Monitoring Strategic Hydraulic Infrastructures by Brillouin Distributed Fiber Optic Sensors

We present a case study of a Structural Health Monitoring (SHM) hybrid system based on Brillouin Distributed Fiber Optic Sensors (D-FOS), Vibrating Wire (VW) extensometers and temperature probes for an existing historical water penstock bridge positioned in a mountain valley in Valle d’Aosta Region, Northwestern Italy. We assessed Brillouin D-FOS performances for this kind of infrastructure, characterized by a complex structural layout and located in a harsh environment. A comparison with the more traditional strain monitoring technology offered by VW strain gauges was performed. The D-FOS strain cable has been bonded to the concrete members using a polyurethane-base adhesive, ensuring a rigid strain transfer. The raw data from all sensors are interpolated on a unique general timestamp with hourly resolution. Strain data from D-FOS and VW strain gauges are then corrected from temperature effects and compared. Considering the inherent differences between the two monitoring technologies, results show a good overall matching between strain time series collected by D-FOS and VW sensors. Brillouin D-FOS proves to be a good solution in terms of performance and economic investment for SHM systems on complex infrastructures such as hydropower plants, which involve extensive geometry combined with the need for detailed and continuous strain monitoring.

Detection and Monitoring of Viral Infections via Wearable Devices and Biometric Data

Mounting clinical evidence suggests that viral infections can lead to detectable changes in an individual's normal physiologic and behavioral metrics, including heart and respiration rates, heart rate variability, temperature, activity, and sleep prior to symptom onset, potentially even in asymptomatic individuals. While the ability of wearable devices to detect viral infections in a real-world setting has yet to be proven, multiple recent studies have established that individual, continuous data from a range of biometric monitoring technologies can be easily acquired and that through the use of machine learning techniques, physiological signals and warning signs can be identified. In this review, we highlight the existing knowledge base supporting the potential for widespread implementation of biometric data to address existing gaps in the diagnosis and treatment of viral illnesses, with a particular focus on the many important lessons learned from the coronavirus disease 2019 pandemic. Expected final online publication date for the Annual Review of Biomedical Engineeing, Volume 24 is June 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Applications of Biochar and Modified Biochar in Heavy Metal Contaminated Soil: A Descriptive Review

Given that the problem of contaminated soil continues to grow, the development of effective control and remediation measures has become imperative, especially for heavy-metal-contaminated soil. Biochar and modified biochar are eco-friendly and cost-effective remediation materials that are widely used in the remediation of contaminated soil. This review provides an overview of the different raw materials used in the preparation of biochar as well as the modification of biochar using various synthesis methods, highlighting their differences and providing recommendations for biochar and modified biochar as applied toward ameliorating pollution in soil contaminated by heavy metals. We also explore the effects of the physicochemical properties of raw materials, pyrolysis temperature, additives, and modification methods on the properties of the resulting biochar and modified biochar, and systematically present the types of soil and operating factors for repair. Moreover, the mechanisms involved in remediation of heavy-metal-contaminated soil by biochar and modified biochar are outlined in detail, and include adsorption, complexation, precipitation, ion exchange, and electrostatic attractions. Finally, the corresponding monitoring technologies after remediation are illustrated. Future directions for studies on biochar and modified biochar in the remediation of contaminated soil are also proposed to support the development of green environmental protection materials, simple preparation methods, and effective follow-up monitoring techniques.

Wearable Technology to Increase Self-Awareness of Low Back Pain: A Survey of Technology Needs among Health Care Workers

Low back pain (LBP) is a leading contributor to musculoskeletal injury worldwide and carries a high economic cost. The healthcare industry is the most burdened, with nurses, in particular, being highly prone to LBP. Wearable technologies have the potential to address the challenges of monitoring postures that contribute to LBP and increase self-awareness of workplace postures and movements. We aimed to gain insight into workers’ perceptions of LBP and whether they would consider using wearable monitoring technologies to reduce injury risks. We conducted a cross-sectional survey to gather information from a selected population of nurses. Sixty-four participants completed the survey, and data were analyzed with the support of Machine Learning techniques. Findings from this study indicate that the surveyed population (64 nurses) is interested in these new approaches to monitor movement and posture in the workplace. This technology can potentially change the way ergonomic guidelines are implemented in this population.

Design of a Non-Contact Radial Torque Sensor with Variable Torque Range by Electromagnetic Coil Coupling with Piezoelectric Sensor

Recently, due to the development of automation technology, torque measuring and monitoring technologies have been brought to the focus. However, the commercially available sensors have the disadvantage of large volume, which results in the difficulty of installation on existing automated machines. Responding to the above-mentioned problem, a contactless torque sensor that uses an electromagnetic coil combined with a permanent magnet was proposed. By adjusting the input electric current in the coil, the strength of the magnetic field can be controlled to generate a non-contact magnetic force to resist external torque loading. For the measurement of such a magnetic force, a cantilever-beam mechanism comprising a piezoelectric-loading (PZT-L) sensor is employed to estimate the external static force by measuring the variation of the electric impedance. According to the measured results, the proposed PZT-L sensor demonstrates the accuracy of the proposed design, for which the maximum estimated error was around 6%. Finally, the proposed contactless torque sensor with 11 cm in diameter and 2 cm in thickness was employed to verify the effectiveness of theoretical analysis. From the sensor characteristic measurement, the detection range for external torque can be from 7.8 to 125.6 N-mm when the driven current input ranged from 2 to 10 A. Therefore, the experimental results presented that the moment of inertia via the resisted torque can be adjusted by the proposed non-contact torque-sensing system according to the measuring condition.

Impact of Fit-for-Purpose Monitoring on EOR Planning

Challenges in the design of efficient EOR field pilots have been discussed and documented in the industry, particularly when it comes to optimization of monitoring plans for technical and economical perspectives. This paper explores the benefits of pilot planning where the monitoring/control strategies are included in the early stages of the design to reduce risk of measurements ambiguity and ensure good quality pilot results evaluation. It addresses the use of new and existing technology in monitoring by highlighting the advantages and challenges of each alternative including potential pairing of complementary options to achieve the pilot objectives including illustration of the use of continuous and sporadic measurements on the evaluation. The proposed approach starts with a review of reservoir performance, heterogeneity and pilot objectives to ascertain the plausible monitoring technologies/strategies to aid during the pilot de-risking, followed by the identification of adequate novel and mature monitoring options, which are specific to EOR type and measurement nature (permanent, time lapse, etc.). Advantages of incorporating the monitoring strategy as integral part of the pilot design, as well as evaluation of the effectiveness/viability in the presence of uncertainty of the selected monitoring alternatives are discussed providing a reference of suitable/plausible EOR specific technologies. The paper illustrates the importance of selecting monitoring alternatives that feed off each other and the importance of using fit-for-purpose evaluation algorithms and a digitally enabled, structured approach to analyze and democratize pilot results and enable actionable decisions in operations.

Choosing and Managing Aged Care Services from Afar: What Matters to Australian Long-Distance Care Givers

This research aims to identify the factors that influence caregivers’ decisions about the aged care providers they select for their elder relatives when caring from a distance and what they value once they have engaged a service. Adult long-distance carers for older relatives living within Australia were purposively sampled and they participated in audio-recorded interviews. A thematic analysis was employed to investigate the data. A sample of 13 participants enabled data saturation with no new major themes identified in the final three interviews. Participants were 50 to 65 years (Mean = 59.8) and mostly (77%) female. Four themes emerged relating to selection of care providers: (1) availability of care, (2) financial arrangements, (3) proximity and location, and (4) reputation of care provider. Five themes detailed valued qualities of care: (1) vigilant monitoring and responsivity, (2) communication with family, (3) flexibility and proactiveness of care, (4) staffing, and (5) access to appropriate and holistic care to maintain wellbeing. Long-distance caregivers face barriers in selecting and managing aged care services from afar within a complex Australian aged care system. They strongly value regular, proactive communication about the wellbeing of their relatives and may be particular beneficiaries of communication and assistive monitoring technologies.

Juvenile Idiopathic Arthritis: A Review of Novel Diagnostic and Monitoring Technologies

Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease of childhood and is characterized by an often insidious onset and a chronic relapsing–remitting course, once diagnosed. With successive flares of joint inflammation, joint damage accrues, often associated with pain and functional disability. The progressive nature and potential for chronic damage and disability caused by JIA emphasizes the critical need for a prompt and accurate diagnosis. This article provides a review of recent studies related to diagnosis, monitoring and management of JIA and outlines recent novel tools and techniques (infrared thermal imaging, three-dimensional imaging, accelerometry, artificial neural networks and fuzzy logic) which have demonstrated potential value in assessment and monitoring of JIA. The emergence of novel techniques to assist clinicians’ assessments for diagnosis and monitoring of JIA has demonstrated promise; however, further research is required to confirm their clinical utility.