Miniaturization has been the driving force of scientific and technological advances over recent decades. Recently, flexibility has gained significant interest, particularly in miniaturization approaches for biomedical devices, wearable sensing technologies, and drug delivery. Flexible microfluidics is an emerging area that impacts upon a range of research areas including chemistry, electronics, biology, and medicine. Various materials with flexibility and stretchability have been used in flexible microfluidics. Flexible microchannels allow for strong fluid-structure interactions. Thus, they behave in a different way from rigid microchannels with fluid passing through them. This unique behaviour introduces new characteristics that can be deployed in microfluidic applications and functions such as valving, pumping, mixing, and separation. To date, a specialised review of flexible microfluidics that considers both the fundamentals and applications is missing in the literature. This review aims to provide a comprehensive summary including: (i) Materials used for fabrication of flexible microfluidics, (ii) basics and roles of flexibility on microfluidic functions, (iii) applications of flexible microfluidics in wearable electronics and biology, and (iv) future perspectives of flexible microfluidics. The review provides researchers and engineers with an extensive and updated understanding of the principles and applications of flexible microfluidics.

Flexible Microfluidics: Fundamentals, Recent Developments, and Applications.

Wearable healthcare devices have garnered substantial interest for the realization of personal health management by monitoring the physiological parameters of individuals. Attaining the integrity between the devices and the biological interfaces is one of the greatest challenges to achieving high-quality body information in dynamic conditions. Liquid metals, which exist in the liquid phase at room temperatures, are advanced intensively as conductors for deformable devices because of their excellent stretchability and self-healing ability. The unique surface chemistry of liquid metals allows the development of various sensors and devices in wearable form. Also, the biocompatibility of liquid metals, which is verified through numerous biomedical applications, holds immense potential in uses on the surface and inside of a living body. Here, the recent progress of liquid metal-based wearable electronic devices for healthcare with respect to the featured properties and the processing technologies is discussed. Representative examples of applications such as biosensors, neural interfaces, and a soft interconnection for devices are reviewed. The current challenges and prospects for further development are also discussed, and the future directions of advances in the latest research are explored.

Liquid Metal-Based Soft Electronics for Wearable Healthcare.

Pavement-distress detection using ground-penetrating radar and network in networks

This paper presents an approach for explosive-landmine detection by designing, developing and integrating a Ground Penetrating Radar (GPR) onboard an autonomous aerial drone. Our goal is twofold: f...

An integrated aerial system for landmine detection: SDR-based Ground Penetrating Radar onboard an autonomous drone

Ground penetrating radar (GPR) is a non-destructive method (NDT) for subsurface object identification. Interpretation of GPR data is often done manually by an engineer, which is a time-intensive task and requires moderate to significant level of training. The authors proposed a novel machine learning based processing for automatic interpretation and quantification of concrete bridge deck GPR B-scan images. The proposed method is based on combination of image processing, machine learning (ML) data classification, data filtering, and spatial pattern analysis for quantification of deterioration in concrete bridge decks. For the first time, the authors introduced a dataset of 4,000 B-scan images cropped from real bridge deck GPR field data, named DECKGPRH1.0. The proposed method is tested on bridge deck GPR data collected from three bridges with different NBI (National Bridge Inventory) ratings. The results presented indicate that by implementing a ML based classifier and a fine tuned filter, the proposed approach provides a robust solution for automatic quantification GPR field data.

A Machine Learning Based Approach for Automatic Rebar Detection and Quantification of Deterioration in Concrete Bridge Deck Ground Penetrating Radar B-scan Images

It is necessary to detect the target reflections in ground penetrating radar (GPR) images, so that surface metal targets can be identified successfully. In order to accurately locate buried metal objects, a novel method called the Multiresolution Monogenic Signal Analysis (MMSA) system is applied in ground penetrating radar (GPR) images. This process includes four steps. First the image is decomposed by the MMSA to extract the amplitude component of the B-scan image. The amplitude component enhances the target reflection and suppresses the direct wave and reflective wave to a large extent. Then we use the region of interest extraction method to locate the genuine target reflections from spurious reflections by calculating the normalized variance of the amplitude component. To find the apexes of the targets, a Hough transform is used in the restricted area. Finally, we estimate the horizontal and vertical position of the target. In terms of buried object detection, the proposed system exhibits promising performance, as shown in the experimental results.

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Identification of Buried Objects in GPR Using Amplitude Modulated Signals Extracted from Multiresolution Monogenic Signal Analysis.

The invention relates to a ground penetrating radar underground target positioning method The method comprises the steps that 1) two-dimensional empirical mode decomposition is carried out on detection echo data of a ground penetrating radar to acquire K two-dimensional empirical mode function components IMF with orderly descending frequency and a residual; 2) the mean of the first M (M</=K) two-dimensional empirical mode function components is used as the characteristic value of the detection echo data; 3) the extreme point of the characteristic value of the detection echo data is acquired and is used as the estimation value of the vertex position of an underground target; 4) the underground propagation velocity of an electromagnetic wave is estimated; and 5) according to the estimation value of the vertex position of the underground target and the underground propagation velocity of the electromagnetic wave, a ground penetrating radar hyperbolic mathematical model is used to carry out hyperbolic fitting to position the underground target According to the method provided by the invention, the target information is completely kept; a clutter suppression effect is improved; and the accuracy of target positioning is improved

Ground penetrating radar underground target positioning method

A handy, flexible micro-thermocouple using low-melting-point metal alloys is proposed in this paper. The thermocouple has the advantages of simple fabrication and convenient integration. Bismuth/gallium-based mixed alloys are used as thermocouple materials. To precisely inject the metal alloys to the location of the sensing area, a micro-polydimethylsiloxane post is designed within the sensing area to prevent outflow of the metal alloy to another thermocouple pole during the metal-alloy injection. Experimental results showed that the Seebeck coefficient of this thermocouple reached −10.54 μV/K, which was much higher than the previously reported 0.1 μV/K. The thermocouple was also be bent at 90° more than 200 times without any damage when the mass ratio of the bismuth-based alloy was <60% in the metal-alloy mixture. This technology mitigated the difficulty of depositing traditional thin–film thermocouples on soft substrates. Therefore, the thermocouple demonstrated its potential for use in microfluidic chips, which are usually flexible devices.

https://www.mdpi.com/1424-8220/19/2/314/pdf

A Handy Flexible Micro-Thermocouple Using Low-Melting-Point Metal Alloys.

Bidimensional empirical mode decomposition method for image processing in sensing system

The invention relates to a ground penetrating radar underground target position detection method. The method comprises the following steps: a ground penetrating radar B-Scan data are subjected to multi-scale amplitude, phase and direction characteristic component extraction; three characteristic components for the first scale are extracted, and a color image is combined by using an HSB channel representation method; a target area of interest is found out; graying is carried out on the color image in the target area of interest, and edge extraction is carried out on an amplitude image in the target area of interest; a target hyperbolas is positioned; and according to the target hyperbolas, target position determination is realized. the method of the invention does not need data training, and online detection is easily carried out; the target information can be kept in a complete mode, the target positioning precision is enhanced, and as for shallow layer detection, false alarms are not likely to be generated, and non metallic pipeline targets are not likely to be omitted; clutter suppression effects can be enhanced, and strong clutters and target echoes can be effectively distinguished; and the algorithm is simple, and target positioning can be ensured to be quickly carried out.

Qifu Wang

Papers

Identification of Buried Objects in GPR Using Amplitude Modulated Signals Extracted from Multiresolution Monogenic Signal Analysis.

Ground penetrating radar underground target positioning method

A Handy Flexible Micro-Thermocouple Using Low-Melting-Point Metal Alloys.

Bidimensional empirical mode decomposition method for image processing in sensing system

Ground penetrating radar underground target position detection method