Medical Monitoring Applications Research Articles

Charlotte-ThermalFace: A Fully Annotated Thermal Infrared Face Dataset with Various Environmental Conditions and Distances

Facial thermography is one of the most popular research areas in infrared thermal imaging, with diverse applications in medical, surveillance, and environmental monitoring. However, in contrast to facial imagery in the visual spectrum, the lack of public datasets on facial thermal images is an obstacle to research improvement in this area. Thermal face imagery is still a relatively new research area to be evaluated and studied in different domains.The current thermal face datasets are limited in regards to the subjects’ distance from the camera, the ambient temperature variation, and facial landmarks’ localization. We address these gaps by presenting a new facial thermography dataset.This article makes two main contributions to the body of knowledge. First, it presents a comprehensive review and comparison of current public datasets in facial thermography. Second, it introduces and studies a novel public dataset on facial thermography, which we call it Charlotte-ThermalFace. Charlotte-ThermalFace contains more than10000 infrared thermal images in varying thermal conditions, several distances from the camera, and different head positions. The data is fully annotated with the facial landmarks, ambient temperature, relative humidity, the air speed of the room, distance to the camera, and subject thermal sensation at the time of capturing each image. Our dataset is the first publicly available thermal dataset annotated with the thermal sensation of each subject in different thermal conditions and one of the few datasets in raw 16-bit format. Finally, we present a preliminary analysis of the dataset to show the applicability and importance of the thermal conditions in facial thermography. The full dataset, including annotations, are freely available for research purpose at https://github.com/TeCSAR-UNCC/UNCC-ThermalFace.

Low-Cost, Real-Time Polymerase Chain Reaction System for Point-of-Care Medical Diagnosis.

Global health crises due to the prevailing Coronavirus Disease 2019 (COVID-19) pandemic have placed significant strain on health care facilities such as hospitals and clinics around the world. Further, foodborne and waterborne diseases are not only spreading faster, but also appear to be emerging more rapidly than ever before and are able to circumvent conventional control measures. The Polymerase Chain Reaction (PCR) system is a well-known diagnostic tool for many applications in medical diagnostics, environmental monitoring, and food and water quality assessment. Here, we describe the design, development, and testing of a portable, low-cost, and real-time PCR system that can be used in emergency health crises and resource-poor situations. The described PCR system incorporates real-time reaction monitoring using fluorescence as an alternative to gel electrophoresis for reaction analysis, further decreasing the need of multiple reagents, reducing sample testing cost, and reducing sample analysis time. The bill of materials cost of the described system is approximately $340. The described PCR system utilizes a novel progressive selective proportional–integral–derivative controller that helps in reducing sample analysis time. In addition, the system employs a novel primer-based approach to quantify the initial target amplicon concentration, making it well-suited for food and water quality assessment. The developed PCR system performed DNA amplification at a level and speed comparable to larger and more expensive commercial table-top systems. The fluorescence detection sensitivity was also tested to be at the same level as commercially available multi-mode optical readers, thus making the PCR system an attractive solution for medical point-of-care and food and water quality assessment.

High‐performance flexible humidity sensors for breath detection and non‐touch switches

AbstractFlexible humidity sensors have attracted much attention due to the promising applications in medical health monitoring. Up to now, the realization of such devices with ultrafast response/recovery and wide humidity range still remains a challenge. In this work, we report a new type of humidity sensor based on laser‐induced graphene (LIG) and graphene oxide (GO) with excellent performances. Graphene interdigital electrodes with good conductivity were prepared by the laser‐induced method. Then, the GO dispersion was drop‐coated on the interdigital electrode and heated to form a film as a sensing material. We have systematically studied the performances of the humidity sensor under different humidity levels. The experiment results reveal that the humidity sensor possesses high response, fast response/recovery behavior with 2 and 35 seconds, and wide humidity range from 11% RH to 97% RH. This proposed high‐performance humidity sensors could be applied in practical applications such as human breath monitoring under different states including slow breath, normal breath, fast breath, cough and rhinitis. In addition, the humidity sensors could also be used to monitor the approaching of fingertips, which makes the sensors be ideal non‐contact buttons of the elevator for stopping contacting spread of COVID‐19 viruses.

Microchannel tube NH3 sensor based on metal-organic framework UiO-66 modified polyaniline

Despite the remarkable development in conductive polymer-based NH3 sensors, there are still several obstacles such as long response/recovery time and difficulty in detecting low concentrations of NH3. In this work, polyaniline (PANI) was modified using a metal-organic framework (MOF) UiO-66 to construct a microchannel tube NH3 sensor. Scanning Electron Microscope (SEM) and Brunauer-Emmett-Teller (BET) characterizations disclose that the addition of UiO-66 could induce formation of a highly porous nanofiber PANI film. The sensor can realize the gas response up to 2540% for 100 ppm NH3, and 20% response to 10 ppb NH3 with excellent reversibility and response/recovery time (25 s/14 s). The improved sensing performance is ascribed to the high specific surface area of the PANI/UiO-66 film. Furthermore, the sensor has a microchannel tube structure which can realize fast and effective on-time detection of small-volume NH3 gas. The as-fabricated sensor could be a potential candidate in practical medical monitoring applications.

Sensitivity Enhanced Refractive Index Sensor With In-Line Fiber Mach-Zehnder Interferometer Based on Double-Peanut and Er-Doped Fiber Taper Structure

A fiber-optic Mach Zehnder interferometer (MZI) refractive index (RI) sensor based on a double peanut-shaped structure in Er-doped fiber with a section of tapered fiber was fabricated using fusion splicer and experimentally demonstrated. The double peanut-shaped structures placed at both ends of the sensor function as beam splitting/combining. Besides, the tapered region works as the sensing area. With RI changes, the optical path difference between the core mode and the cladding modes will change correspondingly, resulting in interference spectrum shifting. By monitoring the shift, the measured RI can be obtained. The experimental results show that the RI sensitivity was significantly improved compared with other types of peanut-shaped fiber sensors. By comparing different taper diameters, it is found that the finer the tapered fiber, the higher the sensitivity of measuring RI.High RI sensitivity of 441.56 nm/RIU is obtained in the experiments. Compared with the similar-structure sensor consisted of single-mode fiber (SMF), the sensitivity of the proposed sensor based on Er-doped fiber is 115.22 nm/RIU higher than that of the former. The proposed sensor has the characteristics of a compact structure. In addition, it has potential in environmental, medical, and aerospace monitoring applications.

Subfemtoampere Resolved Ionization Current Measurements Using a High-Resistance Transimpedance Amplifier

In low-dose-rate dosimetry using ionization chambers, the predominant component in the uncertainty budget is a measurement uncertainty of current at a measurement range of around 10 fA. To improve this, in this article, we report on the development of a system for measuring a small ionization current based on a transimpedance amplifier utilizing a high-resistance feedback resistor. In this amplifier, we used a feedback resistor of 1 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{T}\Omega $ </tex-math></inline-formula> made of a metalized glaze thick film, which has clear traceability to a resistance standard. In addition, the nonlinear current-to-voltage profile of the feedback resistor and its contribution to the measurement uncertainty were carefully evaluated. Type-A uncertainty well below 1 fA can be achieved within a practical measurement time shorter than an hour. As a result, current measurements with relative expanded uncertainty from 0.1 % to 2 % were demonstrated for the ionization currents ranging from sub-fA to sub-pA generated by a <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">137</sup> Cs gamma-ray source. This transimpedance amplifier with high-resistance feedback is appropriate for low-dose-rate radiation dosimetry needed for medical and environmental monitoring applications.

Attacks and Solutions for a Two-Factor Authentication Protocol for Wireless Body Area Networks

As an extension of the 4G system, 5G is a new generation of broadband mobile communication with high speed, low latency, and large connection characteristics. It solves the problem of human-to-thing and thing-to-thing communication to meet the needs of intelligent medical devices, automotive networking, smart homes, industrial control, environmental monitoring, and other IoT application needs. This has resulted in new research topics related to wireless body area networks. However, such networks are still subject to significant security and privacy threats. Recently, Fotouhi et al. proposed a lightweight and secure two-factor authentication protocol for wireless body area networks in medical IoT. However, in this study, we demonstrate that their proposed protocol is still vulnerable to sensor-capture attacks and the lack of authentication between users and mobile devices. In addition, we propose a new protocol to overcome the limitations mentioned above. A detailed comparison shows that our proposed protocol is better than the previous protocols in terms of security and performance.

Wearable Flexible Antenna for UWB On-Body and Implant Communications

This paper describes the development and evaluation of an on-body flexible antenna designed for an in-body application, as well as on-body communications at ISM and UWB frequency bands. The evaluation is performed via electromagnetic simulations using the Dassault Simulia CST Studio Suite. A planar tissue layer model, as well as a human voxel model from the human abdominal area, are used to study the antenna characteristics next to human tissues. Power flow analysis is presented to understand the power flow on the body surface as well as within the tissues. Simulation results show that this wearable flexible antenna is suitable for in-body communications in the intestinal area, e.g., for capsule endoscopy, in the industrial, scientific, and medical (ISM) band and at lower ultra-wideband (UWB). At higher frequencies, the antenna is suitable for on-body communications as well as in-body communications with lower propagation depth requirements. Additionally, an antenna prototype has been prepared and the antenna performance is verified with several on-body measurements. The measurement results show a good match with the simulation results. The novelty of the proposed antenna is a compact size and the flexible substrate material, which makes it feasible and practical for several different medical diagnosis and monitoring applications.

Synthesis and characterization of MXene (Ti3C2Tx)/Iron oxide composite for ultrasensitive electrochemical detection of hydrogen peroxide

Due to the widespread usage of hydrogen peroxide (H2O2) in various consumer and industrial products (Examples: fuel cells and antibacterial agents), it became important to accurately detect H2O2 concentration in environmental, medical and food samples. Herein, titanium carbide Ti3C2Tx (MXene) was synthesized by using Ti, Al and C powders at high-temperature. Then, nanocrystalline iron oxide (α-Fe2O3) was obtained from a single solid-phase method. Using Ti3C2Tx and Fe2O3 powders, Ti3C2Tx-Fe2O3 nanocomposite was prepared by ultrasonication. As-synthesized, Ti3C2Tx-Fe2O3 composite had been characterized by UV–Visible (UV–Vis), Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD) and Raman spectroscopy. The Fe2O3 nanoparticles (NPs) were decorated on the surface of Ti3C2Tx as observed by high resolution scanning electron microscopy (HR-SEM) and high resolution transmission electron microscopy (HR-TEM). The Ti3C2Tx nanosheets were formed with the average size of 400–500 nm. HR-SEM images of α-Fe2O3 showed that the coral-like particles with the average length ~5 μm were obtained. The electrochemical properties of the individual (Ti3C2Tx and α-Fe2O3) and composite materials (Ti3C2Tx-Fe2O3) were investigated by cyclic voltammetry (CV). Ti3C2Tx-Fe2O3 nanocomposite modified electrode had exhibited potent electro-catalytic activity for H2O2 reduction by reducing the overpotential about 320 mV and a linear response was recorded from 10 nM to 1 μM H2O2. The optimization of various parameters such as material composition ratio, amount of catalyst, effects of pH, scan rate and interference effects with other biomolecules were carried out. In addition, the kinetic parameters such as rate constant, diffusion coefficient and the active surface area of the electrodes were calculated. Moreover, the Ti3C2Tx-Fe2O3 composite modified electrode was used successfully to detect H2O2 in food and urine samples. We believe that Ti3C2Tx-Fe2O3 composite based materials could be used for the fabrication of non-enzymatic H2O2 sensors for medical diagnosis, food safety and environmental monitoring applications.

Flexible and stretchable triboelectric nanogenerator fabric for biomechanical energy harvesting and self-powered dual-mode human motion monitoring

Simultaneous monitoring of human motion and collecting ambient energy are important for the development of personal healthcare monitoring and artificial intelligence. Here, a flexible and stretchable coaxial triboelectric nanogenerator (TENG) yarn is designed and fabricated by using coil spring as the inner support layer and mechanoluminescent ZnS:Cu/PDMS composite as the outer friction layer. By weaving coaxial TENG yarns, or mix-weaving with other yarns, a multifunctional TENG fabric can be manufactured for energy harvesting external mechanical energy from human motion or ambient environment. More important, it can self-powered sense human motion in both electrical (through TENG) and optical (from mechanoluminescent ZnS:Cu/PDMS composite) methods. This work provides a new strategy for wearable TENG fabrics with dual-mode sensing and energy harvesting which have potential applications in long-term medical monitoring and human-machine interaction systems. A multifunctional triboelectric nanogenerator fabric is manufactured for energy harvesting external mechanical energy from human motion or ambient environment. Moreover, on the basis of coupling effects between the mechanical luminescence and triboelectrification important, it can self-powered sense human motion in both electrical (through TENG) and optical (from mechanoluminescent ZnS: Cu/PDMS composite) methods. • The wearable fiber is fabricated for energy harvesting and monitoring human signals in medical rehabilitation. • A dual-mode strain sensor is designed by triboelectricity and mechanoluminescence. • A fiber-shaped sensor possesses mechanical luminescence performance, which can sense the force variation more intuitively. • The triboelectric fiber exhibit good washing resistance and reusability.

Flexible Pressure Sensor Based on Molybdenum Diselide/Multi-Walled Carbon Nanotubes for Human Motion Detection

In recent years, with the rapid development of artificial intelligence and Internet of Things, flexible pressure sensors are attracting more and more attentions. Because the flexible pressure sensor has good flexibility, the sensor can be attached to the surface of the human skin as well as the surface of the object with complex structure. In the text, we used molybdenum diselide (MoSe <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> )/multi-walled carbon nanotubes (MWNTs) as the sensing element, using polydimethylsiloxane (PDMS) stripped from sandpaper as the substrate, preparing a pressure sensor with a microscopic surface structure that is rough. This whole production process was simple, economical and could be used for large-scale production. MoSe <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> /MWNTs pressure sensors offer compelling performance, including fast response (~150 ms), good repeatability (~10000 cycles), and a large operating range (0-30 kPa). Not only could it detect large human movements in real time, such as finger bending, walking, running, and swallowing, but also could detect subtle human movements such as coughing, gargling, and breathing. All results indicated that MoSe <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> /MWNTs-based pressure sensors were promising candidates for medical monitoring and artificial intelligence wearable device applications, and could also be potential candidates for human-computer interaction systems.

Reconstruction of bi-dimensional images in Fourier-transform acousto-optic imaging.

We present a new, to the best of our knowledge, method to perform acousto-optic imaging based on a spatiotemporal structuration of long-duration acoustic plane waves. This approach is particularly relevant when using detectors with long integration times. We show how it is possible to reconstruct an image by measuring its two-dimensional Fourier components. A proof of concept is presented using a photorefractive detection scheme, demonstrating equal performances to direct imaging. The overall acquisition time is compatible with medical monitoring applications.

SWIR Photodetection and Visualization Realized by Incorporating an Organic SWIR Sensitive Bulk Heterojunction.

Short‐wavelength infrared (SWIR) photodetection and visualization has profound impacts on different applications. In this work, a large‐area organic SWIR photodetector (PD) that is sensitive to SWIR light over a wavelength range from 1000 to 1600 nm and a SWIR visualization device that is capable of upconverting SWIR to visible light are developed. The organic SWIR PD, comprising an organic SWIR sensitive blend of a near‐infrared polymer and a nonfullerene n‐type small molecule SWIR dye, demonstrates an excellent capability for real‐time heart rate monitoring, offering an attractive opportunity for portable and wearable healthcare gadgets. The SWIR‐to‐visible upconversion device is also demonstrated by monolithic integration of an organic SWIR PD and a perovskite light‐emitting diode, converting SWIR (1050 nm) to visible light (516 nm). The most important attribute of the SWIR visualizing device is its solution fabrication capability for large‐area SWIR detection and visualization at a low cost. The results are very encouraging, revealing the exciting large‐area SWIR photodetection and visualization for a plethora of applications in environmental pollution, surveillance, bioimaging, medical, automotive, food, and wellness monitoring.

Remote Measurement of Human Vital Signs Based on Joint-Range Adaptive EEMD

Remote techniques for measuring human vital signs have attracted great interests due to the benefits shown in medical monitoring and military applications. Compared with continuous-wave Doppler radar, frequency-modulated continuous-wave (FMCW) radar which can discriminate vital signs from different distances, shows potential for reducing the interferences from other targets and the environment. However, in the state-of-the-art algorithms, only one chirp per frame is utilized for FMCW-based vital sign monitoring. Moreover, the vital signal is extracted from only one range bin of the fast Fourier transform. Which does not make full utilization of the long system idle time, and loses the power distributed on other range bins. By exploiting the relationship between respiration and heartbeat vibrations, an adaptive identification embedded ensemble empirical mode decomposition (EEMD) method for joint-range spectral estimation is proposed to measure the heart rate. First, A multi-chirp processing is presented for a 2-dimensional phase accumulation. Then the phase signals from a sequence of range bins are decomposed with a fast adaptive identification process. Finally, with the identified heartbeat components, we solve a multiple measurement vectors problem to estimate the heart rate. Experimental results showed that, at the detection range from 1 m~ 2.5 m, the proposed method can robustly distinguish the heartbeat from respiration and its harmonics and accurately estimate the heart rate with a root mean square error less than 6 bpm.

Data Compression mechanisms in an intelligent E-Health gateway for medical monitoring applications

Abstract In this article, we present data Compression mechanisms in an intelligent E-Health gateway for medical monitoring applications, to improve the collection and processing of data in the context of medical surveillance. These mechanisms, will not only optimize the data storage space required by the gateway, but also to accelerate the processing of the data flow for the fast and lossless transfer of data on the WSN (Wireless Sensor Network) and WLAN (Wireless Local Area Network) networks. In addition, all of the modern data compression mechanisms presented in this article are the following: Forecast compression, Sampling compression, Scheduling compression, distributed compression. We apply some formats of lossless data compression algorithms to these mechanisms (LZ4, LZO and Bzip2), to establish a comparative study between mechanisms using metric parameters. The implementation of these mechanisms in the smart gateway highlights an advanced Internet of Things data processing system for health and medical surveillance, based on a comprehensive and efficient study of advanced data compression techniques.

Tunable plasmonic properties of elongated bimetallic alloys nanoparticles towards deep UV-NIR absorbance and sensing

Combining magnetic nanoparticles with noble metallic nanoparticles to construct multifunctional alloy nanostructures has become a powerful tool for imaging sensing, medicine, biology, and cancer treatment and photothermal therapy. This work reports a study regarding the plasmonic properties of Co-Ag and Co-Au bimetallic alloys nanostructures on the electromagnetic spectrum. In this paper, the optical properties of magnetic and plasmonic nanoparticles (NPs) with different shapes, sizes, compositions, and surrounding medium are investigated by using the discrete dipole approximation (DDA) technique. The absorption and scattering localized surface plasmon resonance (LSPR) peak positions are found between 211–964 nm wavelengths ranges and can be tuned in the deep UV-NIR region of the EM spectrum in accordance with the desired application. Further, we calculate the refractive index sensitivity (S) and figure of merit (FOM) of LSPR based nanosensors. Although, LSPR based sensors undergo low FOM as compared to conventional surface plasmon resonance (SPR) sensors due to high losses from the radiative damping of localized surface plasmons (LSPs) waves. However, LSPR based sensors have potential applications in gas and bio-sensors technology viz. medical and environmental monitoring applications. In this work, the main feature of LSPR peak is dependent on nanoparticle shapes, sizes, compositions, and ambient medium and have ordered as prolate < sphere < cube < rectangular shape NPs. These results suggest that the nanostructures of Co-Ag and Co-Au alloys associated with LSPR tunability and sensitivity can be used in biomedical and sensing environment technology such as detection of chemical and catalytic events.

Blood Pressure Estimation Using On-body Continuous Wave Radar and Photoplethysmogram in Various Posture and Exercise Conditions

The pulse arrival time (PAT), pre-ejection period (PEP) and pulse transit time (PTT) are calculated using on-body continuous wave radar (CWR), Photoplethysmogram (PPG) and Electrocardiogram (ECG) sensors for wearable continuous systolic blood pressure (SBP) measurements. The CWR and PPG sensors are placed on the sternum and left earlobe respectively. This paper presents a signal processing method based on wavelet transform and adaptive filtering to remove noise from CWR signals. Experimental data are collected from 43 subjects in various static postures and 26 subjects doing 6 different exercise tasks. Two mathematical models are used to calculate SBPs from PTTs/PATs. For 38 subjects participating in posture tasks, the best cumulative error percentage (CEP) is 92.28% and for 21 subjects participating in exercise tasks, the best CEP is 82.61%. The results show the proposed method is promising in estimating SBP using PTT. Additionally, removing PEP from PAT leads to improving results by around 9%. The CWR sensors present a low-power, continuous and potentially wearable system with minimal body contact to monitor aortic valve mechanical activities directly. Results of this study, of wearable radar sensors, demonstrate the potential superiority of CWR-based PEP extraction for various medical monitoring applications, including BP measurement.

A NOVEL TECHNIQUE TO MONITOR MEDICAL EQUIPMENT MODES OF OPERATION

Quantitative measurement of the effective usability of the medical equipment is an important parameter in the quality and performance assessment. This paper introduces a simple non-invasive technique for real time monitoring of medical equipment modes of operation based on its power consumption pattern. Mode of operation detection is needed to specify the medical equipment reliability, availability, maintainability and usability. The Electrical Signature Analysis technique (ESA), is applied to monitor the overall power consumption of the electromechanical and power components inside the medical equipment. ESA is extracted using the Root Mean Square (RMS) of the electric current measured by a meter interfaced to a PC via its USB port. The ESA of the medial equipment is recorded, analyzed and correlated with the stored electric current consumption patterns of each specific mode of operation. The results were promising to accomplish the medical equipment monitoring application.

Manipulation of Confined Polyelectrolyte Conformations through Dielectric Mismatch.

We demonstrate that a highly charged polyelectrolyte confined in a spherical cavity undergoes reversible transformations between amorphous conformations and a four-fold symmetry morphology as a function of dielectric mismatch between the media inside and outside the cavity. Surface polarization due to dielectric mismatch exhibits an extra "confinement" effect, which is most pronounced within a certain range of the cavity radius and the electrostatic strength between the monomers and counterions and multivalent counterions. For cavities with a charged surface, surface polarization leads to an increased amount of counterions adsorbed in the outer side, further compressing the confined polyelectrolyte into a four-fold symmetry morphology. The equilibrium conformation of the chain is dependent upon several key factors including the relative permittivities of the media inside and outside the cavity, multivalent counterion concentration, cavity radius relative to the chain length, and interface charge density. Our findings offer insights into the effects of dielectric mismatch in packaging and delivery of polyelectrolytes across media with different relative permittivities. Moreover, the reversible transformation of the polyelectrolyte conformations in response to environmental permittivity allows for potential applications in biosensing and medical monitoring.

Simultaneous learning of reduced prototypes and local metric for image set classification

Classification based on image set is recently a competitive technique, where each set contains multiple images of a person or an object. As a widely used model, affine hull has shown its power in modeling image set. However, due to the existence of noise and outliers, the over-large affine hull usually matches fails when two hulls overlapped. Aiming at alleviating this handicap, this paper proposes a novel method for image set classification, namely Learning of Reduced Prototypes and Local Metric (LRPLM). Specifically, for each gallery image set, a reduced set of prototypes and an optimal local feature-wise metric are simultaneously learned, which jointly minimize the loss function involved the estimation of classification error probability. In doing so, LRPLM inherits the merits of affine hull with better representation to account for the unseen appearances and makes use of the powerful discriminative ability improved by the local metric. It looks like that LRPLM pulls similar image sets with the same class label “closer” to each other, while pushing dissimilar ones “far away”. Extensive experiments illustrate the considerable effectiveness of LRPLM on three widely used datasets. As we know, classification is a research hotspot in expert and intelligent systems. Different from the previous classification methods, LRPLM focuses on image set-based classification technology, while most of them are single-shot classification technology. Thus, the proposed method can be considered as an expert system technology for medical diagnosis, security monitoring, object categorization, and biometrics recognition applications.