A Step Test to Evaluate the Susceptibility to Severe High-Altitude Illness in Field Conditions

Hermand, Eric, Léo Lesaint, Laura Denis, Jean-Paul Richalet, and François J. Lhuissier. A step test to evaluate the susceptibility to severe high-altitude illness in field conditions. High Alt Med Biol. 00:000-000, 2024.-A laboratory-based hypoxic exercise test, performed on a cycle ergometer, can be used to predict susceptibility to severe high-altitude illness (SHAI) through the calculation of a clinicophysiological SHAI score. Our objective was to design a field-condition test and compare its derived SHAI score and various physiological parameters, such as peripheral oxygen saturation (SpO2), and cardiac and ventilatory responses to hypoxia during exercise (HCRe and HVRe, respectively), to the laboratory test. A group of 43 healthy subjects (15 females and 28 males), with no prior experience at high altitude, performed a hypoxic cycle ergometer test (simulated altitude of 4,800 m) and step tests (20 cm high step) at 3,000, 4,000, and 4,800 m simulated altitudes. According to tested altitudes, differences were observed in O2 desaturation, heart rate, and minute ventilation (p < 0.001), whereas the computed HCRe and HVRe were not different (p = 0.075 and p = 0.203, respectively). From the linear relationships between the step test and SHAI scores, we defined a risk zone, allowing us to evaluate the risk of developing SHAI and take adequate preventive measures in field conditions, from the calculated step test score for the given altitude. The predictive value of this new field test remains to be validated in real high-altitude conditions.

Synchronous Diagnosis of Respiratory Viruses Variants via Receptonics Based on Modeling Receptor-Ligand Dynamics

The transmission and pathogenesis of highly contagious fatal respiratory viruses are increasing, and the need for an on-site diagnostic platform has arisen as an issue worldwide. Furthermore, as the spread of respiratory viruses continues, different variants have become the dominant circulating strains. To prevent virus transmission, the development of highly sensitive and accurate on-site diagnostic assays is urgently needed. Herein, a facile diagnostic device is presented for multi-detection based on the results of detailed receptor-ligand dynamics simulations for the screening of various viral strains. The novel bioreceptor-treated electronics (receptonics) device consists of a multichannel graphene transistor and cell-entry receptors conjugated to N-heterocyclic carbene (NHC). An ultrasensitive multi-detection performance is achieved without the need for sample pretreatment, which will enable rapid diagnosis and prevent the spread of pathogens. This platform can be applied for the diagnosis of variants of concern in clinical respiratory virus samples and primate models. This multi-screening platform can be used to enhance surveillance and discriminate emerging virus variants before they become a severe threat to public health.

Survey of Transfer Learning Approaches in the Machine Learning of Digital Health Sensing Data

Machine learning and digital health sensing data have led to numerous research achievements aimed at improving digital health technology. However, using machine learning in digital health poses challenges related to data availability, such as incomplete, unstructured, and fragmented data, as well as issues related to data privacy, security, and data format standardization. Furthermore, there is a risk of bias and discrimination in machine learning models. Thus, developing an accurate prediction model from scratch can be an expensive and complicated task that often requires extensive experiments and complex computations. Transfer learning methods have emerged as a feasible solution to address these issues by transferring knowledge from a previously trained task to develop high-performance prediction models for a new task. This survey paper provides a comprehensive study of the effectiveness of transfer learning for digital health applications to enhance the accuracy and efficiency of diagnoses and prognoses, as well as to improve healthcare services. The first part of this survey paper presents and discusses the most common digital health sensing technologies as valuable data resources for machine learning applications, including transfer learning. The second part discusses the meaning of transfer learning, clarifying the categories and types of knowledge transfer. It also explains transfer learning methods and strategies, and their role in addressing the challenges in developing accurate machine learning models, specifically on digital health sensing data. These methods include feature extraction, fine-tuning, domain adaptation, multitask learning, federated learning, and few-/single-/zero-shot learning. This survey paper highlights the key features of each transfer learning method and strategy, and discusses the limitations and challenges of using transfer learning for digital health applications. Overall, this paper is a comprehensive survey of transfer learning methods on digital health sensing data which aims to inspire researchers to gain knowledge of transfer learning approaches and their applications in digital health, enhance the current transfer learning approaches in digital health, develop new transfer learning strategies to overcome the current limitations, and apply them to a variety of digital health technologies.

Quantitative assessment of spasticity: a narrative review of novel approaches and technologies

Spasticity is a complex neurological disorder, causing significant physical disabilities and affecting patients' independence and quality of daily lives. Current spasticity assessment methods are questioned for their non-standardized measurement protocols, limited reliabilities, and capabilities in distinguishing neuron or non-neuron factors in upper motor neuron lesion. A series of new approaches are developed for improving the effectiveness of current clinical used spasticity assessment methods with the developing technology in biosensors, robotics, medical imaging, biomechanics, telemedicine, and artificial intelligence. We investigated the reliabilities and effectiveness of current spasticity measures employed in clinical environments and the newly developed approaches, published from 2016 to date, which have the potential to be used in clinical environments. The new spasticity scales, taking advantage of quantified information such as torque, or echo intensity, the velocity-dependent feature and patients' self-reported information, grade spasticity semi-quantitatively, have competitive or better reliability than previous spasticity scales. Medical imaging technologies, including near-infrared spectroscopy, magnetic resonance imaging, ultrasound and thermography, can measure muscle hemodynamics and metabolism, muscle tissue properties, or temperature of tissue. Medical imaging-based methods are feasible to provide quantitative information in assessing and monitoring muscle spasticity. Portable devices, robotic based equipment or myotonometry, using information from angular, inertial, torque or surface EMG sensors, can quantify spasticity with the help of machine learning algorithms. However, spasticity measures using those devices are normally not physiological sound. Repetitive peripheral magnetic stimulation can assess patients with severe spasticity, which lost voluntary contractions. Neuromusculoskeletal modeling evaluates the neural and non-neural properties and may gain insights into the underlying pathology of spasticity muscles. Telemedicine technology enables outpatient spasticity assessment. The newly developed spasticity methods aim to standardize experimental protocols and outcome measures and enable quantified, accurate, and intelligent assessment. However, more work is needed to investigate and improve the effectiveness and accuracy of spasticity assessment.

Prospects of Microfluidic Technology in Nucleic Acid Detection Approaches

Conventional diagnostic techniques are based on the utilization of analyte sampling, sensing and signaling on separate platforms for detection purposes, which must be integrated to a single step procedure in point of care (POC) testing devices. Due to the expeditious nature of microfluidic platforms, the trend has been shifted toward the implementation of these systems for the detection of analytes in biochemical, clinical and food technology. Microfluidic systems molded with substances such as polymers or glass offer the specific and sensitive detection of infectious and noninfectious diseases by providing innumerable benefits, including less cost, good biological affinity, strong capillary action and simple process of fabrication. In the case of nanosensors for nucleic acid detection, some challenges need to be addressed, such as cellular lysis, isolation and amplification of nucleic acid before its detection. To avoid the utilization of laborious steps for executing these processes, advances have been deployed in this perspective for on-chip sample preparation, amplification and detection by the introduction of an emerging field of modular microfluidics that has multiple advantages over integrated microfluidics. This review emphasizes the significance of microfluidic technology for the nucleic acid detection of infectious and non-infectious diseases. The implementation of isothermal amplification in conjunction with the lateral flow assay greatly increases the binding efficiency of nanoparticles and biomolecules and improves the limit of detection and sensitivity. Most importantly, the deployment of paper-based material made of cellulose reduces the overall cost. Microfluidic technology in nucleic acid testing has been discussed by explicating its applications in different fields. Next-generation diagnostic methods can be improved by using CRISPR/Cas technology in microfluidic systems. This review concludes with the comparison and future prospects of various microfluidic systems, detection methods and plasma separation techniques used in microfluidic devices.

Portable Surface Plasmon Resonance Detector for COVID-19 Infection

Methods based on nucleic acid detection are currently the most commonly used technique in COVID-19 diagnostics. Although generally considered adequate, these methods are characterised by quite a long time-to-result and the necessity to prepare the material taken from the examined person-RNA isolation. For this reason, new detection methods are being sought, especially those characterised by the high speed of the analysis process from the moment of sampling to the result. Currently, serological methods of detecting antibodies against the virus in the patient's blood plasma have attracted much attention. Although they are less precise in determining the current infection, such methods shorten the analysis time to several minutes, making it possible to consider them a promising method for screening tests in people with suspected infection. The described study investigated the feasibility of a surface plasmon resonance (SPR)-based detection system for on-site COVID-19 diagnostics. A simple-to-use portable device was proposed for the fast detection of anti-SARS-CoV-2 antibodies in human plasma. SARS-CoV-2-positive and -negative patient blood plasma samples were investigated and compared with the ELISA test. The receptor-binding domain (RBD) of spike protein from SARS-CoV-2 was selected as a binding molecule for the study. Then, the process of antibody detection using this peptide was examined under laboratory conditions on a commercially available SPR device. The portable device was prepared and tested on plasma samples from humans. The results were compared with those obtained in the same patients using the reference diagnostic method. The detection system is effective in the detection of anti-SARS-CoV-2 with the detection limit of 40 ng/mL. It was shown that it is a portable device that can correctly examine human plasma samples within a 10 min timeframe.

Multiport Single Element Mimo Antenna Systems: A Review

In response to the increasing demand for voice, data, and multimedia applications, the next generation of wireless communication systems is projected to provide faster data rates and better service quality to customers. Techniques such as Multiple-Input-Multiple-Output (MIMO) and diversity are being studied and implemented to meet the needs of next-generation wireless communication systems. Embedding multiple antennas into the same antenna system is seen as a promising solution, which can improve both the system's channel capacity and the communication link's quality. However, for small handheld and portable devices, embedding many antennas into a single device in a small area and at the same time providing good isolation becomes a challenge. Hence, designing a shared antenna system with multiple feed ports with equivalent or better performance characteristics as compared to the approach of multiple antennas with multiple feed ports is a promising advantage which can reduce the size and cost of manufacturing. This paper intends to provide an in-depth review of different MIMO antenna designs with common radiators covering various antenna design aspects such as isolation techniques, gain, efficiency, envelope correlation coefficient, and size, etc. There is also a discussion of the mathematical concepts of MIMO and different isolation techniques, as well as a comparative analysis of different shared radiator antenna designs. The literature review shows that only very few antennas' design with common radiator have been suggested in the available literature at present. Therefore, in this review paper, we have endeavored to study different antennas' designs with common radiator. A comparison is provided of their performance improvement techniques in a holistic way so that it can lead to further develop the common radiator multiport antenna systems and realize the promising advantages they offer.

Portuino-A Novel Portable Low-Cost Arduino-Based Photo- and Fluorimeter

A novel portable low-cost Arduino-controlled photo- and fluorimeter for on-site measurements has been developed. The device uses LEDs as a light source and a phototransistor as a light sensor. The circuit is based on the discharge of a capacitor with the photocurrent from the phototransistor. Validation experiments for absorbance measurements were performed by measuring protein concentration using the Bradford method and measuring phosphate ions in water using a commercial test kit. The emission light of the excited fluorescent dyes rhodamine 6G and calcofluor white was measured to validate the usability of the device as a fluorescence photometer. In all validation experiments, similar correlation coefficients and limit of detection could be achieved with the portable photo- and fluorimeter and a laboratory spectrometer and fluorimeter. Real sample analysis was performed, measuring phosphate concentration in freshwater and concentration of green fluorescent protein, extracted from Escherichia coli.

Development of an Integrated Salt Cartridge-Reverse Electrodialysis (Red) Device to Increase Electrolyte Concentrations to Biomedical Devices

Emerging technologies in nanotechnology and biomedical engineering have led to an increase in the use of implantable biomedical devices. These devices are currently battery powered which often means they must be surgically replaced during a patient's lifetime. Therefore, there is an important need for a power source that could provide continuous, stable power over a prolonged time. Reverse electrodialysis (RED) based biopower cells have been previously used to generate continuous power from physiologically relevant fluids; however, the low salinity gradient that exists within the body limited the performance of the biopower cell. In this study, a miniaturized RED biopower cell design coupled with a salt cartridge was evaluated for boosting the salt concentration gradient supplied to RED in situ. For the salt cartridge, polysulfone (PSf) hollow fibers were prepared in-house and saturated with NaCl solutions to deliver salt and thereby enhance the concentration gradient. The effect of operational parameters including solution flow rate and cartridge salt concentration on salt transport performance was evaluated. The results demonstrated that the use of the salt cartridge was able to increase the salt concentration of the RED inlet stream by 74% which in turn generated a 3-fold increase in the open circuit voltage (OCV) of the biopower cell. This innovative adaptation of the membrane-based approach into portable power generation could help open new pathways in various biomedical applications.

On-site forensic analysis of colored seized materials: Detection of brown heroin and MDMA-tablets by a portable NIR spectrometer

The increasing workload for forensic laboratories and the expanding complexity of the drug market necessitates efficient approaches to detect drugs of abuse. Identification directly at the scene of crime enables investigative forces to make rapid decisions. Additionally, on-site identification of the material also leads to considerable efficiency and cost benefits. As such, paperwork, transportation, and time-consuming analysis in a laboratory may be avoided. Near-infrared (NIR) spectroscopy is an analysis technique suitable for rapid drug testing using portable equipment. A possible limitation of spectroscopic analysis concerns the complexity of seized materials. NIR measurements represent composite spectra for mixtures and diagnostic spectral features can be obscured by excipients such as colorants. Herein, a NIR-based (1300-2600 nm) detection of heroin and MDMA in colored casework (i.e., brown powders and ecstasy tablets) using a portable analyzer is presented. The application includes a multistage data analysis model based on the net analyte signal (NAS) approach. This identification model was specifically designed for mixture analysis and requires a limited set of pure reference spectra only. Consequently, model calibration efforts are reduced to a minimum. A total of 549 forensic samples was tested comprising brown heroine samples and a variety of colored tablets with different active ingredients. This investigation led to a >99% true negative and >93% true positive rate for heroin and MDMA. These results show that accurate on-site detection in colored casework is possible using NIR spectroscopy combined with an efficient data analysis model. These findings may eventually help in the transition of routine forensic laboratories from laboratory-based techniques to portable equipment operated on scene.

Handheld NIR Spectral Sensor Module Based on a Fully-Integrated Detector Array

For decades, near-infrared (NIR) spectroscopy has been a valuable tool for material analysis in a variety of applications, ranging from industrial process monitoring to quality assessment. Traditional spectrometers are typically bulky, fragile and expensive, which makes them unsuitable for portable and in-field use. Thus, there is a growing interest for miniaturized, robust and low-cost NIR sensors. In this study, we demonstrate a handheld NIR spectral sensor module, based on a fully-integrated multipixel detector array, sensitive in the 850-1700 nm wavelength range. Differently from a spectrometer, the spectral sensor measures a limited number of NIR spectral bands. The capabilities of the spectral sensor module were evaluated alongside a commercially available portable spectrometer for two application cases: to quantify the moisture content in rice grains and to classify plastic types. Both devices achieved the two sensing tasks with comparable performance. Moisture quantification was achieved with a root mean square error (RMSE) prediction of 1.4% and 1.1% by the spectral sensor and spectrometer, respectively. Classification of the plastic type was achieved with a prediction accuracy on unknown samples of 100% and 96.4% by the spectral sensor and spectrometer, respectively. The results from this study are promising and demonstrate the potential for the compact NIR modules to be used in a variety of NIR sensing applications.

Detection, Diagnosis and Treatment of Acute Ischemic Stroke: Current and Future Perspectives

Stroke is one of the leading causes of disability worldwide. Early diagnosis and treatment of stroke are important for better clinical outcome. Rapid and accurate diagnosis of stroke subtypes is critical. This review discusses the advantages and disadvantages of the current diagnostic and assessment techniques used in clinical practice, particularly for diagnosing acute ischemic stroke. Alternative techniques for rapid detection of stroke utilizing blood based biomarkers and novel portable devices employing imaging methods such as volumetric impedance phase-shift spectroscopy, microwave tomography and Doppler ultrasound are also discussed. Current therapeutic approaches for treating acute ischemic stroke using thrombolytic drugs and endovascular thrombectomy are discussed, with a focus on devices and approaches recently developed to treat large cranial vessel occlusions.

State of the Art in Smart Portable, Wearable, Ingestible and Implantable Devices for Health Status Monitoring and Disease Management

Several illnesses that are chronic and acute are becoming more relevant as the world's aging population expands, and the medical sector is transforming rapidly, as a consequence of which the need for "point-of-care" (POC), identification/detection, and real time management of health issues that have been required for a long time are increasing. Biomarkers are biological markers that help to detect status of health or disease. Biosensors' applications are for screening for early detection, chronic disease treatment, health management, and well-being surveillance. Smart devices that allow continual monitoring of vital biomarkers for physiological health monitoring, medical diagnosis, and assessment are becoming increasingly widespread in a variety of applications, ranging from biomedical to healthcare systems of surveillance and monitoring. The term "smart" is used due to the ability of these devices to extract data with intelligence and in real time. Wearable, implantable, ingestible, and portable devices can all be considered smart devices; this is due to their ability of smart interpretation of data, through their smart sensors or biosensors and indicators. Wearable and portable devices have progressed more and more in the shape of various accessories, integrated clothes, and body attachments and inserts. Moreover, implantable and ingestible devices allow for the medical diagnosis and treatment of patients using tiny sensors and biomedical gadgets or devices have become available, thus increasing the quality and efficacy of medical treatments by a significant margin. This article summarizes the state of the art in portable, wearable, ingestible, and implantable devices for health status monitoring and disease management and their possible applications. It also identifies some new technologies that have the potential to contribute to the development of personalized care. Further, these devices are non-invasive in nature, providing information with accuracy and in given time, thus making these devices important for the future use of humanity.

Litter Detection with Deep Learning: A Comparative Study

Pollution in the form of litter in the natural environment is one of the great challenges of our times. Automated litter detection can help assess waste occurrences in the environment. Different machine learning solutions have been explored to develop litter detection tools, thereby supporting research, citizen science, and volunteer clean-up initiatives. However, to the best of our knowledge, no work has investigated the performance of state-of-the-art deep learning object detection approaches in the context of litter detection. In particular, no studies have focused on the assessment of those methods aiming their use in devices with low processing capabilities, e.g., mobile phones, typically employed in citizen science activities. In this paper, we fill this literature gap. We performed a comparative study involving state-of-the-art CNN architectures (e.g., Faster RCNN, Mask-RCNN, EfficientDet, RetinaNet and YOLO-v5), two litter image datasets and a smartphone. We also introduce a new dataset for litter detection, named PlastOPol, composed of 2418 images and 5300 annotations. The experimental results demonstrate that object detectors based on the YOLO family are promising for the construction of litter detection solutions, with superior performance in terms of detection accuracy, processing time, and memory footprint.

Physical and Chemical Sensors on the Basis of Laser-Induced Graphene: Mechanisms, Applications, and Perspectives

Laser-induced graphene (LIG) is produced rapidly by directly irradiating carbonaceous precursors, and it naturally exhibits as a three-dimensional porous structure. Due to advantages such as simple preparation, time-saving, environmental friendliness, low cost, and expanding categories of raw materials, LIG and its derivatives have achieved broad applications in sensors. This has been witnessed in various fields such as wearable devices, disease diagnosis, intelligent robots, and pollution detection. However, despite LIG sensors having demonstrated an excellent capability to monitor physical and chemical parameters, the systematic review of synthesis, sensing mechanisms, and applications of them combined with comparison against other preparation approaches of graphene is still lacking. Here, graphene-based sensors for physical, biological, and chemical detection are reviewed first, followed by the introduction of general preparation methods for the laser-induced method to yield graphene. The preparation and advantages of LIG, sensing mechanisms, and the properties of different types of emerging LIG-based sensors are comprehensively reviewed. Finally, possible solutions to the problems and challenges of preparing LIG and LIG-based sensors are proposed. This review may serve as a detailed reference to guide the development of LIG-based sensors that possess properties for future smart sensors in health care, environmental protection, and industrial production.

Handheld Devices for Food Authentication and Their Applications: A Review

This review summarises miniaturised technologies, commercially available devices, and device applications for food authentication or measurement of features that could potentially be used for authentication. We first focus on the handheld technologies and their generic characteristics: (1) technology types available, (2) their design and mode of operation, and (3) data handling and output systems. Subsequently, applications are reviewed according to commodity type for products of animal and plant origin. The 150 applications of commercial, handheld devices involve a large variety of technologies, such as various types of spectroscopy, imaging, and sensor arrays. The majority of applications, ~60%, aim at food products of plant origin. The technologies are not specifically aimed at certain commodities or product features, and no single technology can be applied for authentication of all commodities. Nevertheless, many useful applications have been developed for many food commodities. However, the use of these applications in practice is still in its infancy. This is largely because for each single application, new spectral databases need to be built and maintained. Therefore, apart from developing applications, a focus on sharing and re-use of data and calibration transfers is pivotal to remove this bottleneck and to increase the implementation of these technologies in practice.

A Smartphone-Enabled Portable Digital Light Processing 3D Printer

3D printing has emerged as an enabling approach in a variety of different fields. However, the bulk volume of printing systems limits the expansion of their applications. In this study, a portable 3D Digital Light Processing (DLP) printer is built based on a smartphone-powered projector and a custom-written smartphone-operated app. Constructs with detailed surface architectures, porous features, or hollow structures, as well as sophisticated tissue analogs, are successfully printed using this platform, by utilizing commercial resins as well as a range of hydrogel-based inks, including poly(ethylene glycol)-diacrylate, gelatin methacryloyl, or allylated gelatin. Moreover, due to the portability of the unique DLP printer, medical implants can be fabricated for point-of-care usage, and cell-laden tissues can be produced in situ, achieving a new milestone for mobile-health technologies. Additionally, the all-in-one printing system described herein enables the integration of the 3D scanning smartphone app to obtain object-derived 3D digital models for subsequent printing. Along with further developments, this portable, modular, and easy-to-use smartphone-enabled DLP printer is anticipated to secure exciting opportunities for applications in resource-limited and point-of-care settings not only in biomedicine but also for home and educational purposes.

Recent advances in portable devices for fruit firmness assessment

Fruit firmness is of vital importance in various links of the fruit supply chain, such as determining harvest time, choosing packaging and transportation methods, regulating storage conditions and predicting shelf life. Portable devices are useful tools to perform on-site measurements of fruit firmness to guide production, optimize processing procedures, improve handling practices and formulate supply strategies. This paper reviews the recent advances in the design and development of portable devices to evaluate fruit firmness based on sensing mechanical, sonic, vibrational and optical properties of fruits. The principle, structure, composition, application and performance of different portable devices are presented. Since each sensor has its merits and limitations, the integration of multiple microsensors to develop a miniaturized, low-cost and facile-operation device may achieve higher sensing performance in determining fruit firmness.

Towards the Development of Portable and In Situ Optical Devices for Detection of Micro and Nanoplastics in Water: A Review on the Current Status

The prevalent nature of micro and nanoplastics (MP/NPs) on environmental pollution and health-related issues has led to the development of various methods, usually based on Fourier-transform infrared (FTIR) and Raman spectroscopies, for their detection. Unfortunately, most of the developed techniques are laboratory-based with little focus on in situ detection of MPs. In this review, we aim to give an up-to-date report on the different optical measurement methods that have been exploited in the screening of MPs isolated from their natural environments, such as water. The progress and the potential of portable optical sensors for field studies of MPs are described, including remote sensing methods. We also propose other optical methods to be considered for the development of potential in situ integrated optical devices for continuous detection of MPs and NPs. Integrated optical solutions are especially necessary for the development of robust portable and in situ optical sensors for the quantitative detection and classification of water-based MPs.

Smart Wearables for Cardiac Autonomic Monitoring in Isolated, Confined and Extreme Environments: A Perspective from Field Research in Antarctica

Antarctica is a space-analog ICE (isolated, cold, and extreme) environment. Cardiovascular and heart autonomic adjustments are key-adaptive physiological responses to Antarctica, both in summer camps and in research stations winter-over. Research fieldwork in ICE environments imposes limitations such as energy restriction, the need for portable and easy-to-handle resources, and resistance of materials to cold and snow/water. Herein, we present the methods we use for cardiac monitoring in the Antarctic field, the limitations of the equipment currently available, and the specific demands for smart wearables to physiological and health tracking in ICE environments, including the increased remote monitoring demand due to COVID-19 restrictions.

Advances in Portable Visual Detection of Pathogenic Bacteria

Food safety and regulation of consumer welfare are of great concern, so it is necessary to be able to detect pathogenic bacteria quickly and effectively. Although traditional methods of pathogen detection are reliable and widely used, the detection and analysis processes are cumbersome and time-consuming, which is not conducive to fast assays in the field. New detection strategies have emerged in recent years, especially point-of-care testing (POCT) methods, which do not rely on the laboratory and have become an important development direction for pathogen detection. Many visual detection schemes have been developed that integrate portable glucose meters (PGMs), test strips, smartphones, and other portable devices. Importantly, portable and ultrasensitive biosensors have vast promise in detecting pathogens, as they can be suitable tools for clinical diagnosis and the regulation of food safety. This Review focuses on the latest advances in portable device-based methods for visual detection of pathogens, evaluating their advantages and disadvantages.

Artificial Neural Network for Atrial Fibrillation Identification in Portable Devices

Atrial fibrillation (AF) is a common cardiac disorder that can cause severe complications. AF diagnosis is typically based on the electrocardiogram (ECG) evaluation in hospitals or in clinical facilities. The aim of the present work is to propose a new artificial neural network for reliable AF identification in ECGs acquired through portable devices. A supervised fully connected artificial neural network (RSL_ANN), receiving 19 ECG features (11 morphological, 4 on F waves and 4 on heart-rate variability (HRV)) in input and discriminating between AF and non-AF classes in output, was created using the repeated structuring and learning (RSL) procedure. RSL_ANN was created and tested on 8028 (training: 4493; validation: 1125; testing: 2410) annotated ECGs belonging to the "AF Classification from a Short Single Lead ECG Recording" database and acquired with the portable KARDIA device by AliveCor. RSL_ANN performance was evaluated in terms of area under the curve (AUC) and confidence intervals (CIs) of the received operating characteristic. RSL_ANN performance was very good and very similar in training, validation and testing datasets. AUC was 91.1% (CI: 89.1-93.0%), 90.2% (CI: 86.2-94.3%) and 90.8% (CI: 88.1-93.5%) for the training, validation and testing datasets, respectively. Thus, RSL_ANN is a promising tool for reliable identification of AF in ECGs acquired by portable devices.

Smartphone and Paper-Based Fluorescence Reader: A Do It Yourself Approach

Given their photoluminescent character, portable quantum dot readers are often sophisticated and relatively expensive. In response, we engineered a "do it yourself" fluorescence reader employing paper materials and a mid-range smartphone camera. Black paperboard facilitated a versatile, lightweight and foldable case; whereas cellophane paper was observed to behave as a simple, yet effective, optical bandpass filter leading to an advantageous device for the quantitative interrogation of quantum dot nanocrystals concentrations (from 2.5 to 20 nM), which are suitable for optical point-of-care biosensing. The streptavidin-coated nanocrystals employed are commercially available and the developed reader was benchmarked with a standard portable quantum dot reader, thereby demonstrating advantages in terms of cost and linear analytical range.

Environmentally Friendly Manufacturing of Flexible Graphite Electrodes for a Wearable Device Monitoring Zinc in Sweat

Electrochemical sensors based on graphite and polymers have emerged as powerful analytical tools for bioanalytical applications. However, most of the fabrication processes are not environmentally friendly because they often involve the use of toxic reagents and generate waste. This study describes an alternative method to produce flexible electrodes in plastic substrates using graphite powder and thermal laminating sheets by solid-solid deposition through hot compression, without the use of hazardous chemical reagents. The electrodes developed through the proposed approach have successfully demonstrated flexibility, robustness, reproducibility (relative standard deviation around 6%), and versatility. The electrodes were thoroughly characterized by cyclic voltammetry, electrochemical impedance spectroscopy, Raman spectroscopy, and scanning electron microscopy. As a proof of concept, the electrode surfaces were modified with bismuth and used for zinc analysis in sweat. The modified electrodes presented linearity (R² = 0.996) for a wide zinc concentration range (50-2000 ppb) and low detection limit (4.31 ppb). The proposed electrodes were tested using real sweat samples and the achieved zinc concentrations did not differ statistically from the data obtained by atomic absorption spectroscopy. To allow wearable applications, a 3D-printed device was fabricated, integrated with the proposed electrochemical system, and fixed at the abdomen by using an elastic tape to collect, store, and analyze the sweat sample. The matrix effect test was performed, spiking the real sample with different zinc levels, and the recovery values varied between 85 and 106%, thus demonstrating adequate accuracy and robustness of the flexible electrodes developed based on the proposed fabrication method.

Evolution of Wearable Devices with Real-Time Disease Monitoring for Personalized Healthcare

Wearable devices are becoming widespread in a wide range of applications, from healthcare to biomedical monitoring systems, which enable continuous measurement of critical biomarkers for medical diagnostics, physiological health monitoring and evaluation. Especially as the elderly population grows globally, various chronic and acute diseases become increasingly important, and the medical industry is changing dramatically due to the need for point-of-care (POC) diagnosis and real-time monitoring of long-term health conditions. Wearable devices have evolved gradually in the form of accessories, integrated clothing, body attachments and body inserts. Over the past few decades, the tremendous development of electronics, biocompatible materials and nanomaterials has resulted in the development of implantable devices that enable the diagnosis and prognosis through small sensors and biomedical devices, and greatly improve the quality and efficacy of medical services. This article summarizes the wearable devices that have been developed to date, and provides a review of their clinical applications. We will also discuss the technical barriers and challenges in the development of wearable devices, and discuss future prospects on wearable biosensors for prevention, personalized medicine and real-time health monitoring.

Perovskite-a Perfect Top Cell for Tandem Devices to Break the S-Q Limit

Up to now, multijunction cell design is the only successful way demonstrated to overcome the Shockley-Quiesser limit for single solar cells. Perovskite materials have been attracting ever-increasing attention owing to their large absorption coefficient, tunable bandgap, low cost, and easy fabrication process. With their rapidly increased power conversion efficiency, organic-inorganic metal halide perovskite-based solar cells have demonstrated themselves as the most promising candidates for next-generation photovoltaic applications. In fact, it is a dream come true for researchers to finally find a perfect top-cell candidate in tandem device design in commercially developed solar cells like single-crystalline silicon and CIGS cells used as the bottom component cells. Here, the recent progress of multijunction solar cells is reviewed, including perovskite/silicon, perovskite/CIGS, perovskite/perovskite, and perovskite/polymer multijunction cells. In addition, some perspectives on using these solar cells in emerging markets such as in portable devices, Internet of Things, etc., as well as an outlook for perovskite-based multijunction solar cells are discussed.

Label-free plasmonic biosensors for point-of-care diagnostics: a review

Introduction: Optical biosensors, particularly those based on nanoplasmonics technology, have emerged in recent decades as a potential solution for disease diagnostics and therapy follow-up at the point-of-care (POC). These biosensor platforms could overcome some of the challenges faced in conventional diagnosis techniques offering label-free assays with immediate results and employing small and user-friendly devices. Areas covered: In this review, we will provide a critical overview of the recent advances in the development of nanoplasmonic biosensors for the POC diagnostics. We focus on those systems with demonstrated capabilities for integration in portable platforms, highlighting some of the most relevant diagnostics applications targeting proteins, nucleic acids, and cells as disease biomarkers. Expert commentary: Despite the attractive features of label-free nanoplasmonic sensors in terms of miniaturization and analytical robustness, the route toward an effective clinical implementation involves the integration of fully automated microfluidic systems for sample processing and analysis, and the optimization of surface biofunctionalization procedures. Additionally, the development of multiplexed sensors for high-throughput analysis and including specific neoantigens and novel biomarkers in detection panels will provide the means for delivering a powerful analytical technology for an accurate and improved medical diagnosis.

Different Ways to Apply a Measurement Instrument of E-Nose Type to Evaluate Ambient Air Quality with Respect to Odour Nuisance in a Vicinity of Municipal Processing Plants

This review paper presents different ways to apply a measurement instrument of e-nose type to evaluate ambient air with respect to detection of the odorants characterized by unpleasant odour in a vicinity of municipal processing plants. An emphasis was put on the following applications of the electronic nose instruments: monitoring networks, remote controlled robots and drones as well as portable devices. Moreover, this paper presents commercially available sensors utilized in the electronic noses and characterized by the limit of quantification below 1 ppm v/v, which is close to the odour threshold of some odorants. Additionally, information about bioelectronic noses being a possible alternative to electronic noses and their principle of operation and application potential in the field of air evaluation with respect to detection of the odorants characterized by unpleasant odour was provided.