Non-invasive Monitoring Method Research Articles

Application of optical analysis methods for non-invasive monitoring of blood oxygen saturation level

An intelligent optical system for medical express diagnostics has been developed and tested. A method for visualizing the oxygen status of biological tissues in the form of "digital images" describing the general functional state of the human body is demonstrated. It has been shown that the method of principal components and hierarchical clustering can be used in combination with optical methods for detecting hemoglobin forms in biological tissues to perform non-invasive monitoring and express diagnostics of the oxygen status of the human body. The results obtained show that it is possible to stratify the subjects into risk groups based on optical sensor readings. In comparison with pulse oximetry, the use of which is common for determining the oxygen saturation level of blood, the described method can be employed to estimate peripheral oxygen saturation, and thus thrombosis and ischemia of the extremities can be detected in time.

A non-invasive method of glucose monitoring using FR4 material based microwave antenna sensor

Abstract This work presents a unique non-invasive method for monitoring glucose levels in blood using a planar Yagi–Uda antenna as a microwave sensor. The proposed antenna, operating at 5.5 GHz, exhibits a directional radiation pattern with a peak gain of 6.74 dBi. A low-cost FR4 material of size 30 mm × 40 mm × 1.6 mm is used as a dielectric substrate. A human finger phantom, comprising layers of skin, fat, blood, and bone, is created at 5.5 GHz in EM simulation tool for mimicking a real human finger. The finger phantom is positioned at different locations around the antenna and corresponding frequency shifts are remarked to a variation in glucose concentration from 0–500 mg/dL. An exemplary frequency shift of maximum 26 MHz is recorded when the phantom is placed at the bottom of the antenna. Time domain analysis is also carried out to understand the effect of glucose concentration variation on the output signal amplitude and delay. Simulated antenna results are found to be in stupendous agreement with the measured results. An experiment of placing a real human finger around the fabricated antenna also presents a splendid correspondence with the simulated results. Hence, this mechanism can be expedient for monitoring glucose levels in blood.

330 Remote Monitoring of Pediatric Heart Failure: A Systematic Review

OBJECTIVES/GOALS: Pediatric heart failure is a complex disease presenting as an end-stage condition due to various etiologies and symptoms, causing 14,000 hospitalizations per year in the United States. Currently, there is a lack of objective metrics that are monitored non-invasively. This study explores tools to adapt remote monitoring technologies for pediatrics. METHODS/STUDY POPULATION: The task was determining commercially available and upcoming technologies for remote heart failure monitoring in the pediatric population. Literature and patent reviews were done in various databases with defined eligibility and key terms. Our inclusion criteria were: English peer-reviewed research or review articles, patents filed by cardiac monitoring companies, and independent groups focusing on non-invasive monitoring solutions. Key terms used for the literature search and patent review included pediatric heart failure’, at-home monitoring’, cardiac monitoring’, and non-invasive’. Based on a strong correlation between increased filling pressures and pediatric heart failure, the term filling pressures’ was also included in the search. RESULTS/ANTICIPATED RESULTS: Preliminary searches demonstrate an abundance of adult-use commercially available devices and patents for monitoring heart failure. Yet, there are no FDA-approved devices for use in the pediatric population. Current devices include monitoring metrics such as lung congestion and multi-parametric monitoring to capture heart rate, thoracic impedance, and oxygen saturation levels. In monitoring filling pressures, Abbott CardioMEMs is a leader in measuring pulmonary arterial pressure invasively in adults. Thus, there is a gap for non-invasive monitoring of filling pressures in both pediatric and adult populations. For further review, a larger focus will be placed on non-invasive methods for direct monitoring or extrapolation of cardiac filling pressures. DISCUSSION/SIGNIFICANCE: Current methods of heart failure monitoring are ineffective in serving the pediatric population. Thus, an identified gap exists in non-invasive filling pressure monitoring for pediatric heart failure. This review informs that innovation within this area would address inefficacies within the current paradigm of heart failure monitoring.

Non Intrusive Power Load Monitoring Method Based on Machine Learning

In order to improve the accuracy of non-invasive power load monitoring and shorten the monitoring time, a new non-invasive power load monitoring method based on machine learning is proposed. Firstly, the power load data is collected by sensors and normalized. Secondly, based on the normalized results of power load data, the RBF neural network model in machine learning is used for iterative training to extract power load characteristics. Finally, according to the characteristics of power load, the hidden Markov model is used to transform the non-invasive power load monitoring problem into a decoding problem, and the improved Viterbi algorithm is used to solve the hidden Markov model, and the non-invasive power load monitoring is completed according to the obtained state sequence.

Application of Optical Analysis Methods for Noninvasive Monitoring of the Blood Oxygen Saturation Level

Application of Optical Analysis Methods for Noninvasive Monitoring of the Blood Oxygen Saturation Level

Emerging Technologies of Three-Dimensional Printing and Mobile Health in COVID-19 Immunity and Regenerative Dentistry.

The ongoing coronavirus disease 2019 (COVID-19) pandemic highlights the importance of developing point-of-care (POC) antibody tests for monitoring the COVID-19 immune response upon viral infection or following vaccination, which requires three key aspects to achieve optimal monitoring, including three-dimensional (3D)-printed POC devices, mobile health (mHealth), and noninvasive sampling. As a critical tissue engineering concept, additive manufacturing (AM, also known as 3D printing) enables accurate control over the dimensional and architectural features of the devices. mHealth refers to the use of portable digital devices, such as smartphones, tablet computers, and fitness and medical wearables, to support health, which facilitates contact tracing, and telehealth consultations during the pandemic. Compared with invasive biosample (blood), saliva is of great importance in the spread and surveillance of COVID-19 as a noninvasive diagnostic method for virus detection and immune status monitoring. However, investigations into 3D-printed POC antibody test and mHealth using noninvasive saliva are relatively limited. Further exploration of 3D-printed antibody POC tests and mHealth applications to monitor antibody production for either disease onset or immune response following vaccination is warranted. This review briefly describes the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and immune response after infection and vaccination, then discusses current widely used binding antibody tests using blood samples and enzyme-linked immunosorbent assays on two-dimensional microplates before focusing upon emerging POC technological platforms, such as field-effect transistor biosensors, lateral flow assay, microfluidics, and AM for fabricating immunoassays, and the possibility of their combination with mHealth. This review proposes that noninvasive biofluid sampling combined with 3D POC antibody tests and mHealth technologies is a promising and novel approach for POC detection and surveillance of SARS-CoV-2 immune response. Furthermore, as key concepts in dentistry, the application of 3D printing and mHealth was also included to facilitate the appreciation of cutting edge techniques in regenerative dentistry. This review highlights the potential of 3D printing and mHealth in both COVID-19 immunity monitoring and regenerative dentistry.

Assessing the potential use of environmental DNA for multifaceted genetic monitoring of cetaceans: Example of a wandering whale in a highly disturbed bay area

Environmental DNA (eDNA) sampling of water is a powerful method for comprehensive and noninvasive monitoring of aquatic animal species. However, there have been few reports of its application to cetacean species. On June 29, 2021, a whale (nicknamed Xiaobu) appeared in Dapeng Bay off Guangdong Province, China. We used eDNA technology to obtain information related to this whale (e.g., species identification and food resources) and to trace its possible origin. Fragments of four whale mitochondrial sequences (12S rDNA, 16S rDNA, cytochrome c oxidase subunit 1, and control region) were obtained from amplicons of eDNA collected in Dapeng Bay; sequence barcoding showed that this was an Eden’s whale (Balaenoptera edeni edeni Anderson 1879). Analysis of potential prey species (PPS) suggested that this whale might enter Dapeng Bay while tracking prey, mainly sardines (Sardinella lemuru, Sardinella gibbosa and Sardinella jussieui) and anchovies (Thryssa dussumieri, Thryssa vitrirostris and Thryssa kammalensis). Retrieval of eDNA metabarcoding data from samples collected in waters adjacent to Dapeng Bay (i.e. Lingding Bay and Daya Bay) revealed that Eden’s whale had appeared outside Lingding Bay up to 2 months prior to the appearance of this whale in Dapeng Bay (early April 2021). Overall, this study showed that eDNA is a highly effective noninvasive survey method for the accurate identification of target cetacean species and prey composition; it can be used to monitor megafauna that are under strict legal protection or to monitor megafauna with unknown conditions.

Hollow village detection method based on non-intrusive power load monitoring

With the development of urbanization, the population and resources converge to the city, leading to different degrees of hollow village phenomenon in rural areas. Therefore, a hollow village detection model based on non-invasive load monitoring method is proposed in this paper. Firstly, the power load data of users is collected in rural areas, and the data is processed and analyzed. A data analysis algorithm based on the improved Attention mechanism is constructed, and the existing public data sets are used for verification and improvement. Six kinds of frequently used electrical appliances among rural users were selected as typical electrical appliances, the power load curves of selected typical electrical appliances were obtained, and the long and short term memory network algorithm was used to identify the types of household electrical appliances of rural users. After algorithm recognition and analysis, the usage characteristics of typical rural electric appliances are obtained, and it is taken as the electricity consumption behavior habits of rural residents. According to their electricity consumption habits, rural residents are divided into four categories: young people living alone, the elderly, two adults and a child, and vacant houses. According to the four groups of people, the index of hollow village is determined. By judging the corresponding household population of four groups of rural residents, the selected village is judged whether it is hollow village or whether there is a tendency of hollow village.

Design and performance evaluation of a slit-slat camera for 2D prompt gamma imaging in proton therapy monitoring: A Monte Carlo simulation study.

We investigated the design of a prompt gamma camera for real-time dose delivery verification and the partial mitigation of range uncertainties. A slit slat (SS) camera was optimized using the trade-off between the signal-to-noise ratio and spatial resolution. Then, using the GATE Monte Carlo package, the camera performances were estimated by means of target shifts, beam position quantification, changing the camera distance from the beam, and air cavity inserting. A homogeneous PMMA phantom and the air gaps induced PMMA phantom were used. The air gaps ranged from 5mm to 30mm by 5mm increments were positioned in the middle of the beam range. To reduce the simulation time, phase space scoring was used. The batch method with five realizations was used for stochastic error calculations. The system's detection efficiency was PGs/proton) for a 10 × 20 cm2 detector (source-to-collimator distance=15.0cm). Axial and transaxial resolutions were 23mm and 18mm, respectively. The SS camera estimated the range as 69.0±3.4 (relative stochastic error 1-sigma is 5%) and 67.6±1.8mm (2.6%) for the real range of 67.0mm for 107 and 108 protons of 100 MeV, respectively. Considering 160 MeV, these values are 155.5±3.1 (2%) and 152.2±2.0mm (1.3%) for the real range of 152.0mm for 107 and 108 protons, respectively. Considering phantom shift, for a 100 MeV beam, the precision of the quantification (1-sigma) in the axial and lateral phantom shift estimation is 2.6mm and 1mm, respectively. Accordingly, the axial and lateral quantification precisions were 1.3mm and 1mm for a 160 MeV beam, respectively. Furthermore, the quantification of an air gap formulated as , where and gapreal are the estimated and real air gap, respectively. The precision of the air gap quantification is 1.6mm (1 sigma). Moreover, 2D PG images show the trajectory of the proton beam through the phantom. The proposed slit-slat imaging systems can potentially provide a real-time, in-vivo, and non-invasive treatment monitoring method for proton therapy.

Gas-permeable and stretchable on-skin electronics based on a gradient porous elastomer and self-assembled silver nanowires

On-skin electronics offers a noninvasive method for continuous and stable signal monitoring, which has played a significant role in healthcare and rehabilitation engineering. However, most present on-skin electronicses are highly restricted by their gas permeability and stretchability due to the materials, fabrication process, and cost. This study develops gas-permeable and stretchable on-skin electronics fabricated via a gradient porous elastomer and self-assembled silver nanowires. The introduction of a gradient porous structure offers the elastomer substrate a good water vapor permeability of 3073.3 g day−1 m−2, which is much higher than the average evaporation rate of water vapor on human skin (432 g day−1m−2). Additionally, the examined electronic device has no adverse effects on the skin and possesses good stretchability and flexibility (110%, 0.07778 MPa). In addition, it offers excellent fatigue resistance (0.70% electrical resistance change within 1000 stretch cycles). The electronic device achieves conformal and comfortable contact with human skin for a long period of wearing and accomplishes high-quality biopotential measurement with a high signal-to-noise ratio (SNR) during electromyography (EMG) signal detection. The proposed simple fabrication process may supply inspiration for new on-skin electronics used in biological signal detection and rehabilitation engineering.

An Online Non-Invasive Condition Assessment Method of Outdoor High-Voltage SF6 Circuit Breaker

Online monitoring of outdoor high voltage SF6 circuit breakers (HVCBs) is essential to detecting potential damages. To this end, the study of accurate and non-invasive monitoring methods has been significantly investigated in recent decades. Considering that HVCB vibration patterns carry important information about mechanical and electrical integrity and that vibration analysis requires a low level of invasiveness, this article presents methods of obtaining mechanism and reaction times using interference signals of outdoor high voltage SF6 circuit breakers (HVCBs). Compared to traditional methods of monitoring outdoor SF6 circuit breakers that are based on encoders, the proposed method presented ease of installation, as it only requires the insertion of accelerometers. The method of obtaining the mechanism time is based on the use of interference and auxiliary contact signals, in the time domain, where the accelerometer is installed, in the structure of the HVCB, makes it possible to guarantee the moment of the trip command. To obtain the reaction time of each HVCB pole, the envelope technique was applied with the Hilbert transform module of the hearing signal, filtered in a certain resonance band. The proof of the technique of analyzing the vibration of the signal in time was developed with laboratory tests of an HVCB, instrumented with accelerometers and angular encoders. The results obtained via vibration analysis were compared with those obtained via angular encoders and it was concluded that with the acceleration signals, in time, it is possible to obtain performance parameters of an HVCB from its displacement curve. Finally, the online monitoring of the circuit breaker applied in the field is presented, where the acquisition of trip current signals, the condition of the SF6 gas and extinguishing current signals were added to the instrumentation.

Extracorporeal Circulation and Optic Nerve Ultrasound: A Pilot Study.

Background and Objectives: Cardiopulmonary bypass (CPB) is an extracorporeal circuit that provides surgical access to an immobile and bloodless area, allowing for technical and procedural advances in cardiothoracic surgery. CBP can alter the integrity of the blood-brain barrier and cause changes in intracranial pressure (ICP) postoperatively. Optical nerve sheath diameter (ONSD) measurement is among the alternative non-invasive methods for ICP monitoring. In this study, we aimed to evaluate the optic nerve sheath diameter measurements under the guidance of ultrasonography for ICP changes during the extracorporeal circulation process. Materials and Methods: The study population included 21 patients over 18 years of age who required extracorporeal circulation. Demographic data of the patients, such as age, gender, comorbidity, American Society of Anesthesiologists (ASA) classification and reason for operation (coronary artery disease or mitral or aortic valve disease) were recorded. The ONSD was measured and evaluated before the extracorporeal circulation (first time) and at the 30th minute (second time), 60th minute (third time) and 90th minute (fourth time) of the extracorporeal circulation. Non-invasive ICP (ICP ONSD) values were calculated based on the ONSD values found. Results: The mean ONSD values measured before the extracorporeal circulation of the patients were found to be 4.13 mm (3.8-4.6) for the right eye and 4.36 mm (4.1-4.7) for the left eye. Calculated nICPONSD values of 11.0 mm Hg (1.0-21.0) for the right eye and 10.89 mm Hg (1.0-21.0) for the left eye were found. It was observed that there was a significant increase in the ONSD and nlCPONSD values recorded during the extracorporeal circulation of all patients compared to the baseline values (p < 0.005). Conclusions: During extracorporeal circulation, ultrasound-guided ONSD measurement is an easy, inexpensive and low-complication method that can be performed at the bedside during the operation to monitor ICP changes.

Non-invasive method for blood glucose monitoring using ECG signal

Abstract Introduction: Tight glucose monitoring is crucial for diabetic patients by using a Continuous Glucose Monitor (CGM). The existing CGMs measure the Blood Glucose Concentration (BGC) from the interstitial fluid. These technologies are quite expensive, and most of them are invasive. Previous studies have demonstrated that hypoglycemia and hyperglycemia episodes affect the electrophysiology of the heart. However, they did not determine a cohort relationship between BGC and ECG parameters. Material and method: In this work, we propose a new method for determining the BGC using surface ECG signals. Recurrent Convolutional Neural Networks (RCNN) were applied to segment the ECG signals. Then, the extracted features were employed to determine the BGC using two mathematical equations. This method has been tested on 04 patients over multiple days from the D1namo dataset, using surface ECG signals instead of intracardiac signal. Results: We were able to segment the ECG signals with an accuracy of 94% using the RCNN algorithm. According to the results, the proposed method was able to estimate the BGC with a Mean Absolute Error (MAE) of 0.0539, and a Mean Squared Error (MSE) of 0.1604. In addition, the linear relationship between BGC and ECG features has been confirmed in this paper. Conclusion: In this paper, we propose the potential use of ECG features to determine the BGC. Additionally, we confirmed the linear relationship between BGC and ECG features. That fact will open new perspectives for further research, namely physiological models. Furthermore, the findings point to the possible application of ECG wearable devices for non-invasive continuous blood glucose monitoring via machine learning.

Early prediction of bronchopulmonary dysplasia: can noninvasive monitoring methods be essential?

Despite remarkable breakthroughs in diagnosis and treatment, the prevalence of bronchopulmonary dysplasia (BPD) in preterm infants and the consequent mortality have remained high over the last half-century. The pathophysiology of BPD is complicated, with several causes. In addition, infants with severe BPD are predisposed to a variety of complications that need multidisciplinary collaboration during hospitalisation and post-discharge home treatment. Consequently, early prediction, precise prevention and individualised management have become the cornerstones of therapeutic care of preterm infants with BPD, thereby improving patient survival and prognosis. BPD has an operational clinical description; however, it has various clinical phenotypes and endotypes, making accurate prediction challenging. Currently, most approaches for predicting BPD in preterm infants include invasive collection of biofluids, which is inappropriate in fragile neonates. Consequently, researchers and clinicians are becoming more interested in noninvasive monitoring for BPD prediction. Comprehensive assessments of pertinent research, however, remain scarce. In this review, we compared many noninvasive monitoring techniques that contribute to early prediction of BPD development in premature infants.

Hair Follicles as a Critical Model for Monitoring the Circadian Clock.

Clock (circadian) genes are heterogeneously expressed in hair follicles (HFs). The genes can be modulated by both the central circadian system and some extrinsic factors, such as light and thyroid hormones. These circadian genes participate in the regulation of several physiological processes of HFs, including hair growth and pigmentation. On the other hand, because peripheral circadian genes are synchronized with the central clock, HFs could provide a noninvasive and practical method for monitoring and evaluating multiple circadian-rhythm-related conditions and disorders among humans, including day and night shifts, sleep-wake disorders, physical activities, energy metabolism, and aging. However, due to the complexity of circadian biology, understanding how intrinsic oscillation operates using peripheral tissues only may be insufficient. Combining HF sampling with multidimensional assays such as detection of body temperature, blood samples, or certain validated questionnaires may be helpful in improving HF applications. Thus, HFs can serve as a critical model for monitoring the circadian clock and can help provide an understanding of the potential mechanisms of circadian-rhythm-related conditions; furthermore, chronotherapy could support personalized treatment scheduling based on the gene expression profile expressed in HFs.

The value of pulmonary artery acceleration time in evaluating pulmonary vascular disease in preterm infants with bronchopulmonary dysplasia.

Early screening and dynamic monitoring of pulmonary vascular disease (PVD) in bronchopulmonary dysplasia (BPD) high-risk infants is of great clinical significance. Pulmonary artery acceleration time (PAAT) is a reliable and non-invasive method for assessing PVD in children over 1 year, but to date, few studies have used PAAT to assess pulmonary hemodynamics of preterm infants, especially those with BPD. Through dynamic monitoring the main hemodynamic indicators reflected PVD after birth, this study aimed to assess the value of PAAT in evaluating early PVD in BPD infants. All 81 preterm infants at risk of BPD were divided into BPD and non-BPD groups according to whether BPD occurred. Clinical characteristics, PAAT, right ventricular ejection time (RVET) and other main hemodynamic indicators at four different time points after birth were studied and compared. PAAT and PAAT/RVET increased gradually within 72h after birth in the BPD group (p<.05), but the curve tended to be flat over time after 72h (p>.05). At PMA32 and 36weeks, the PAAT (49.7±4.8vs. 54.8±5.7, p=.001; 50.0±5.3vs. 57.0±5.3, p=.001) and PAAT/RVET (.33±.04vs..35±.03, p=.001; .34±.03vs. .37±.04, p=.001) in BPD group were significantly lower than those in the non-BPD group. PAAT and PAAT/RVET in the BPD group infants showed different change patterns compared to non-BPD group infants. PAAT can be used as a noninvasive and reliable screening method for screening and dynamic monitoring of PVD in BPD high-risk infants.

Enhancement of NH3 gas sensing with Ag-Pt co-catalyst on SnO2 nanofilm towards medical diagnosis

Exhaled breath analysis is a noninvasive diagnostic method for fatal disease monitoring and screening, which is recently gained extensive interest of researchers worldwide emphasizing on the development of effective chemiresistive gas sensor for practical application. Here, the Ag-Pt bimetallic nanoparticles were used to decorate nanofilms of SnO2 making different gas sensors with high performance. We found that the bimetal alloy improved the sensor performance significantly with super sensitivity as compared with the separate Ag and Pt catalyst. The right ratio of the bimetal made the sensor very sensitive to NH3, so that it was able to quickly (12 s) detect 1 parts-per-million of NH3 with a response of 4.31 at a temperature of 250 °C. The sensor limit of detection for NH3 was less than 10 parts-per-billion. The response of the sensor was negligibly affected by humidity and interfering gases. The results showed that the tiny, robust, and inexpensive sensor developed in this work can be used in breath analysis for early diagnosis via NH3 monitoring.

Admission Cardiotocography: Its Role in Predicting Perinatal Outcome in Term, Uncomplicated (Low Risk) Pregnant Women in Spontaneous Labour

Introduction: Labour admission cardiotocography (CTG) is commonly used non-invasive method of fetal monitoring in Sri Lanka. It may have a potentialto predict perinatal outcome in low-risk term pregnancies. Objectives: Objectives of the study were to determine the perinatal outcomes of normal, suspicious and pathological admission CTGs and role of labour admission cardiotocography as a predictive test for perinatal outcome in low-risk term pregnancies in spontaneous labour. Methods: This study was a prospective observational study done involving 445 low risk, term pregnancies in spontaneous labour. Labour admission CTG was performed in each pregnancy and categorized into normal, suspicious and pathological CTG according to criteria depicted by National Institute of Clinical Excellence (NICE) guideline 2007. Apgar score less than 7 at five minutes, resuscitation at birth, admission to neonatal intensive care unit (NICU), seizure within first 24 hours of birth and meconium-stained amniotic fluid were the primary outcome measures to assess fetal asphyxia. Mode of delivery in each category, nuchal cord at birth were also assessed. Results: Majority of participants were in 25-to-29-year age group and were nulliparous. Frequencies of normal, suspicious and pathological CTG were 74.8%, 18% and 7.2% respectively. Pathological CTG was significantly associated with low Apgar score compared to non-pathological CTG group (p 0.005) while other outcome measures were not significant. Rate of operative delivery was 68% in pathological group and 20.8% in non-pathological CTG group. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of labour admission CTG to detect fetal asphyxia were 51.85%, 95.69%, 43.75% and 96.85% respectively. Conclusions: Incidence of pathological labour admission CTG was 7.2%. Apgar score less than 7 at five minutes of birth was significantly associated with pathological CTG group compared to non-pathological CTG (p 0.05). Worsening of CTG from normal to pathological showed increasing rate of operative delivery. Even though sensitivity and positive predictive values of labour admission CTG were low, specificity and negative predictive values were high for detecting low Apgar score. Therefore, labour admission CTG has a value in excluding adverse perinatal outcomes in low-risk term pregnancies in spontaneous labour.

Biosensors and Sleep: The Future and Beyond

Biosensors have revolutionized nanotechnological development and are therefore the future ubiquitous devices for disease diagnosis monitoring treatment and health management. They provide a non-invasive method of continuous monitoring of various physiological signals like temperature heart rate blood pressure respiration rate and oxygen saturation and transmits that information to the patient and the physician. Thus their role in at-home detection of cases with obstructive sleep apnea OSA is significant which can easily replace the gold standard yet complex in-lab polysomnography PSG. The oral health care providers can be of great value to the team of sleep specialists when it comes to early detection and intervention with correct therapy for such patients. All the parameters that are studied in PSG can now be easily analyzed with the help of biosensors. However most of the sensing systems available today are extra-oral in nature and have no relation in anyway to the dental aspect of detection of OSA. Thus there is a vast space that is left unexplored in the world of biosensors when it comes to oral appliances which can be put into a pivotal role in diagnosing the undetected sleep apneic patients at a very early stage. This review paper presents an overview of the biosensors exploring their types functional modes and applications with particular emphasis on their potential application in diagnosing OSA.

Frequency-based leak signature investigation using acoustic sensors in urban water distribution networks

Cities worldwide have been plagued by water pipe leaks for many decades, resulting in financial losses, public health risks, and environmental impacts. Current practice still relies heavily on periodic and localized inspection rather than long-term continuous monitoring, and since water pipelines are buried underground, leaks can often go undetected for prolonged periods. Noninvasive acoustic-based methods for continuous pipeline monitoring have gained increasing popularity the past decade thanks to the recent advances in sensing and communication technology. Previous research indicates that hydrophones, in particular, are capable of effectively detecting leak-induced acoustic waves inside a water pipe. However, most studies to date have been limited to either controlled or field test-bed settings; hence, findings might not generalize well to real-world complex pipe networks. Through rigorous leak tests conducted in a real water distribution network and an extensive analysis of the field-collected acoustic signals, the current study aims to test the applicability of low-cost, non-intrusive hydrophones attached to fire hydrants for continuous pipe monitoring and leak detection. Continuous wavelet transform, power spectrum, and band power analyses were employed to identify the leak signature and distinguish normal from leak acoustic data in various leak scenarios. Results indicate that the acoustic signals generated by the simulated leaks in this field study are characterized by a consistent increase in the power of the frequency band 150–450 Hz primarily, whereas background noise levels and conditions significantly vary depending on the location of the sensor in the network. Realistic conditions in urban water distribution networks, including background noise, complicated topology, and varying pipe size and material, are still posing significant challenges for cost-effective and widespread implementation of acoustic-based sensors to achieve continuous monitoring in water pipe networks for leak detection. Even though further research and development is required to handle the highly variable conditions of real systems, the low-cost hydrophones tested in this work demonstrated potential in detecting low-flow leaks in simple and complex pipe topologies.