Non-invasive Monitoring Method Research Articles

The Skin as a Window to Diabetes Mellitus: Manifestations, Complications and Clinical Insights

Introduction and purpose Diabetes mellitus (DM) is a chronic disease with a growing global prevalence, affecting 8.3% of adults, with a significant proportion remaining undiagnosed. The condition impacts multiple organ systems, including the skin, where manifestations often represent the earliest and most visible signs of metabolic dysregulation. Skin changes associated with DM, such as acanthosis nigricans, xerosis, diabetic dermopathy and necrobiosis lipoidica, not only highlight underlying metabolic disturbances but also provide valuable non-invasive tools for monitoring glycemic control and disease progression. Material and methods This study is based on a comprehensive review of recent literature focusing on the skin manifestations and clinical implications of diabetes mellitus -related skin changes. Description of the State of KnowledgeHyperglycemia disrupts normal cellular processes in the skin, leading to impaired wound healing, increased oxidative stress, and inflammation. These pathological changes contribute to various dermatological symptoms, including xerosis, pruritus, erythema, and fibrosis. Skin changes, such as diabetic dermopathy, necrobiosis lipoidica, and recurrent fungal infections, are not only indicators of DM but also reflect glycemic control and disease severity. These manifestations can signal undiagnosed diabetes or poorly controlled blood glucose levels, offering a non-invasive method for disease monitoring. ConclusionsSkin manifestations are vital diagnostic tools in diabetes care, providing early indications of metabolic imbalances and poor glycemic control. Their presence underscores the need for timely interventions, including lifestyle modifications, pharmacological treatments, and patient education. Dermatological assessments, particularly in resource-limited settings, offer an accessible approach to monitoring therapy effectiveness and predicting complications.

Comprehensive Learning Salp Swarm Algorithm with Ensemble Deep Learning-based ECG Signal Classification on Internet of Things Environment

The Internet of Things (IoT) in healthcare relates to implementing interconnected devices and systems for collecting and sharing healthcare information in real time. The integration of IoT in healthcare has the potential to enhance patient outcomes, reduce healthcare costs, and improve the efficacy of medical services. Electrocardiogram (ECG) is a non-invasive heart monitoring method that has become widely accessible due to user-friendly, low-cost, and lead-free wearable heart monitors. However, relying on overworked caregivers for manual monitoring is inefficient. This study develops a Comprehensive Learning Salp Swarm Algorithm with Ensemble Deep Learning (CLSSA-EDL) technique for ECG signal classification in IoT healthcare. The objective of CLSSA-EDL is to detect and classify ECG signals to support decision-making in the IoT healthcare environment. The CLSSA-EDL approach employs the DenseNet201 feature extraction method, with hyperparameters optimally selected by the CLSSA system. For ECG signal detection and classification, an ensemble model using a Stacked Autoencoder (SAE), Gated Recurrent Unit (GRU), and Long Short-Term Memory (LSTM) is utilized. The CLSSA-EDL technique was evaluated on a benchmark ECG dataset, achieving an accuracy of 98.7%, sensitivity of 97.5%, and specificity of 99.1%, demonstrating superior performance compared to recent algorithms.

Pulse oximetry at two sensor placement sites in conscious foals

BackgroundPulse oximetry has not been thoroughly evaluated for assessment of oxygenation in conscious foals. Compared with invasive arterial blood sampling, it is a painless and non-invasive method for real-time monitoring of blood oxygen saturation. The aim of this prospective clinical study was to evaluate the usability, validity, and reliability of pulse oximetry at two measuring sites (lip and caudal abdominal skin fold) for blood oxygen saturation measurement in conscious foals with and without respiratory compromise. Thirty-two foals under one month of age were used. Nineteen foals had normal respiratory and cardiovascular function, and 13 had pneumonia. Pulse oximetry with a transmittance sensor was performed in triplicate on each foal’s lip (n = 196 measurements) and/or skin fold (n = 338 measurements), and arterial blood sample was collected. The oxygen saturation values measured by pulse oximetry from the lip and skin fold were compared with each other (n = 58 measurement pairs) and with the calculated arterial oxygen saturation based on arterial blood samples (n = 93 measurement pairs). Furthermore, repeatability of the pulse oximetry measurements was assessed.ResultsMeasured blood oxygen saturation was clearly associated with the calculated saturation, but on average (± SD) it was 1.8 (± 3.3) percentage units higher from the lip and 5.7 (± 4.3) percentage units higher from the skin fold than the calculated saturation. In concurrent lip and skin fold measurements within a foal, the skin fold measurements were 2.4 (± 2.4) percentage units higher than the lip measurements. The repeatability of three pulse oximetry saturation measurement results was moderate to good and significantly improved when the measurement furthest from the middle-measured value was excluded. The most deviating measurement was often obtained first. Pulse oximetry in general was well tolerated and easy to perform, but as expected in conscious foals, movement and contact problems generated occasional technical difficulties in some individuals.ConclusionsIn conscious foals, pulse oximetry with a transmittance sensor attached to the lip (but not to the skin fold) is a clinically applicable and valid method for arterial blood oxygen saturation determination. Several measurements should be obtained and outliers discarded to obtain a reliable result.

A novel method for detecting intracranial pressure changes by monitoring cerebral perfusion via electrical impedance tomography

BackgroundAcute and critical neurological diseases are often accompanied with elevated intracranial pressure (ICP), leading to insufficient cerebral perfusion, which may cause severe secondary lesion. Existing ICP monitoring techniques often fail to effectively meet the demand for real-time noninvasive ICP monitoring and warning. This study aimed to explore the use of electrical impedance tomography (EIT) to provide real-time early warning of elevated ICP by observing cerebral perfusion.MethodsAn intracranial hypertension model was prepared by injecting autologous un-anticoagulated blood into the brain parenchyma of twelve Landrace swine. Invasive ICP monitoring was used as a control method, and a high-precision EIT system was used to acquire and analyze the changing patterns of cerebral perfusion EIT image parameters with respect to ICP. Four EIT parameters related to cerebral perfusion were extracted from the images, and their potential application in detecting ICP elevation was analyzed.ResultsWhen ICP increased, all EIT perfusion parameters decreased significantly (P < 0.05). When the subjects were in a state of intracranial hypertension (ICP > 22 mmHg), the correlation between EIT perfusion parameters and ICP was more significant (P < 0.01), with correlation coefficients ranging from −0.72 to −0.83. We tested the objects when they were in baseline ICP and in ICP of 15–40 mmHg. Under both circumstances, ROC curve analysis showed that the comprehensive model of perfusion parameters based on the random forest algorithm had a sensitivity and specificity of more than 90% and an area under the curve (AUC) of more than 0.9 for detecting ICP increments of both 5 and 10 mmHg.ConclusionThis study demonstrates the feasibility of using perfusion EIT to detect ICP increases in real time, which may provide a new method for real-time non-invasive monitoring of patients with increased ICP.

P0291 Tailoring Crohn’s disease surveillance after ileocolic resection: the importance of inflammatory biomarkers

Abstract Background Recurrence of Crohn’s disease (CD) after ileocolic resection is common. However, reliable non-invasive monitoring methods are lacking, for instance, the use of faecal calprotectin (FC) has showed inconsistent results in this subgroup of patients. The aim of this study was to evaluate clinical and biochemical factors associated with post-operative endoscopic recurrence in CD patients. Methods Retrospective single-center study including patients with CD who underwent ileocolonoscopy for CD surveillance, after ileocolic resection. The patients’ clinical status was evaluated through Harvey-Bradshaw index (HBI), with clinical remission considered as ≤ 4 points. Biochemical parameters included erythrocyte sedimentation rate (ESR), c-reactive protein (CRP) and FC. Clinical and biochemical parameters were evaluated in the 6 months prior to ileocolonoscopy. Post-operative endoscopic recurrence was defined as a Rutgeerts score ≥ i2b. Results A total of 81 patients and 121 ileocolonoscopies were included. Most patients were female (55.6%), with a mean age of 48±13 years. Regarding the Montreal classification, 37 patients had ileal disease (45.7%) and 44 ileocolonic disease (54.3%); 9 patients had nonstricturing, nonpenetrating disease (11.1%), 35 stricturing (43.2%) and 37 penetrating disease (45.7%). Nineteen patients had perianal disease (23.5%). The mean time between the surgery and the endoscopic evaluation was 135±79 months. Post-operative endoscopic recurrence was observed in 52 ileocolonoscopies (43.0%). Symptomatic patients (HBI &amp;gt; 4 points) were 11 times more likely to have post-operative endoscopic recurrence (OR 10.686, 95%CI 2.930-38.974, p&amp;lt;0.001). Those with post-operative endoscopic recurrence had a significantly higher FC values (median 189 vs 69 µg/g, p&amp;lt;0.001) and higher ESR values (median 14 vs 9 mm, p=0.002). In fact, patients with FC values ≥ 150 µg/g and those with ESR values &amp;gt; 12 mm were 4 and 3 times more likely to have post-operative endoscopic recurrence (OR 3.654, 95%CI 1.605-8.316, p=0.002 and OR 3.059, 95%CI 1.397-6.696, p=0.005, respectively). The presence of post-operative endoscopic recurrence was not associated with CRP values (median 2.9 vs 2.9 mg/L, p=0.466), and neither with mean time between the surgery and the endoscopic evaluation (mean 126±83 vs 142±75 months, p=0.263). Conclusion The presence of symptoms (HBI &amp;gt; 4 points), FC values ≥ 150 µg/g and ESR values &amp;gt; 12 mm was associated with post-operative endoscopic recurrence in CD. Therefore, the HBI, FC and ESR values can be used to monitor CD patients after ileocolic resection, and prompt endoscopic evaluation should be performed in those with HBI &amp;gt; 4 points, FC values ≥ 150 µg/g and/or ESR values &amp;gt; 12 mm.

Smartphone-assisted colorimetry and array test strip integrated platform for urine multi-index simultaneous precise quantification and personalized healthcare monitoring

As a non-invasive monitoring method, urine analysis is one of the “three routines” of medical examination, which is of great significance for the early diagnosis, therapeutic effect judgment and long-term fine monitoring of chronic diseases such as metabolic system diseases and kidney diseases. It is imperative to develop a home urine routine detection system. In this paper, Smart Urine Analyzer is innovatively developed by combining smartphones with array urine dipsticks, and equipped with the unique design of adjustable bracket suitable for camera position of different smartphones. The optimal colorimetric value was selected for analysis based on chromogenic response characteristics combined with digital image colorimetry, and the breakthrough from qualitative semi-quantification to precise quantification of 9 kinds of urine biomarkers was completed. And a smartphone App for automated image recognition and processing was developed, which was applied for at-home routine healthcare. 100 clinical urine samples were used to evaluate the reliability of the system. Among them, the ROC curve showed a high consistency between Smart Urine Analyzer and the Dirui H-800 urine analyzer in hospital, which further verified the practicability. As a result, the user-friendly Smart Urine Analyzer can share health data and condition with doctors in real time, which provides a new scheme and means for the home detection of urine biomarkers, and has great practical application value as a potential home medical service assistant.

Investigating the Effect of Syringe Infiltration on Nicotiana tabacum (Tobacco).

Plant infiltration techniques, particularly agroinfiltration, have transformed plant science and biotechnology by enabling transient gene expression for genetic engineering of plants or genomic studies. Recently, the use of infiltration has expanded to introduce nanomaterials and polymers in plants to enable nonnative functionalities. Despite its wide use, the impact of the infiltration process per se on plant physiology needs to be better understood. This study investigates the effect of syringe infiltration, a commonly employed technique in plants, using a typical infiltration buffer solution. Noninvasive and real-time monitoring methods, including high-resolution thermal imaging and a porometer/fluorometer, were used to study the physiological responses and stress levels of the infiltrated plants. Our results revealed localized cell damage at the infiltration site due to syringe compression, but the overall cell viability and tissue integrity were largely unaffected. Thermography showed a temporary temperature increase of the leaves and stomatal conductance alterations postinfiltration, with leaf recovery in 3-6 days. Additionally, fluorescence measurements indicated a 6% decrease in maximum quantum efficiency (F v/F m) and a 34% decrease in photosystem II (ΦPSII) quantum yield, persisting for 5 days after infiltration, suggesting sustained photosystem efficiency changes. Our work highlights the need to consider the effect of infiltration when performing biological studies and aims to facilitate the optimization of protocols commonly used in plant science and biotechnology.

Non-invasive in-situ monitoring of deep etching processes using terahertz metasurfaces

This study presents an in-situ and non-invasive process control and monitoring (PCM) method for deep silicon etching, leveraging terahertz metasurfaces. The technique addresses the challenges for monitoring deep and high aspect ratio etching processes, which are prevalent in semiconductor microfabrication. By incorporating metasurfaces with identical geometric shapes and sizes as crucial components of targeted devices, the method enables accurate monitoring of the etching depth in the process. Continuous shifts of terahertz reflection spectra provide information on etching depth, while abrupt change in the curves highlights the etching endpoint, preventing over-etching. For the commonly used comb-finger structure, numerical simulations demonstrate a strong linear relationship between etching depth and terahertz resonant wavelengths (nonlinearity &lt; 1%) and an abrupt resonant frequency change (&gt; 0.6 THz) at the endpoint. Experimental validations confirm the accuracy of the PCM method, with an etching depth estimation error below 2 µm. This approach enhances the precision of PCM in microfabrication, offering the potential for widespread applications in the production of micromechanical sensors, actuators, and other microelectronic devices.

EFFECT OF ELECTRODE BELT USED FOR LUNG MONITORING WITH ELECTRICAL IMPEDANCE TOMOGRAPHY ON TIDAL VOLUME IN HEALTHY SUBJECTS

Electrical impedance tomography is a radiation free, non-invasive lung monitoring method that is increasingly coming to the forefront of the interest of researchers and clinicians. The most frequently used EIT system PulmoVista 500 (Dräger Medical, Germany) uses stiff silicone electrode belt that is applied around the patient’s thorax to monitor the distribution of ventilation. To achieve proper electrode-skin connection and obtain high-quality signal, the electrode belt needs to be placed tightly at the level of 4th to 6th intercostal space. There is a possibility that tightly placed belt affects the compliance of the chest wall, tidal volume, and respiratory effort of the patient. In this study, we monitored tidal volumes using spirometer in 10 healthy, spontaneously breathing volunteers with and without the electrode belt applied around the thorax. Potentially clinically significant, but not statistically significant changes occurred in 70% of the subjects during calm breathing and in 90% of the subjects during forced breathing. The study did not determine whether the use of the electrode belt increases or decreases the value of tidal volume. However, when monitoring lung ventilation with EIT system, the possible influence of the stiff electrode belt on chest wall compliance and tidal volumes should be considered.

Hyperspectral Imaging for Detecting Plastic Debris on Shoreline Sands to Support Recycling

Environmental pollution from plastic debris is raising concerns not only for the vulnerability of marine species to ingestion but also for potential human health hazards posed by small particles, known as microplastics. In this context, marine areas suffer from a lack of constant shoreline cleanups to remove accumulated debris, preventing their degradation and fragmentation. To establish optimal strategies for streamlining plastic recovery and recycling operations, it is important to have a system for recognizing plastic debris on the beach and, more specifically, for identifying the type of polymer and mapping (e.g., topologically assessing) the distribution of plastic debris on shoreline sands. This study aims to provide an operative tool finalized to perform an in situ detection, analysis, and characterization of plastic debris present in the coastal environment (i.e., beaches), adopting a near-infrared (NIR)-based hyperspectral imaging (HSI) approach. In more detail, the possibility of identifying and classifying polymers of plastic debris by NIR-HSI in three different areas along the Pontine coastline of the Lazio region (Latina, Italy) was investigated. The study focused on three distinct beaches (i.e., Foce Verde, Capo Portiere, and Sabaudia), each characterized by a different type of sand. For each location, the adopted approach allowed for the systematic classification of the various types of plastic waste found. Three Partial Least Squares Discriminant Analysis (PLS-DA) classification models were developed using a cascade detection strategy. The first model was designed to distinguish plastics from other materials in sand samples, the second to detect plastic particles in the sand, and the third to classify the type of polymer composing each identified plastic particle. Obtained results showed that, on the one hand, plastics were correctly detected from sand and other materials (i.e., sensitivity = 0.892–1.000 and specificity = 0.909–0.996), and on the other, the recognition of polymer type was satisfactory, according to the performance statistical parameters (i.e., sensitivity = 1.000 and specificity = 0.991–1.000). This research highlights the potential of the NIR-HSI approach as a reliable, non-invasive method for plastic debris monitoring and polymer classification. Its scalability and adaptability suggest possible future integration into mobile systems, enabling large-scale monitoring and efficient debris management.

Exploring pulse transit time as a potential indicator of blood pressure: a scientific inquiry

Non-invasive continuous blood pressure (BP) monitoring is crucial, especially in critical care settings. While pulse transit time (PTT) has been used for cuffless BP monitoring, it requires accurate detection of pulse waves at arterial sites, which can be uncomfortable for patients. Pulse arrival time (PAT), the interval between the ECG Q-wave and pulse arrival at a distant site, offers a potentially less invasive approach for BP estimation. However, the reliability of PAT as a BP indicator remains uncertain. This study aimed to evaluate the feasibility of using PAT as a continuous, non-invasive BP monitoring method. Data from 37 subjects, including PAT and BP measurements, were analyzed. Statistical analysis revealed a weak correlation (r = 0.17) between PAT and BP, suggesting that PAT may not be a reliable standalone method for BP measurement. These findings indicate that further research is necessary to address the limitations of PAT and explore its potential as a supplementary tool for BP monitoring in clinical settings.

Comparison Between Continuous Non-invasive Arterial Pressure (CNAP) and Invasive Arterial Pressure Monitoring During Weaning from CPB in Patients Undergoing CABG Surgery: A Comparative Case Study

Background: Accurate and continuous measurement of arterial blood pressure is crucial in managing patients undergoing cardiac surgery to prevent complications and ensure better outcomes. Objectives: This study aimed to compare blood pressure monitoring using continuous non-invasive arterial pressure (CNAP) and invasive arterial pressure (IAP) methods after weaning from cardiopulmonary bypass (CPB). Methods: Blood pressure monitoring was conducted on 30 patients referred to Dr. Masih Daneshvari Hospital in Tehran for coronary artery bypass grafting (CABG) surgery. Measurements were taken every two minutes for 30 minutes after separation from CPB using both non-invasive CNAP and invasive IAP methods simultaneously. Data on systolic, diastolic, and mean arterial blood pressure (MAP) were collected and analyzed using SPSS statistical software. Results: The findings revealed no significant difference between the CNAP and IAP methods in monitoring MAP (P &gt; 0.05). However, systolic blood pressure (SBP) measured by the IAP method was significantly higher than that measured by the CNAP method starting 10 minutes after weaning from CPB (P &lt; 0.05). Conversely, diastolic blood pressure measured by the CNAP method was significantly higher than the IAP method at 2, 8, 10, 18, 20, and 22 minutes after CPB separation (P &lt; 0.05). Conclusions: Continuous non-invasive arterial pressure is a non-invasive and continuous blood pressure monitoring method that can be considered an alternative to the IAP method for measuring MAP in CABG surgery patients during weaning from CPB.

Comparison of Plasma Metagenomic Next-generation Sequencing and PCR Methods for Epstein-Barr Virus Viral Load Monitoring in Nasopharyngeal Carcinoma.

Plasma Epstein-Barr virus (EBV) viral load measurement is prognostic in nasopharyngeal carcinoma (NPC) disease monitoring; however, a consensus measurement approach does not exist. This study characterized the clinical performance of metagenomic next-generation sequencing (mNGS), an unbiased sequencing-based assay distinct from polymerase chain reaction (PCR) or targeted sequencing approaches, in 73 peripheral blood specimens from 32 patients diagnosed with NPC. Samples were analyzed for plasma EBV viral load either by mNGS profiling or PCR-based assays (either LMP2 or BAMHI-W PCR) and compared to tumor presence by clinical assessment. Plasma mNGS-based EBV detection was quantified as reads per million (RPM). Plasma mNGS displayed similar overall performance (100% sensitivity, 86% specificity, 92% accuracy) to BAMHI-W PCR (100% sensitivity, 86% specificity, 94% accuracy) and superior performance to the LMP2 PCR assay (36% sensitivity, 56% specificity, 45% accuracy). In a subset of 13 patients who underwent longitudinal analysis, plasma mNGS EBV RPM correlated with cancer recurrence (95%CI Pre-CRT=232.10±214; 95%CI Post-CRT=0.34±0.32; 95%CI difference=-231.70±214; *p=0.03, paired t-test), suggesting plasma mNGS exhibits potential for monitoring recurrence. Plasma mNGS is a distinct method for EBV titer measurement in NPC patients and more broadly, is a promising method for non-invasive monitoring of disease status for infection-associated malignancies.

Near-infrared diffuse optical characterization of human thyroid using ultrasound-guided hybrid time-domain and diffuse correlation spectroscopies.

Thyroid vascularization and hemodynamics become altered in thyroid pathologies and could thus inform diagnostics, therapy planning, and follow-up. However, the current non-invasive monitoring methods available in clinics lack the necessary sensitivity and/or are impractical for large-scale deployment. As a step towards proposing a new modality, we applied the first platform, to our knowledge, designed to do simultaneous measurements of neck anatomy and thyroid microvascular hemodynamics and metabolism in a single probe placement, integrating state-of-the-art near-infrared spectroscopy techniques and clinical ultrasound. A rich dataset was formed with sixty-five subjects (forty-eight females), including eighteen healthy volunteers and forty-seven patients with thyroid nodules, characterizing thyroid tissue and the effects of demographic and anatomical variables while preserving the standard clinical workflow. We have found marked reductions with age and body mass index in thyroid total hemoglobin concentration (THC), tissue oxygen saturation (StO 2), and blood flow index (BFi), among others. Patients showed lower THC and BFi than healthy subjects, and the limited sample of malignant nodules showed a higher StO 2 than the benign. These findings support the need for personalized clinical approaches.

The Liquid Biopsy: A Detailed Review of Evolution, Technologies and Clinical Implications

Liquid biopsy has transformed molecular diagnostics by providing a non-invasive method for disease identification and monitoring, notably in cancer. This study examines the history of liquid biopsy, with an emphasis on the critical role of circulating tumor DNA (ctDNA) and the move from targeted to genome-wide analysis. It emphasizes the value of liquid biopsy in non-invasive diagnosis, patient comfort, real-time monitoring, and individualized treatment solutions. Success stories in early cancer identification across several cancer types highlight the efficiency of liquid biopsy in detecting particular genetic alterations associated with early-stage illness. The paper also examines the use of liquid biopsy for tracking treatment response and finding minimum residual disease, underlining its potential to revolutionize therapy assessment and post-treatment care. However, consistency issues, such as heterogeneity in sample collection, storage, and processing, as well as variations among cancer types, represent substantial barriers to the widespread use of liquid biopsy. Efforts to solve these problems through collaborative projects and standardization ideas are presented, with a focus on data sharing and the advancement of innovative liquid biopsy technologies. Overall, this review gives a thorough overview of liquid biopsy achievements and limitations, emphasizing its promise as a foundation for current diagnostic techniques.

Non-Invasive Monitoring of Cerebral Edema Using Ultrasonic Echo Signal Features and Machine Learning.

Cerebral edema, a prevalent consequence of brain injury, is associated with significant mortality and disability. Timely diagnosis and monitoring are crucial for patient prognosis. There is a pressing clinical demand for a real-time, non-invasive cerebral edema monitoring method. Ultrasound methods are prime candidates for such investigations due to their non-invasive nature. Acute cerebral edema was introduced in rats by permanently occluding the left middle cerebral artery (MCA). Ultrasonic echo signals were collected at nine time points over a 24 h period to extract features from both the time and frequency domains. Concurrently, histomorphological changes were examined. We utilized support vector machine (SVM), logistic regression (LogR), decision tree (DT), and random forest (RF) algorithms for classifying cerebral edema types, and SVM, RF, linear regression (LR), and feedforward neural network (FNNs) for predicting the cerebral infarction volume ratio. The integration of 16 ultrasonic features associated with cerebral edema development with the RF model enabled effective classification of cerebral edema types, with a high accuracy rate of 97.9%. Additionally, it provided an accurate prediction of the cerebral infarction volume ratio, with an R2 value of 0.8814. Our proposed strategy classifies cerebral edema and predicts the cerebral infarction volume ratio with satisfactory precision. The fusion of ultrasound echo features with machine learning presents a promising non-invasive approach for the monitoring of cerebral edema.

A Technique for Monitoring Mechanically Ventilated Patient Lung Conditions.

Mechanical ventilation is a critical but resource-intensive treatment. Automated tools are common in screening diagnostics, whereas real-time, continuous trend analysis in mechanical ventilation remains rare. Current techniques for monitoring lung conditions are often invasive, lack accuracy, and fail to isolate respiratory resistance-making them impractical for continuous monitoring and diagnosis. To address this challenge, we propose an automated, non-invasive condition monitoring method to support pulmonologists. Our method leverages ventilation waveform time-series data in controlled modes to monitor lung conditions automatically and non-invasively on a breath-by-breath basis while accurately isolating respiratory resistance. Using statistical classification and regression models, the approach achieves 99.1% accuracy for ventilation mode classification, 97.5% accuracy for feature extraction, and 99.0% for predicting mechanical lung parameters. The models are both computationally efficient (720 K predictions per second per core) and lightweight (24.5 MB). By storing breath-by-breath predictions, pulmonologists can access a high-resolution trend of lung conditions, gaining clear insights into sudden changes without speculation and streamlining diagnosis and decision-making. The deployment of this solution could expand domain knowledge, enhance the understanding of patient conditions, and enable real-time dashboards for parallel monitoring, helping to prioritize patients and optimize resource use, which is especially valuable during pandemics.

Robust Anticorrosive Polymer Thin Film for Reliable Protection of Ingestible Devices.

Ingestible devices (ID) provide a safe and noninvasive method for monitoring, diagnosing, and delivering drugs to specific sites in the human body, particularly within the gastrointestinal (GI) tract. However, the GI environment is highly acidic and humid, which can cause IDs to fail, and their corrosion in the acidic environment can cause leaching of toxic metal ions, thereby substantially limiting their long-term use. Thus, an efficient method is required to protect IDs, especially in the chemically and mechanically harsh GI environment. However, an anticorrosive polymer coating that can safeguard IDs in the GI environment without delamination or performance degradation has not been developed to date. The protective layer must satisfy several critical requirements, e.g., high biocompatibility, mechanical durability, and superior anticorrosion performance. This paper reports a highly cross-linked but submicron-thick siloxane-based anticorrosive polymer thin film that can be deposited directly onto IDs without damaging them. The 500 nm-thick cross-linked polymer coating demonstrates exceptional corrosion resistance and chemical and mechanical stability in the GI environment without cytotoxicity. A printed circuit board (PCB) coated with the developed ultrathin protective film sustained performance after exposure to a pH 1.00 phosphate buffered saline solution at 37 °C for 72 h without leaching of metal ions. The ID continued to operate effectively under such challenging conditions; thus, the developed film is suitable for applications that require prolonged functionality, e.g., diagnostics, drug delivery, and continuous health monitoring in the GI tract.

Аналіз оптичних методів для визначення цукру в крові

The article discusses promising optical methods for non-invasive blood glucose monitoring, in particular, optical coherence tomography (OCT), near-infrared (NIR), Raman spectroscopy, terahertz spectroscopy (THz), fluorescence spectroscopy, polarimetry, and oxyhemoglobin spectroscopy. The principles of each method, their advantages and limitations are described. Modern technological advances aimed at improving the accuracy, efficiency and convenience of these methods for clinical use, especially in the context of monitoring patients with diabetes, are considered.

On-machine evaluation of micro-EDM process signature in radio frequency (RF) domain: A step towards cost-effective data collection in a multiphysical process

In the growing age of digitization, there is a need for cost-effective data collection techniques to enable manufacturing data collection of production processes in small and medium scale enterprises (SMEs). This goes further where electrophysical processes, such as micro electrical discharge machining (micro-EDM) are employed in high-end micro-components such as fuel injection nozzles and precision components for automotive and aerospace sectors. There have been several efforts to get process information using electrical and acoustic monitoring, AI-based and multiphysics models, and fundamental physics experiments. All aforementioned techniques have contributed to improving understanding of the discharge behaviour in micro-EDM processes. However, they are all expensive and invasive in nature, thereby limiting their application for SMEs in enabling digitalisation of process-chain involving micro-EDM process.To address this gap, this paper investigates micro-EDM process signature in radio frequency (RF) domain and hence RF-based strategy is proposed as a low-cost and non-invasive process monitoring technique. Research is conducted to investigate the radiation sources and potential influencing factors during the EDM process. First, the RF mechanism in EDM is examined by analysing the monitored RF signals across different discharge stages of various pulse waveforms. From this analysis, the corresponding equivalent RF radiation models are established. Second, through an experimental design, the impact of different machining parameters, dielectric fluids, discharge states, monitoring equipment, and workpiece materials on RF signals are explored in both the time and frequency domains. The results indicate that only parameters related to breakdown voltage and gap current affect RF intensity, however, machining parameters show to be not significant on the radiation spectrum. The influence of dielectrics and workpiece materials on radiation behaviour is primarily associated with their corresponding equivalent resistance. Notable differences in both discharge pulses and antenna devices in monitoring RF signals are observed. Additionally, the monitorability of RF strategy is also evaluated under two application scenarios. By investigating the RF signals in EDM, it is expected to provide a non-invasive, interference-free, and low-cost method for discharge state monitoring.