable and rare opportunity to examine the long-term characteristics of the loads, bridge responses, and their relationships, thereby enabling the assessment of the bridge’s load evolution and structural condition over time. Results show that traffic loads have remained stable after 2007, highway vehicles kept increasing until the COVID-19 pandemic in 2020, the annual maximum deck temperature continued to increase at a rate of 0.51 °C/decade, typhoon durations increased by 2.5 h/year, and monsoon speeds decreased and became dispersed and variable. For the bridge responses, deck displacement is governed by the varying temperature. Natural frequencies in the past 26 years were almost unchanged. The overall condition of the bridge is very satisfactory. Current status and recent update of the health monitoring system are also reported. Lastly, prospects of bridge health monitoring are discussed. This study is the first to report the over one-quarter century status of a structural health monitoring system and the behavior of a long-span suspension bridge. This research provides a benchmark for many other bridge monitoring systems worldwide.

The effect of chlorine/argentum atomic ratios on electrochemical behaviors and signal acquisition abilities of embroidered electrodes for bio-potential signal measurement

Bio-potential dry electrode is an important part of smart garments or wearable devices for monitoring bio-potential signals. In this work, embroidered electrodes are developed by embroidering silver-plated yarns in woven fabric. Then, AgCl is electrochemically deposited on silver-plated yarns in the embroidered electrode, and the chlorine/argentum (Cl/Ag) atomic ratios can be adjusted by the chlorination time. Moreover, a novel active evaluation system of wearable bio-potential electrodes developed by our group is utilized to evaluate the performance of the embroidered electrodes, and two novel indexes (bio-potential phase shift and voltage amplitude attenuation) were presented for evaluating the performance of embroidered electrodes. Results show that the chlorination of silver-plated yarns can improve the performance of embroidered electrodes. The electrochemical behaviors and signal acquisition abilities of the embroidered electrodes can be affected by Cl/Ag atomic ratios. The embroidered electrodes with the Cl/Ag atomic ratios of 62% (E-90) have the lowest impedance (3364 ± 894 O), and their static open-circuit potential and dynamic open-circuit potential variation are all less than 7 mV. During the standard ECG signal test, E-90 shows the minimum bio-potential phase shift (0.011 s), voltage amplitude attenuation (11.768%), noise amplitude (0.025 mV), and maximum signal to noise (41 dB). The noise amplitude of human body ECG of E-90 is also the lowest (0.013 mV) and signal to noise is the maximum (40.996 dB). The embroidered electrodes have broad application prospects in long-term health-monitoring system.

RapidHARe: A computationally inexpensive method for real-time human activity recognition from wearable sensors

Recent human activity recognition (HAR) methods, based on on-body inertial sensors, have achieved increasing performance; however, this is at the expense of longer CPU calculations and greater energy consumption. Therefore, these complex models might not be suitable for real-time prediction in mobile systems, e.g., in elder-care support and long-term health-monitoring systems. Here, we present a new method called RapidHARe for real-time human activity recognition based on modeling the distribution of a raw data in a half-second context window using dynamic Bayesian networks. Our method does not employ any dynamic-programming-based algorithms, which are notoriously slow for inference, nor does it employ feature extraction or selection methods. In our comparative tests, we show that RapidHARe is an extremely fast predictor, one and a half times faster than artificial neural networks (ANNs) methods, and more than eight times faster than recurrent neural networks (RNNs) and hidden Markov models (HMMs). Moreover, in performance, RapidHare achieves an F1 score of 94.27\% and accuracy of 98.94\%, and when compared to ANN, RNN, HMM, it reduces the F1-score error rate by 45\%, 65\%, and 63\% and the accuracy error rate by 41\%, 55\%, and 62\%, respectively. Therefore, RapidHARe is suitable for real-time recognition in mobile devices.

An improved genetic algorithm for increasing the addressing accuracy of encoding fiber Bragg grating sensor network

Abstract Large-capacity encoding fiber Bragg grating (FBG) sensor network is widely used in modern long-term health monitoring system. Encoding FBG sensors have greatly improved the capacity of distributed FBG sensor network. However, the error of addressing increases correspondingly with the enlarging of capacity. To address the issue, an improved algorithm called genetic tracking algorithm (GTA) is proposed in the paper. In the GTA, for improving the success rate of matching and reducing the large number of redundant matching operations generated by sequential matching, the individuals are designed based on the feasible matching. Then, two kinds of self-crossover ways and a dynamic variation during mutation process are designed to increase the diversity of individuals and to avoid falling into local optimum. Meanwhile, an assistant decision is proposed to handle the issue that the GTA cannot solve when the variation of sensor information is highly overlapped. The simulation results indicate that the proposed GTA has higher accuracy compared with the traditional tracking algorithm and the enhanced tracking algorithm. In order to address the problems of spectrum fragmentation and low sharing degree of spectrum resources in survivable.

Structural health monitoring of a newly built high-piled wharf in a harbor with fiber Bragg grating sensor technology: design and deployment

Structural health monitoring (SHM) of civil infrastructure using fiber Bragg grating sensor networks (FBGSNs) has received significant public attention in recent years. However, there is currently little research on the health-monitoring technology of high-piled wharfs in coastal ports using the fiber Bragg grating (FBG) sensor technique. The benefits of FBG sensors are their small size, light weight, lack of conductivity, resistance corrosion, multiplexing ability and immunity to electromagnetic interference. Based on the properties of high-piled wharfs in coastal ports and servicing seawater environment and the benefits of FBG sensors, the SHM system for a high-piled wharf in the Tianjin Port of China is devised and deployed partly using the FBG sensor technique. In addition, the health-monitoring parameters are proposed. The system can monitor the structural mechanical properties and durability, which provides a state-of-the-art mean to monitor the health conditions of the wharf and display the monitored data with the BIM technique. In total, 289 FBG stain sensors, 87 FBG temperature sensors, 20 FBG obliquity sensors, 16 FBG pressure sensors, 8 FBG acceleration sensors and 4 anode ladders are installed in the components of the back platform and front platform. After the installation of some components in the wharf construction site, the good signal that each sensor measures demonstrates the suitability of the sensor setup methods, and it is proper for the full-scale, continuous, autonomous SHM deployment for the high-piled wharf in the costal port. The South 27# Wharf SHM system constitutes the largest deployment of FBG sensors for wharf structures in costal ports to date. This deployment demonstrates the strong potential of FBGSNs to monitor the health of large-scale coastal wharf structures. This study can provide a reference to the long-term health-monitoring system deployment for high-piled wharf structures in coastal ports.

Wearable Devices in Medical Internet of Things: Scientific Research and Commercially Available Devices.

ObjectivesWearable devices are currently at the heart of just about every discussion related to the Internet of Things. The requirement for self-health monitoring and preventive medicine is increasing due to the projected dramatic increase in the number of elderly people until 2020. Developed technologies are truly able to reduce the overall costs for prevention and monitoring. This is possible by constantly monitoring health indicators in various areas, and in particular, wearable devices are considered to carry this task out. These wearable devices and mobile apps now have been integrated with telemedicine and telehealth efficiently, to structure the medical Internet of Things. This paper reviews wearable health care devices both in scientific papers and commercial efforts.MethodsMIoT is demonstrated through a defined architecture design, including hardware and software dealing with wearable devices, sensors, smart phones, medical application, and medical station analyzers for further diagnosis and data storage.ResultsWearables, with the help of improved technology have been developed greatly and are considered reliable tools for long-term health monitoring systems. These are applied in the observation of a large variety of health monitoring indicators in the environment, vital signs, and fitness.ConclusionsWearable devices are now used for a wide range of healthcare observation. One of the most important elements essential in data collection is the sensor. During recent years with improvement in semiconductor technology, sensors have made investigation of a full range of parameters closer to realization.

Long Term Application of a Vehicle-Based Health Monitoring System to Short and Medium Span Bridges and Damage Detection Sensitivity

Largest portion of the bridge stock in almost any country and bridge owning organisation consists on ordinary bridges that has short or medium spans and are now deteriorating due to aging, etc. Therefore, it is becoming an important social concern to develop and put to practical use simple and efficient health monitoring systems for existing short and medium span (10 - 30 m) bridges. In this paper, one practical solution to the problem for condition assessment of short and medium span bridges was discussed. A vehicle-based measurement with a public bus as part of a public transit system (called “Bus monitoring system”) has been developed to be capable of detecting damage that may affect the structural safety of a bridge from long term vibration measurement data collected while the vehicle (bus) crossed the target bridges. This paper systematically describes how the system has been developed. The bus monitoring system aims to detect the transition from the damage acceleration period, in which the structural safety of an aged bridge declines sharply, to the deterioration period by continually monitoring the bridge of interest. To evaluate the practicality of the newly developed bus monitoring system, it has been field-tested over a period of about four years by using an in-service fixed-route bus operating on a bus route in the city of Ube, Yamaguchi Prefecture, Japan. The verification results thus obtained are also described in this paper. This study also evaluates the sensitivity of “characteristic deflection”, which is a bridge (health) condition indicator used by the bus monitoring system, in damage detection. Sensitivity of “characteristic deflection” is verified by introducing artificial damage into a bridge that has ended its service life and is awaiting removal. As the results, it will be able to make a rational long-term health monitoring system for existing short and mediumspan bridges, and then the system helps bridge administrators to establish the rational maintenance strategies.

Health Monitoring System Design of Coastal High-Piled Wharf

There is little research on health monitoring technology of coastal ports at present. Based on the characteristics of high-piled wharf in coastal ports and staying in particular environment, the mechanical properties of coastal high-piled wharf is analyzed, and the health monitoring parameters are proposed. Finally, the health monitoring system of coastal high-piled wharf is constructed. And the appropriate structural health monitoring system is designed for standardized front segment of a high-piled wharf in the Tianjin port. The monitoring parameters are proposed, and the sensors and specification parameters are provided to reach the point. The data acquisition and transmission subsystem implementation technology and related indicators are given. This can provide a reference for the long-term health monitoring system construction in coastal high-piled wharf structure.

Features of long-term health monitored strains of a bridge with wavelet analysis

This paper analyses the five years' monitored strains collected from a long-term health monitoring system installed on a bridge with wavelet transform. In the analysis, the monitored strains are pre-processed, features of the monitored data are summarized briefly. The influences of the base functions on the results of wavelet analysis are studied simultaneously. The results show that the db wavelet is a good mother wavelet function in the analysis, and the order N should be larger than 20, but less than 46 in decomposing the monitored strains of the bridge. According to the strain variation features of concrete bridge, the proper decomposition level is 4 in the wavelet multi-resolution analysis. With the present method, the strains caused by random loads and daily sunlight can be accurately extracted from the monitored strains. The decomposed components of the monitored strains show that the amplitudes of the strains caused by random loads, daily sunlight, and annual temperature effect, are about 5με, 25με, and 50με respectively. The structural response under random load is smaller than the other parts.