Search Results (18)

The quality of surface morphology can reflect the electrical performance of silver-based contacts. Existing research on the correlation of morphological–electrical performance is based solely on empirical models from traditional visual inspections and only considers the impact of visually observable macro-textural features on electrical performance. However, the influence of micro-textural features on electrical performance should not be overlooked. This paper establishes a contactless surface morphology acquisition device based on a laser profilometer to address the assembly characteristics of contact components. Various original profile signals such as surface roughness, waviness, and surface form error are calculated using wavelet transformation, and a robust weight function is introduced to separate micro-textural features from macro-textural features. After the morphological parameters affecting electrical performance are quantified, the variation laws of single and composite morphological parameters on electrical performance are clarified. Parameter optimization iterations and parameter space distribution optimization are performed using a decision tree, and the optimized predictive model forecasts specific electrical parameter values. The predicted results are quantitatively evaluated, establishing evaluation metrics that reflect the errors and degree of fit between the model predictions and actual values from different perspectives. From the experimental results, the accuracy of the predictive model established in this study exceeds 97%. Full article

Blood oxygen saturation (SpO₂) is an essential physiological parameter for evaluating a person’s health. While conventional SpO₂ measurement devices like pulse oximeters require skin contact, advanced computer vision technology can enable remote SpO₂ monitoring through a regular camera without skin contact. In this paper, we propose novel deep learning models to measure SpO₂ remotely from facial videos and evaluate them using a public benchmark database, VIPL-HR. We utilize a spatial–temporal representation to encode SpO₂ information recorded by conventional RGB cameras and directly pass it into selected convolutional neural networks to predict SpO₂. The best deep learning model achieves 1.274% in mean absolute error and 1.71% in root mean squared error, which exceed the international standard of 4% for an approved pulse oximeter. Our results significantly outperform the conventional analytical Ratio of Ratios model for contactless SpO₂ measurement. Results of sensitivity analyses of the influence of spatial–temporal representation color spaces, subject scenarios, acquisition devices, and SpO₂ ranges on the model performance are reported with explainability analyses to provide more insights for this emerging research field. Full article

Surface electromyography (sEMG) is the acquisition, from the skin, of the electrical signal produced by muscle activation. Usually, sEMG is measured through electrodes with electrolytic gel, which often causes skin irritation. Capacitive contactless electrodes have been developed to overcome this limitation. However, contactless EMG devices are still sensitive to motion artifacts and often not comfortable for long monitoring. In this study, a non-invasive contactless method to estimate parameters indicative of muscular activity and fatigue, as they are assessed by EMG, through infrared thermal imaging (IRI) and cross-validated machine learning (ML) approaches is described. Particularly, 10 healthy participants underwent five series of bodyweight squats until exhaustion interspersed by 1 min of rest. During exercising, the vastus medialis activity and its temperature were measured through sEMG and IRI, respectively. The EMG average rectified value (ARV) and the median frequency of the power spectral density (MDF) of each series were estimated through several ML approaches applied to IRI features, obtaining good estimation performances (r = 0.886, p < 0.001 for ARV, and r = 0.661, p < 0.001 for MDF). Although EMG and IRI measure physiological processes of a different nature and are not interchangeable, these results suggest a potential link between skin temperature and muscle activity and fatigue, fostering the employment of contactless methods to deliver metrics of muscular activity in a non-invasive and comfortable manner in sports and clinical applications. Full article

Photoplethysmography (PPG) is a noninvasive optical technology with applications including vital sign extraction and patient monitoring. However, its current use is primarily limited to heart rate and oxygenation monitoring. This study aims to demonstrate the utility of PPG for physiological investigations. In particular, we sought to demonstrate the utility of simultaneous data acquisition from several regions of tissue using remote/contactless PPG (rPPG). Specifically, using a high-speed scientific-grade camera, we collected rPPG from the hands (palmar/dorsal) of 22 healthy volunteers. Data collected through the red and green channels of the RGB CMOS sensor were analyzed. We found a statistically significant difference in the amplitude of the glabrous skin signal over the non-glabrous skin signal (1.41 ± 0.85 in the red channel and 2.27 ± 0.88 in the green channel). In addition, we found a statistically significant lead of the red channel over the green channel, which is consistent between glabrous (17.13 ± 10.69 ms) and non-glabrous (19.31 ± 12.66 ms) skin. We also found a statistically significant lead time (32.69 ± 55.26 ms in the red channel and 40.56 ± 26.97 ms in the green channel) of the glabrous PPG signal over the non-glabrous, which cannot be explained by bilateral variability. These results demonstrate the utility of rPPG imaging as a tool for fundamental physiological studies and can be used to inform the development of PPG-based devices. Full article

Today, low-cost sensors in various civil engineering sectors are gaining the attention of researchers due to their reduced production cost and their applicability to multiple nodes. Low-cost sensors also have the advantage of easily connecting to low-cost microcontrollers such as Arduino. A low-cost, reliable acquisition system based on Arduino technology can further reduce the price of data acquisition and monitoring, which can make long-term monitoring possible. This paper introduces a wireless Internet-based low-cost data acquisition system consisting of Raspberry Pi and several Arduinos as signal conditioners. This study investigates the beneficial impact of similar sensor combinations, aiming to improve the overall accuracy of several sensors with an unknown accuracy range. The paper then describes an experiment that gives valuable information about the standard deviation, distribution functions, and error level of various individual low-cost sensors under different environmental circumstances. Unfortunately, these data are usually missing and sometimes assumed in numerical studies targeting the development of structural system identification methods. A measuring device consisting of a total of 75 contactless ranging sensors connected to two microcontrollers (Arduinos) was designed to study the similar sensor combination theory and present the standard deviation and distribution functions. The 75 sensors include: 25 units of HC-SR04 (analog), 25 units of VL53L0X, and 25 units of VL53L1X (digital). Full article

The acquisition of nutrient data on a precise scale has played a vital role in nutrient management processes for soils. However, the lack of rapid precise and multi-index detection techniques for soil macronutrient contents hinders both rational fertilization and cost reduction. In this paper, a rapid detection method and device were devised, combining capillary electrophoresis (CE) and capacitively coupled contactless conductivity detection (C4D), and presented to detect macronutrient contents of soil. The device consisted of a capillary channel, C4D detector, high-voltage system, etc. It separated macronutrient ions using capillary electrophoresis and then measured the ion concentration based on the C4D principle. Lime concretion black soil samples from a complete field were collected and detected. NO₃⁻, NH₄⁺, H₂PO₄⁻ and K⁺ in sample solutions could be detected in 5 min with relative standard deviations (RSDs) from 1.0 to 7.51%. The injection voltage was set to 10 kV for 5 s, and the separation voltage was set to 14 kV. This demonstrated the excellent performance of the C4D device on the detection of soil macronutrients, which could help to guide fertilization operations more effectively. Full article

Dedicated research is currently being conducted on novel thin film magnetoelectric (ME) sensor concepts for medical applications. These concepts enable a contactless magnetic signal acquisition in the presence of large interference fields such as the magnetic field of the Earth and are operational at room temperature. As more and more different ME sensor concepts are accessible to medical applications, the need for comparative quality metrics significantly arises. For a medical application, both the specification of the sensor itself and the specification of the readout scheme must be considered. Therefore, from a medical user’s perspective, a system consideration is better suited to specific quantitative measures that consider the sensor readout scheme as well. The corresponding sensor system evaluation should be performed in reproducible measurement conditions (e.g., magnetically, electrically and acoustically shielded environment). Within this contribution, an ME sensor system evaluation scheme will be described and discussed. The quantitative measures will be determined exemplarily for two ME sensors: a resonant ME sensor and an electrically modulated ME sensor. In addition, an application-related signal evaluation scheme will be introduced and exemplified for cardiovascular application. The utilized prototype signal is based on a magnetocardiogram (MCG), which was recorded with a superconducting quantum-interference device. As a potential figure of merit for a quantitative signal assessment, an application specific capacity (ASC) is introduced. In conclusion, this contribution highlights metrics for the quantitative characterization of ME sensor systems and their resulting output signals in biomagnetism. Finally, different ASC values and signal-to-noise ratios (SNRs) could be clearly presented for the resonant ME sensor (SNR: $-90$ dB, ASC: $9.8\times {10}^{-7}$ dB Hz) and also the electrically modulated ME sensor (SNR: $-11$ dB, ASC: 23 dB Hz), showing that the electrically modulated ME sensor is better suited for a possible MCG application under ideal conditions. The presented approach is transferable to other magnetic sensors and applications. Full article

This work presents an automated contactless fingerprint recognition system for smartphones. We provide a comprehensive description of the entire recognition pipeline and discuss important requirements for a fully automated capturing system. In addition, our implementation is made publicly available for research purposes. During a database acquisition, a total number of 1360 contactless and contact-based samples of 29 subjects are captured in two different environmental situations. Experiments on the acquired database show a comparable performance of our contactless scheme and the contact-based baseline scheme under constrained environmental influences. A comparative usability study on both capturing device types indicates that the majority of subjects prefer the contactless capturing method. Based on our experimental results, we analyze the impact of the current COVID-19 pandemic on fingerprint recognition systems. Finally, implementation aspects of contactless fingerprint recognition are summarized. Full article

The design and implementation of a contactless scanner and its software are proposed. The scanner regards the photographic digitization of planar and approximately planar surfaces and is proposed as a cost-efficient alternative to off-the-shelf solutions. The result is 19.8 Kppi micrometer scans, in the service of several applications. Accurate surface mosaics are obtained based on a novel image acquisition and image registration approach that actively seeks registration cues by acquiring auxiliary images and fusing proprioceptive data in correspondence and registration tasks. The device and operating software are explained, provided as an open prototype, and evaluated qualitatively and quantitatively. Full article

During the COVID-19 pandemic, there has been a significant increase in the use of non-contact infrared devices for screening the body temperatures of people at the entrances of hospitals, airports, train stations, churches, schools, shops, sports centres, offices, and public places in general. The strong correlation between a high body temperature and SARS-CoV-2 infection has motivated the governments of several countries to restrict access to public indoor places simply based on a person’s body temperature. Negating/allowing entrance to a public place can have a strong impact on people. For example, a cancer patient could be refused access to a cancer centre because of an incorrect high temperature measurement. On the other hand, underestimating an individual’s body temperature may allow infected patients to enter indoor public places where it is much easier for the virus to spread to other people. Accordingly, during the COVID-19 pandemic, the reliability of body temperature measurements has become fundamental. In particular, a debated issue is the reliability of remote temperature measurements, especially when these are aimed at identifying in a quick and reliable way infected subjects. Working distance, body–device angle, and light conditions and many other metrological and subjective issues significantly affect the data acquired via common contactless infrared point thermometers, making the acquisition of reliable measurements at the entrance to public places a challenging task. The main objective of this work is to sensitize the community to the typical incorrect uses of infrared point thermometers, as well as the resulting drifts in measurements of body temperature. Using several commercial contactless infrared point thermometers, we performed four different experiments to simulate common scenarios in a triage emergency room. In the first experiment, we acquired several measurements for each thermometer without measuring the working distance or angle of inclination to show that, for some instruments, the values obtained can differ by 1 °C. In the second and third experiments, we analysed the impacts of the working distance and angle of inclination of the thermometers, respectively, to prove that only a few cm/degrees can cause drifts higher than 1 °C. Finally, in the fourth experiment, we showed that the light in the environment can also cause changes in temperature up to 0.5 °C. Ultimately, in this study, we quantitatively demonstrated that the working distance, angle of inclination, and light conditions can strongly impact temperature measurements, which could invalidate the screening results. Full article

Recent developments enable biometric recognition systems to be available as mobile solutions or to be even integrated into modern smartphone devices. Thus, smartphone devices can be used as mobile fingerprint image acquisition devices, and it has become feasible to process fingerprints on these devices, which helps police authorities carry out identity verification. In this paper, we provide a comprehensive and in-depth engineering study on the different stages of the fingerprint recognition toolchain. The insights gained throughout this study serve as guidance for future work towards developing a contactless mobile fingerprint solution based on the iPhone 11, working without any additional hardware. The targeted solution will be capable of acquiring 4 fingers at once (except the thumb) in a contactless manner, automatically segmenting the fingertips, pre-processing them (including a specific enhancement), and thus enabling fingerprint comparison against contact-based datasets. For fingertip detection and segmentation, various traditional handcrafted feature-based approaches as well as deep-learning-based ones are investigated. Furthermore, a run-time analysis and first results on the biometric recognition performance are included. Full article

With growing interest in healthcare, wearable healthcare devices have been developed and researched. In particular, near-field communication (NFC) based wearable devices have been actively studied for device miniaturization. Herein, this article proposes a low-cost and convenient healthcare system, which can monitor heart rate and temperature using a wireless/battery-free sensor and the customized smartphone application. The authors designed and fabricated a customized healthcare device based on the NFC system, and developed a smartphone application for real-time data acquisition and processing. In order to achieve compact size without performance degradation, a dual-layered layout is applied to the device. The authors demonstrate that the device can operate as attached on various body sites such as wrist, fingertip, temple, and neck due to outstanding flexibility of device and adhesive strength between the device and the skin. In addition, the data processing flow and processing result are presented for offering heart rate and skin temperature. Therefore, this work provides an affordable and practical pathway for the popularization of wireless wearable healthcare system. Moreover, the proposed platform can easily delivery the measured health information to experts for contactless/personal health consultation. Full article

Traditional capacitive electrocardiogram (cECG) electrodes suffer from limited patient comfort, difficulty of disinfection and low signal-to-noise ratio in addition to the challenge of integrating them in wearables. A novel hybrid flexible cECG electrode was developed that offers high versatility in the integration method, is well suited for large-scale manufacturing, is easy to disinfect in clinical settings and exhibits better performance over a comparable rigid contactless electrode. The novel flexible electrode meets the frequency requirement for clinically important QRS complex detection (0.67–5 Hz) and its performance is improved over rigid contactless electrode across all measured metrics as it maintains lower cut-off frequency, higher source capacitance and higher pass-band gain when characterized over a wide spectrum of patient morphologies. The results presented in this article suggest that the novel flexible electrode could be used in a medical device for cECG acquisition and medical diagnosis. The novel design proves also to be less sensitive to motion than a reference rigid electrode. We therefore anticipate it can represent an important step towards improving the repeatability of cECG methods while requiring less post-processing. This would help making cECG a viable method for remote cardiac health monitoring. Full article

Vascular pattern based biometric recognition is gaining more and more attention, with a trend towards contactless acquisition. An important requirement for conducting research in vascular pattern recognition are available datasets. These datasets can be established using a suitable biometric capturing device. A sophisticated capturing device design is important for good image quality and, furthermore, at a decent recognition rate. We propose a novel contactless capturing device design, including technical details of its individual parts. Our capturing device is suitable for finger and hand vein image acquisition and is able to acquire palmar finger vein images using light transmission as well as palmar hand vein images using reflected light. An experimental evaluation using several well-established vein recognition schemes on a dataset acquired with the proposed capturing device confirms its good image quality and competitive recognition performance. This challenging dataset, which is one of the first publicly available contactless finger and hand vein datasets, is published as well. Full article

The rapid and reliable detection of chemical and biological agents in the field is important for many applications such as national security, environmental monitoring, infectious diseases screening, and so on. Current commercially available devices may suffer from low field deployability, specificity, and reproducibility, as well as a high false alarm rate. This paper reports the development of a portable lab-on-a-chip device that could address these issues. The device integrates a polymer multiplexed microchip system, a contactless conductivity detector, a data acquisition and signal processing system, and a graphic/user interface. The samples are pre-treated by an on-chip capillary electrophoresis system. The separated analytes are detected by conductivity-based microsensors. Extensive studies are carried out to achieve satisfactory reproducibility of the microchip system. Chemical warfare agents soman (GD), sarin (GB), O-ethyl S-[2-diisoproylaminoethyl] methylphsophonothioate (VX), and their degradation products have been tested on the device. It was demonstrated that the device can fingerprint the tested chemical warfare agents. In addition, the detection of ricin and metal ions in water samples was demonstrated. Such a device could be used for the rapid and sensitive on-site detection of both chemical and biological agents in the future. Full article