Diagnostic Devices Research Articles

A Multi-Channel Handheld Diagnostic Device Based on Green Biomimetic Material for Point-of-Care Testing of Vitamin C in Human Fluids.

In the era of "Great Health", maintaining an appropriate level of vitamin C is crucial for human health as it directly impacts the proper functioning of the immune system. In this study, a handheld nonenzymatic electrochemical sensor based on biomimetic material prussian blue functionalized polydopamine is proposed for point-of-care testing (POCT) of vitamin C in human fluids. Particularly, Prussian blue, known as a bio-antidote, and polydopamine, a main component of cuttlefish ink, ensure the safety and reliability of home testing. The experimental results quantitatively demonstrate that this electrochemical POCT sensor enables rapid and accurate determination of vitamin C with a wide linear detection range from 0.2 to 200µm, a low limit of detection at 0.03µm, and high sensitivity at 0.33µAµm-1cm-2. More importantly, the performance evaluation using human urine and saliva samples confirms satisfactory accuracy and recovery rates for vitamin C determination by this electrochemical POCT sensor. Thus, the proposed handheld electrochemical POCT sensor holds potential utility as an affordable tool for VC determination and home-based healthcare.

Chemical Heating for Minimally Instrumented Point-of-Care (POC) Molecular Diagnostics

The minimal instrumentation of portable medical diagnostic devices for point-of-care applications is facilitated by using chemical heating in place of temperature-regulated electrical heaters. The main applications are for isothermal nucleic acid amplification tests (NAATs) and other enzymatic assays that require elevated, controlled temperatures. In the most common implementation, heat is generated by the exothermic reaction of a metal (e.g., magnesium, calcium, or lithium) with water or air, buffered by a phase-change material that maintains a near-constant temperature to heat the assay reactions. The ability to incubate NAATs electricity-free and to further to detect amplification with minimal instrumentation opens the door for fully disposable, inexpensive molecular diagnostic devices that can be used for pathogen detection as needed in resource-limited areas and during natural disasters, wars, and civil disturbances when access to electricity may be interrupted. Several design approaches are reviewed, including more elaborate schemes for multiple stages of incubation at different temperatures.

Innovative Peptide-Based Plasmonic Optical Biosensor for the Determination of Cholesterol

Plasmonic-based biosensors have gained prominence as potent optical biosensing platforms in both scientific and medical research, attributable to their enhanced sensitivity and precision in detecting biomolecular and chemical interactions. However, the detection of low molecular weight analytes with high sensitivity and specificity remains a complex and unresolved issue, posing significant limitations for the advancement of clinical diagnostic tools and medical device technologies. Notably, abnormal cholesterol levels are a well-established indicator of various pathological conditions; yet, the quantitative detection of the free form of cholesterol is complicated by its small molecular size, pronounced hydrophobicity, and the necessity for mediator molecules to achieve efficient sensing. In the present study, a novel strategy for cholesterol quantification was developed, leveraging a plasmonic optical readout in conjunction with a highly specific cholesterol-binding peptide (C-pept) as a biorecognition element, anchored on a functionalized silica substrate. The resulting biosensor exhibited an exceptionally low detection limit of 21.95 µM and demonstrated a linear response in the 10–200 µM range. This peptide-integrated plasmonic sensor introduces a novel one-step competitive method for cholesterol quantification, positioning itself as a highly sensitive biosensing modality for implementation within the AVAC platform, which operates using reflective dark-field microscopy.

Optimization of upper respiratory tract cancer diagnosis method based on exhaled breath gas analysis

Introduction. Head and neck tumors comprise about 7 % of all malignant neoplasms. In the head and neck area, tumors are usually located on the tongue (25–40 %) and floor of mouth (15–20 %). In the majority of cases, diagnosis, especially at early disease stages, is based on clinical and histopathological evaluation of tumor process. However, recently development and implementation of non-invasive techniques of early diagnosis of upper respiratory tract tumors through detection of pathognomonic volatile tumor markers in the exhaled air has become topical.Aim. To evaluate diagnostic accuracy of sensory gas analysis device and artificial neural network for examination of exhaled gas samples from patients with oropharyngeal, laryngeal, laryngopharyngeal cancer and to establish the optimal conditions for sampling.Materials and methods. The study included 28 patients with oropharyngeal, laryngeal, laryngopharyngeal cancers and 25 healthy volunteers. The proposed technique is based on analysis of samples of exhaled gas from the studied individuals using a diagnostic device developed by the authors. The device detects volatile compounds in the exhaled air using a set of semiconductor sensors with subsequent analysis by a neural network. The exhaled air was sampled using two methods: in the morning in the fasted state before daily hygienic procedures and physical activity (prepared samples) and in the context of everyday life, nutrition and hygiene without restrictions before sampling (non-prepared samples).Results. Based on the signals from the sensors, the neural network classified and detected patients with malignant tumors. Accuracy of the prepared samples from healthy volunteers and patients with oropharyngeal, laryngeal, laryngopharyngeal cancers was 79.17 %, of non-prepared – 84.09 %.Conclusion. High diagnostic accuracy of the developed technique of non-invasive diagnosis of malignant tumors of the oropharyngeal, laryngeal, laryngopharyngeal areas using exhaled air samples which does not require special preparation of the studied samples was demonstrated.

The influence of the general vibration on the quality of the assessment of the pilot's physiological indicators

The article considers flight safety issues related to continuous monitoring of the pilot's functional state by using means of monitoring physiological health indicators, which is due to the complexity of flight work, accompanied by a whole range of unfavorable factors that reduce the efficiency of professional activity. The article studies the influence of the general vibration factor on the quality (accuracy) of the assessment of the pilot's physiological indicators recorded by non-invasive diagnostic devices in transmitted light. Such indicators include heart rate, fractional blood saturation level, and respiratory rate. A mathematical model of quasi-deterministic general vibration, which is the resultant of individual frequency components of corrected vibration acceleration directed along three axes of the Cartesian coordinate system, has been developed. Mathematical modeling of the effect of general vibration on the information photoplethysmographic signal has been performed and it has been shown that the effect changes the frequency-time structure of the signal and relative errors of the estimated physiological parameters appear – the level of fractional blood saturation (4.16 %), heart rate (4.78 %) and respiration (3.75 %). As a result of a practical experiment to analyze the effect of general vibration on the quality of assessment of the specified physiological parameters, it was found that, compared to the declared error of a pulse oximeter of ±2 %, the errors in determining the heart rate, fractional blood saturation and respiration rate increased by 3.221 %; 2.483 % and 1.906 %, respectively. The results of theoretical and practical studies have a strong pair correlation according to Pearson, the pair correlation coefficients were 0.72, 0.83, 0.76 for the results of measurements of heart rate, fractional blood saturation level and respiratory rate, respectively, which indicates the validity of the adopted simplifi ations in the development of the mathematical model. The obtained results can be used to develop devices for non-invasive diagnostics of the pilot's physiological indicators, functioning directly during the flight.

Development of the continuous ambulatory vestibular assessment (CAVA) system to provide an automatic diagnosis for vestibular conditions: protocol for a multicentre, single-arm, non-randomised clinical trial

IntroductionDizziness is a common symptom that can occur in an unpredictable and episodic manner leading to the imprecise reporting of symptoms. Patients will often see many specialists before receiving a...

A computational study on the detection properties of pristine, Al-, and Ga- doped Zn12O12 nanoclusters toward Deferiprone in gas and solvent phases

Electrochemical sensors have great potential in point-of-care diagnostic devices, benefiting from advancements in nanomaterials that enhance sensitivity and selectivity and reduce costs. This study theoretically investigates Deferiprone (DEF) sensing using pristine and aluminum – and gallium-doped Zn12O12 nanoclusters (AlZn11O12 and GaZn11O12) through a density functional theory (DFT) approach at the B3LYP-D level with a 6-311G (d, p) basis set. The results indicate DEF adsorption energies of −29.53 kcal mol−1 for Zn12O12, −42.19 kcal mol−1 for AlZn11O12, and −27.12 kcal mol−1 for GaZn11O12 in their most stable orientations. The adsorption of DEF significantly alters the energy gap (Eg) in the doped nanoclusters, highlighting the superior sensitivity of AlZn11O12 and GaZn11O12 for DEF detection. Transition theory calculations reveal a practical recovery time of 72.64 s for GaZn11O12, indicating favourable adsorption characteristics. Solvent effect studies show that the DEF/GaZn11O12 complex is stable in water, with a higher dipole moment reflecting increased water polarisation. UV-Vis analysis demonstrates that DEF adsorption on GaZn11O12 shifts the spectrum to higher wavelengths, indicating enhanced adsorption. Thus, GaZn11O12 is proposed as a promising candidate for DEF detection in both gas and solvent phases.

A Flexible Antibacterial Gel Electrochemiluminescence Device for Monitoring and Therapy of Chronic Diabetic Wounds

ABSTRACTThe rapid development of internal light‐driven photodynamic therapy stems from its capability to eliminate bulky physical light sources, addressing the medical requirements for comfort and portability in long‐term diabetic wound management. To overcome limitations such as tissue penetration depth and controllability of internal light sources, this study introduces an antibacterial gel electrochemiluminescence device for the treatment of diabetic wounds and the monitoring of wound bacteria. We deploy a large‐area luminescent device combining flexible screen‐printed electrodes and a dual‐network hydrogel, in which photodynamic therapy is driven by Ru@COFs' nanoconfinement‐enhanced near‐infrared electrochemiluminescence to achieve a deeper and safer antibacterial effect. The custom‐sized screen‐printed electrodes inherit the inborn electrochemical sensing function and enable intimate contact between reactive oxygen species and the wound. The device avoids physical light sources and provides a new paradigm for developing miniaturized integrated diagnostic and therapeutic wearable devices.

Drug Efficacy Estimation for Follow-on Companion Diagnostic Devices Through External Studies.

A therapeutic product is usually not suitable for all patients but for only a subpopulation. The safe and effective use of such a therapeutic product requires the co-approval of a companion diagnostic device which can be used to identify suitable patients. While the first-of-a-kind companion diagnostic device is often developed in conjunction with its intended therapeutic product and simultaneously validated through a randomized clinical trial, there remains room for the innovation of new and improved follow-on companion diagnostic devices designed for the same therapeutic product. However, conducting a new randomized trial or a bridging study for the follow on companion devices may be unethical, expensive or unpractical. Hence, there arises a need for an external study to evaluate the concordance between the FDA-approved comparator companion diagnostic device (CCD) and the subsequent follow-on companion diagnostic devices (FCD), indirectly validating the latter. In this article, we introduce a novel external study design, referred to as the targeted treatment design, as an extension of the existing concordance design. Additionally, we present corresponding statistical analysis methods. Our approach combines the CCD randomized trial data and the FCD external study data, enabling the estimation of drug efficacy within the FCD+ and FCD- subpopulations-the parameters crucial for the validation of the FCD. Theoretical results and simulation studies validate the proposed methods and we further illustrate the proposed methods through an application in a real example of non-small-cell lung cancer.

Administrative Aspects of Molecular Diagnostics-Oversight, Regulatory Approval Process, Clinical and Operational Workflows, and Payment Models.

This paper discusses the administrative aspects of molecular diagnostics in oncology, including US Food and Drug Administration (FDA) oversight, the regulatory approval process, clinical, and operational workflows, and payment models. Comprehensive molecular testing is important to deliver optimal oncology care and improve patient outcomes. Despite the potential benefits of testing, utilization remains low. The FDA regulatory approval process is reviewed for in vitro diagnostic products, which includes classification into three regulatory classes on the basis of risk. Companion diagnostic devices are used to guide treatment decisions. The clinical and operational challenges associated with molecular testing in oncology are also discussed, including the rapidly evolving landscape of precision oncology, the wide range of biomarker testing options, and complexities of test ordering, interpretation, and result delivery. There is a need for a multifaceted support approach involving education, technology enhancements, and workflow support to overcome these challenges. In terms of payment models, coverage policies between Medicare and commercial payers are compared with differences in coverage criteria, with Medicare focusing on FDA approval or clearance, whereas commercial payers consider additional factors such as National Comprehensive Cancer Network and ASCO guidelines. Commercial payers tend to cover smaller panels on the basis of guideline-recommended biomarkers, whereas coverage for broad tumor profiling is limited. Several strategies can increase the utilization of molecular testing, including integrating test results into electronic medical record platforms, standardizing billing practices, increasing clinical trials, and primary literature supporting the use of molecular testing, educating physicians, and using tumor boards for result interpretation and treatment discussions.

Comparison of Precision, Agreement, and Accuracy of Two Swept-Source Optical Coherence Tomography Biometers.

Background/Objectives: This study's aim was to compare the precision, agreement, and accuracy in axial length (AL) measurements of Argos® (Alcon Healthcare, US) and Eyestar 900® (Haag-Streit, Switzerland) swept-source optical coherence tomography (SS-OCT) biometers. Methods: We performed a prospective evaluation of two diagnostic devices. Three consecutive measurements of AL with the Argos® and the Eyestar® 900 SS-OCT biometers were conducted in random order in eyes undergoing cataract surgery in Barcelona, Spain. The main endpoint was the median difference in AL between devices. Secondary endpoints included agreement on Bland-Altman plots and 95% limits of agreement (LoAs), repeatability as measured within-subject standard deviation (SW), percent of failed AL measurements, percent of eyes within ±0.50 D and ±1.00 D one month after surgery, and median and mean prediction error. Results: We included 107 eyes of 107 patients (60.8% females, mean age of 73.1 years). The median difference in AL (Argos®-Eyestar 900®) was -0.01 mm (interquartile range [IQR], 0.06), p = 0.01. The 95% LoAs were -0.11 to +0.08 mm, with a trend towards less extreme measurements with Argos® for very short and long eyes. The median (IQR) Sw was 0.0058 (0.0058) and 0.0000 (0.0058) for Argos® and Eyestar 900®, respectively. There were no failed AL measurements with either device (0%, 95% CI = 0% to 3.4%). Overall, 96.1% of eyes were within ±0.50 D and 100% were within ±1.00 D. Conclusions: Argos® and Eyestar 900® provided statistically different but clinically negligible differences in AL. However, they are not interchangeable in very long or short eyes, due to the different principles used to determine AL.

Fabrication of a Polyglycolic Acid Porous Microneedle Array Patch Using the Nonsolvent Induced Phase Separation Method for Body Fluid Extraction

ABSTRACTTraditional blood sampling is essential for early diagnosis and subsequent analysis, but the methods using hypodermic needles are painful and burdensome. Recently, a minimally invasive approach utilizing porous microneedles has been developed and various porous microneedle array patches (MAPs) composed of biodegradable polymers have been investigated. To address issues about low mechanical strength and liquid absorption with porous MAPs, we used polyglycolic acid (PGA) as it is a biodegradable and hydrophilic polymer with high mechanical properties. In this study, we established a nonsolvent‐induced phase separation (NIPS) method for the fabrication of PGA porous MAPs, as the porous MAPs can be fabricated by simply immersing the molds injected with PGA‐hexafluoro‐2‐propanol (HFIP) solution in nonsolvents. We achieved the maximum liquid absorption rate of 16 ± 8.2 × 10−2 µL/min per one microneedle using the PGA porous MAPs fabricated by using ethanol as nonsolvent and PGA concentration of 10% (w/w). Our study provides a comprehensive understanding of porous MAPs fabricated using PGA material as well as its characteristics regarding the structural and mechanical properties of PGA MAPs, with potential as a diagnostic device to substitute conventional hypodermic needles for interstitial fluid (ISF) sampling and diagnosis.

The effectiveness of a mobile mammography units in breast cancer screening

Breast cancer remains the leading cause of death in the female population. Screening studies are conducted in order to detect the disease at an early stage. At the same time, domestic authors emphasize the lack of alternatives to preventive mammography in breast cancer screening and the prospects of using mobile mammographs for early diagnosis of breast cancer and precancerous breast diseases.Aim. To evaluat the results of the use of mobile mammography units for active and early detection of breast cancer.Materials and methods. The research uses methods of content analysis, information and analytical materials of Russian and foreign researchers, and forms of federal statistical observation. Statistical research methods were used to analyze the data obtained.Results. Regression analysis with a very low probability of error (p = 0.001) showed that the larger the total volume of mammographic studies with preventive purposes in the subjects of the Russian Federation, the higher the proportion of cases of active detection of breast cancer, although this relationship is rather weak. Taking into account the obtained value of R2 (0.192), only 19.2% of the increase in the proportion of breast cancer cases detected actively can be explained by an increase in the volume of preventive mammograms. The correlation analysis showed that the volumes of preventive mammograms performed using mobile devices in the subjects of the Russian Federation were not associated with either the proportion of breast cancer cases detected actively or with the proportion of breast cancer cases detected in the early stages. At the same time, it is worth noting that the obtained value of p ≥ 0.5 indicates a statistically insignificant result of evaluating the relationship between variables, the interpretation of which should be performed with caution.Conclusion. Despite the high cost of mobile mammography units, the increase in their number in the subjects of the Russian Federation and the growth in their activities, the contribution of these diagnostic devices to solving the problem of early and active diagnosis of breast cancer remains uncertain. More promising are personalized approaches to the timely detection of cancers, including breast cancer, based on an assessment of the individual risk of their occurrence.

Friction in soft biological systems and surface self-organization: the role of viscoelasticity

AbstractFriction is a critical factor in the proper functioning of human organs as well as in the potential development of disease. It is also important for the design of diagnostic and interventional medical devices. Nanoscale surface roughness, viscoelastic or plastic deformations, wear, and lubrication all influence the functions of individual cells. The effects of friction in soft matter systems are quantified using different types of frictional coefficients, including the dynamic friction coefficient, friction-skin drag, and pressure drag. These coefficients are determined by the viscoelastic properties of the two systems in contact and their relative velocity. In this review, several biological systems are considered, including (i) epithelial tissues in contact with soft hydrogel-like implants, (ii) the collective migration of epithelial monolayers on substrate matrices, (iii) blood flow through blood vessels, and (iv) the movement of cancer cells past epithelial clusters along with the migration of epithelial cells within the cluster.

Using Bland-Altman plot-based harmonization algorithm to optimize the harmonization for immunoassays.

Harmonization has been recommended by theInternational Organization for Standard (ISO) to achieve equivalent results across invitro diagnostic measurement devices (IVD-MDs). We aim to evaluate the effectiveness of Bland-Altman plot-based harmonization algorithm (BA-BHA) created in this study and compare it with weighted Deming regression-based harmonization algorithm (WD-BHA) proposed in ISO 21151:2020. Eighty patient sera were used as the harmonization reference material (HRM) to develop IVD-MD-specific harmonization algorithms. Another panel of 40 patient sera was used to validate the effectiveness of harmonization algorithms. We compared regression slopes, intercepts, Bland-Altman plot layouts, percent differences, limits of agreement (LoAs), between-method coefficients of variation (CV) before and after harmonization. After harmonization by WD-BHA, acceptable slopes and intercepts between measured values and HRM targets were observed in weighted Deming regression, but not in Passing-Bablok analysis. Mean differences were-5.5 to 5.0 % and differences at specific levels were-33.9 to 23.9 %. LoAs were-64.6 to 74.6 %. Between-method CV was 22.9 % (±12.9 %). However, after harmonization by BA-BHA, both weighted Deming and Passing-Bablok regressions equations presented harmonized results. Mean differences were-0.3 to 0.2 % and differences at specific levels were-1.1 to 1.6 %. LoAs were-23.3 to 23.2 %. Between-method CV was 8.4 % (±4.0 %). The data points were evenly distributed at both sides of the mean in Bland-Altman plots. The inequivalence of test results between different methods can be improved but unacceptable analytical differences at specific levels may be hidden in terms of an acceptable slope and intercept on WD-BHA. The new protocol BA-BHA may be a viable alternative to optimize the harmonization for immunoassays.

Zwitterionic Polymers for Biomedical Applications: Antimicrobial and Antifouling Strategies toward Implantable Medical Devices and Drug Delivery.

Poly(ethylene glycol) (PEG) is extensively utilized in biomedical applications due to its biocompatibility; however, its thermal instability and susceptibility to oxidative degradation significantly constrain its long-term effectiveness. Zwitterionic polymers, characterized by their distinctive structure, enhanced stability, and superior biocompatibility, offer a more advantageous alternative. These polymers exhibit super hydrophilicity, resist nonspecific protein adsorption, and maintain stability in biological environments due to their charge-neutral ionic nature. Zwitterionic polymers enhance anticancer drug delivery by precisely targeting tumor cells and facilitating an efficient drug release. Their inherent antifouling properties and prolonged circulation within the bloodstream render them highly suitable for redox-sensitive drug carriers, thereby augmenting the antitumor efficacy. Moreover, zwitterionic polymers markedly mitigate biofouling in implants, biosensors, and wound dressings, thereby improving both their functionality and their therapeutic outcomes. These advantages arise from the formation of robust hydration layers, which significantly enhance the hemocompatibility and inhibit the adhesion of proteins, platelets, and bacteria. Zwitterionic polymers, including sulfobetaine (SB), phosphorylcholine (PC), and carboxybetaine (CB), are increasingly employed in blood-contacting devices and as effective coating materials for implantable devices. This mini-review paper aims to explore the recent diverse biomedical applications of zwitterionic polymers and highlight their advantageous properties compared with unmodified polymers. We will cover their use in drug delivery systems, tumor targeting nanocarriers, antibiofouling and antibacterial activities in implantable devices, tissue engineering, and diagnostic devices, demonstrating how their unique properties can translate into different applications. Through this exploration, this Perspective will display the potential of zwitterionic polymers as innovative polymer materials in the field of biomedical engineering and beyond.

Public evidence on AI products for digital pathology

Novel products applying artificial intelligence (AI)-based methods to digital pathology images are touted to have many uses and benefits. However, publicly available information for products can be variable, with few sources of independent evidence. This review aimed to identify public evidence for AI-based products for digital pathology. Key features of products on the European Economic Area/Great Britain (EEA/GB) markets were examined, including their regulatory approval, intended use, and published validation studies. There were 26 AI-based products that met the inclusion criteria and, of these, 24 had received regulatory approval via the self-certification route as General in vitro diagnostic (IVD) medical devices. Only 10 of the products (38%) had peer-reviewed internal validation studies and 11 products (42%) had peer-reviewed external validation studies. To support transparency an online register was developed using identified public evidence (https://osf.io/gb84r/), which we anticipate will provide an accessible resource on novel devices and support decision making.

Deep transfer learning with improved crayfish optimization algorithm for oral squamous cell carcinoma cancer recognition using histopathological images

Oral Squamous Cell Carcinoma (OSCC) causes a severe challenge in oncology due to the lack of diagnostic devices, leading to delays in detecting the disorder. The OSCC diagnosis through histopathology demands a pathologist expert because the cellular presentation is variable and highly complex. Existing diagnostic approaches for OSCC have specific efficiency and accuracy restrictions, highlighting the necessity for more reliable techniques. The increase of deep neural networks (DNN) model and their applications in medical imaging have been instrumental in disease diagnosis and detection. Automatic detection systems using deep learning (DL) approaches show tremendous promise in investigating medical imagery with speed, efficiency, and accuracy. In terms of OSCC, this system allows the diagnostic method to be streamlined, facilitating earlier diagnosis and enhancing survival rates. Automatic analysis of histopathological image (HI) can assist in accurately detecting and identifying tumorous tissue, reducing diagnostic turnaround times and increasing the efficacy of pathologists. This study presents a Squeeze-Excitation with Hybrid Deep Learning for Oral Squamous Cell Carcinoma Recognition (SEHDL-OSCCR) on HIs. The presented SEHDL-OSCCR technique mainly focuses on detecting oral cancer (OC) using hybrid DL models. The bilateral filtering (BF) technique is initially used to remove the noise. Next, the SEHDL-OSCCR technique employs the SE-CapsNet model to recognize the feature extractors. An improved crayfish optimization algorithm (ICOA) technique is utilized to improve the performance of the SE-CapsNet model. At last, the classification of the OSCC technique is performed by employing a convolutional neural network with a bidirectional long short-term memory (CNN-BiLSTM) model. The simulation results obtained using the SEHDL-OSCCR technique are investigated using a benchmark medical image dataset. The experimental validation of the SEHDL-OSCCR technique illustrated a greater accuracy outcome of 98.75% compared to recent approaches.

CFTrack: Advanced Diagnostic, Monitoring, and Tracking Device for Cystic Fibrosis Care.

Cystic fibrosis (CF) is a genetic disorder that primarily affects the respiratory, digestive, and reproductive systems. In the United States, approximately 32,000 individuals, spanning both children and adults, suffer from CF, and roughly 1,000 new cases are diagnosed annually. The current gold standard for CF diagnosis is the sweat test, yet this method is plagued by issues such as being time-consuming, expensive, challenging to replicate, and lacking treatment monitoring capabilities. In contrast, the emerging field of wearable sweat biosensors has gained significant attention due to their potential for noninvasive health monitoring. Despite this, there remains a conspicuous absence of a wearable sweat biosensor tailored specifically for CF diagnosis and monitoring. Here, this study introduces a flexible wearable sweat biosensor, named CFTrack, designed to address the unique challenges associated with CF. This proposed CFTrack biosensor not only facilitates CF diagnosis but also enables the monitoring of medication treatment effectiveness and tracks therapy activities. In addition, it operates in a self-powered and customized manner, ensuring seamless integration into the daily lives of individuals with CF. Given that sweat tests and fitness routines are the predominant methods for diagnosing and treating cystic fibrosis patients, respectively, the proposed CFTrack biosensor leverages ion concentration in sweat for diagnostic purposes. Additionally, it incorporates a motion-tracking function to monitor physical activity, providing a comprehensive approach to CF management. To evaluate the feasibility of the proposed CFTrack biosensor, a comprehensive evaluation has been performed including numerical simulations, theoretical analyses, and experimental tests. The results demonstrate the efficacy of the proposed CFTrack biosensor in diagnosing and monitoring CF conditions while also showcasing its ability to effectively track the progress of patients undergoing physical therapy. The proposed CFTrack biosensor resolves key issues associated with existing sweat sensors including high energy consumption, intricate fabrication procedures, and the absence of continuous monitoring capabilities. By addressing these challenges, the proposed sweat biosensor aims to revolutionize CF diagnosis and monitoring, offering a more efficient and user-friendly alternative to current methods.

Ultrasonic A-Scan Signals Data Augmentation Using Electromechanical System Modelling to Enhance Cataract Classification Methods

The use of artificial intelligence in diverse diagnosis areas has significantly increased in the past few years because of the advantages it represents in clinical routine. Among the diverse diagnostic techniques, the use of ultrasounds is often preferred because of their simplicity, low cost, non-invasiveness, and non-ionizing characteristic. However, obtaining an adequate number of patients and data for training and testing machine learning models is challenging. To overcome this limitation, a novel approach is proposed for simulating data produced by ultrasonic diagnostic devices. The implemented method was based on a clinical prototype for eye cataract diagnosis, although the method can be extended to other applications as well. The proposed model encompasses the electric-to-acoustic signal conversion in the ultrasonic transducer, the wave propagation through the biological medium, and the subsequent acoustic-to-electric signal conversion in the transducer. Electrical modelling of the transducer was performed using a two-port network approach, while the acoustic wave propagation was modelled by using the k-Wave MATLAB toolbox. It was verified that the holistic modelling approach enabled the generation of synthetic data augmentation, presenting high similarity with real data.