https://iopscience.iop.org/article/10.1149/1945-7111/ab729c/pdf

Editors’ Choice—Critical Review—A Critical Review of Solid State Gas Sensors

The diagnosis and treatment of patients with cancer requires access to imaging to ensure accurate management decisions and optimal outcomes. Our global assessment of imaging and nuclear medicine resources identified substantial shortages in equipment and workforce, particularly in low-income and middle-income countries (LMICs). A microsimulation model of 11 cancers showed that the scale-up of imaging would avert 3·2% (2·46 million) of all 76·0 million deaths caused by the modelled cancers worldwide between 2020 and 2030, saving 54·92 million life-years. A comprehensive scale-up of imaging, treatment, and care quality would avert 9·55 million (12·5%) of all cancer deaths caused by the modelled cancers worldwide, saving 232·30 million life-years. Scale-up of imaging would cost US$6·84 billion in 2020-30 but yield lifetime productivity gains of $1·23 trillion worldwide, a net return of $179·19 per $1 invested. Combining the scale-up of imaging, treatment, and quality of care would provide a net benefit of $2·66 trillion and a net return of $12·43 per $1 invested. With the use of a conservative approach regarding human capital, the scale-up of imaging alone would provide a net benefit of $209·46 billion and net return of $31·61 per $1 invested. With comprehensive scale-up, the worldwide net benefit using the human capital approach is $340·42 billion and the return per dollar invested is $2·46. These improved health and economic outcomes hold true across all geographical regions. We propose actions and investments that would enhance access to imaging equipment, workforce capacity, digital technology, radiopharmaceuticals, and research and training programmes in LMICs, to produce massive health and economic benefits and reduce the burden of cancer globally.

Medical imaging and nuclear medicine: a Lancet Oncology Commission.

Ultrasound detection is one of the major components of photoacoustic imaging systems. Advancement in ultrasound transducer technology has a significant impact on the translation of photoacoustic imaging to the clinic. Here, we present an overview on various ultrasound transducer technologies including conventional piezoelectric and micromachined transducers, as well as optical ultrasound detection technology. We explain the core components of each technology, their working principle, and describe their manufacturing process. We then quantitatively compare their performance when they are used in the receive mode of a photoacoustic imaging system.

Overview of Ultrasound Detection Technologies for Photoacoustic Imaging

Detection of volatile organic compounds (VOCs), challenged by their diversity and similarity, is gaining much attention due to concerns about adverse health effects they cause, along with intensifying development efforts in wireless sensor nodes. Precise identification of volatiles may be subject to the sensitivity and selectivity of a sensor itself and the proximity of the sensor to the source, necessitating power-efficient and portable/wearable sensing systems. The metal-oxide sensors, commonly employed for detection of VOCs, are not power efficient, due to the required heating element, and lack the selectivity, thus reporting only the total VOC level. In this paper, we present a complete low-power wireless gas-sensing system based a capacitive micromachined ultrasonic transducer array, which is known to have several advantages such as high mass sensitivity, easy implementation of a multielement structure, and high selectivity upon polymer coating. We took a holistic approach to designing the sensing elements and the custom integrated circuit (IC) as well as to operating the system, resulting in a small self-contained sensor node (38-mm detect-weight diameter and 16-mm detect-weight height). The chemical-sensing capability of the system has been validated with ethanol, achieving 120-ppb limit-of-detection while the sensor array, including the IC and the power management unit, consuming 80- $\mu \text{W}$ average power with power cycling by actively taking measurements for 3 s detect-weight per minute. The presented system will eventually provide a ubiquitous tool to identify VOCs with the help of multivariate data analysis.

A Low-Power Wireless Multichannel Gas Sensing System Based on a Capacitive Micromachined Ultrasonic Transducer (CMUT) Array

This review article is focused on the analysis of the state of the art of sensors for guided ultrasonic waves for the detection and localization of impacts for structural health monitoring (SHM). The recent developments in sensor technologies are then reported and discussed through the many references in recent scientific literature. The physical phenomena that are related to impact event and the related main physical quantities are then introduced to discuss their importance in the development of the hardware and software components for SHM systems. An important aspect of the article is the description of the different ultrasonic sensor technologies that are currently present in the literature and what advantages and disadvantages they could bring in relation to the various phenomena investigated. In this context, the analysis of the front-end electronics is deepened, the type of data transmission both in terms of wired and wireless technology and of online and offline signal processing. The integration aspects of sensors for the creation of networks with autonomous nodes with the possibility of powering through energy harvesting devices and the embedded processing capacity is also studied. Finally, the emerging sector of processing techniques using deep learning and artificial intelligence concludes the review by indicating the potential for the detection and autonomous characterization of the impacts.

Ultrasonic Guided-Waves Sensors and Integrated Structural Health Monitoring Systems for Impact Detection and Localization: A Review.

Capacitive micromachined ultrasonic transducer (CMUT) technology has enjoyed rapid development in the last decade. Advancements both in fabrication and integration, coupled with improved modelling, has enabled CMUTs to make their way into mainstream ultrasound imaging systems and find commercial success. In this review paper, we touch upon recent advancements in CMUT technology at all levels of abstraction; modeling, fabrication, integration, and applications. Regarding applications, we discuss future trends for CMUTs and their impact within the broad field of biomedical imaging.

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Advances in Capacitive Micromachined Ultrasonic Transducers.

Capacitive Micromachined Ultrasonic Transducers (CMUTs) can be used as small, highly sensitive chemical sensors in air. Single CMUT chemical sensors lack selectivity, but arrays of multiple sensors can be used to allow selective chemical detection. In this work, we demonstrate the simultaneous operation of eight CMUT chemical sensors on a single chip. We then use seven sensors from this array to classify five different chemical vapors and measure their concentrations. Finally, we use the same sensor array to classify three samples of coffee beans grown on different farms. The sensor array is able to perform both classification tasks with 100% accuracy, demonstrating its selectivity.

An 8-channel CMUT chemical sensor array on a single chip

Capacitive micromachined ultrasonic transducers (CMUTs) can function as extremely sensitive mass-loading chemical sensors. The resonant frequency of the CMUT changes as mass is added due to chemicals absorbing into a chemical-sensitive layer on the top of the plate. However, these sensors suffer from the problem that they are not selective to a single chemical. As a solution, we present a system of four CMUT chemical sensors with different functionalization layers. Neural networks are used to do pattern recognition on the sensor outputs in order to distinguish different chemicals. The system is capable of distinguishing water, ethanol, acetone, ethyl acetate, methane and carbon dioxide in air at concentrations less than 1% with 98% accuracy. Once the chemical is identified, the concentration can be determined using polynomial regression with an RMS percentage error ranging from 1.1% to 13%, depending on the analyte.

Distinguishing chemicals using CMUT chemical sensor array and artificial neural networks

Capacitive micromachined ultrasonic transducers (CMUTs) make extremely sensitive chemical sensors in air. In this work, we demonstrate a CMUT chemical sensor chip with integrated temperature and pressure sensors. These sensors allow the measurement of multiple environmental parameters using a single chip and allow the influence of temperature and pressure on the chemical sensors to be corrected for. Additionally, the CMUTs are designed to have low charging. We demonstrate the use the temperature sensor to correct for resonance frequency variations due to temperature. With temperature correction, we measure the drift of two chemical sensors to be 19 parts per million and 59 parts per million over 12 hours. This is progress towards being able to make continuous measurements with the chemical sensor without comparing to a reference gas.

CMUT chip with integrated temperature and pressure sensors

Significance Ultrasound can be focused through skull onto the deep brain, altering neural activity noninvasively. Despite its broad utility, the action of focused ultrasound on specific cell types is almost entirely unknown. Understanding cell type–specific responses to FUS would allow selection of ultrasound waveforms that engage the intended targets while limiting effects on off-target fields. We developed a system combining FUS targeting and optical recording of virally labeled deep brain cell types in freely behaving animals. We used the tool to identify a protocol for the hippocampus that selectively increases inhibitory neural activity while decreasing excitatory activity with high spatial specificity. The protocol robustly suppressed epileptiforms in a chronic epilepsy model demonstrating the tool’s potential for examining experimental FUS therapies.

Quintin Stedman

Papers

Advances in Capacitive Micromachined Ultrasonic Transducers.

An 8-channel CMUT chemical sensor array on a single chip

Distinguishing chemicals using CMUT chemical sensor array and artificial neural networks

CMUT chip with integrated temperature and pressure sensors

A tool for monitoring cell type–specific focused ultrasound neuromodulation and control of chronic epilepsy