Search

In fermentation processes, changes in yeast cell count and substrate concentration are indicators of yeast performance. Therefore, monitoring the composition of the biological suspension, particularly the dispersed solid phase (i.e., yeast cells) and the continuous liquid phase (i.e., medium), is a prerequisite to ensure favorable process conditions. However, the available monitoring methods are often invasive or restricted by detection limits, sampling requirements, or susceptibility to masking effects from interfering signals. In contrast, ultrasound measurements are non-invasive and provide real-time data. In this study, the suitability to characterize the dispersed and the liquid phase of yeast suspensions with ultrasound was investigated. The ultrasound signals collected from three commercially available Saccharomyces yeast were evaluated and compared. For all three yeasts, the attenuation coefficient and speed of sound increased linearly with increasing yeast concentrations (0.0–1.0 wt%) and cell counts (R2 > 0.95). Further characterization of the dispersed phase revealed that cell diameter and volume density influence the attenuation of the ultrasound signal, whereas changes in the speed of sound were partially attributed to compositional variations in the liquid phase. This demonstrates the ability of ultrasound to monitor industrial fermentations and the feasibility of developing targeted control strategies. [ABSTRACT FROM AUTHOR]

Mapping the skin with various biophysical properties can demonstrate not only skin condition but also organize a convenient approach to managing diseases. The aim of this study, mapping of the regional alteration for 6 biophysical parameters with noninvasive method. Totally 39 dogs [healthy (n=16) and canine atopic dermatitis (n=23)] were enrolled. Skin pH, hydration, melanin, sebum content and temperature for pinna, perilabial region, hind-fore feet (dorsal metacarpus-dorsal metatarsus), axillae, lateral thorax/flanks, elbows, abdomen/inguinal and ventral tail were measured. Atopic dogs exhibited more acidic skin (P

Mapping the skin with various biophysical properties can demonstrate not only skin condition but also organize a convenient approach to managing diseases. The aim of this study, mapping of the regional alteration for 6 biophysical parameters with noninvasive method. Totally 39 dogs [healthy (n=16) and canine atopic dermatitis (n=23)] were enrolled. Skin pH, hydration, melanin, sebum content and temperature for pinna, perilabial region, hind-fore feet (dorsal metacarpus-dorsal metatarsus), axillae, lateral thorax/flanks, elbows, abdomen/inguinal and ventral tail were measured. Atopic dogs exhibited more acidic skin (P<0.001) compared to healthy dogs, with the thorax/ flanks region showing significant regional differences (P=0.037). Hydration levels were consistently lower in atopic dogs (P<0.001), with significant regional differences observed in the abdominal/inguinal region (P=0.037). Skin temperatures were generally higher in atopic dogs, with a significant increase noted in the tail (P=0.037), while other areas showed no significant differences. Melanin and sebum content did not exhibit significant regional variations. In conclusion, this study demonstrated regional variations in biophysical parameters in atopic dogs using non-invasive measurements. These findings provide valuable insights for understanding canine atopic dermatitis and its management. [ABSTRACT FROM AUTHOR]

The glucose level in the blood is measured through invasive methods, causing discomfort in the patient, loss of sensitivity in the area where the sample is obtained, and healing problems. This article deals with the design, implementation, and evaluation of a device with an ESP-WROOM-32D microcontroller with the application of near-infrared photospectroscopy technology that uses a diode array that transmits between 830 nm and 940 nm to measure glucose levels in the blood. In addition, the system provides a webpage for the monitoring and control of diabetes mellitus for each patient; the webpage is hosted on a local Linux server with a MySQL database. The tests are conducted on 120 people with an age range of 35 to 85 years; each person undergoes two sample collections with the traditional method and two with the non-invasive method. The developed device complies with the ranges established by the American Diabetes Association: presenting a measurement error margin of close to 3% in relation to traditional blood glucose measurement devices. The purpose of the study is to design and evaluate a device that uses non-invasive technology to measure blood glucose levels. This involves constructing a non-invasive glucometer prototype that is then evaluated in a group of participants with diabetes. [ABSTRACT FROM AUTHOR]

This study addresses the limitations of current tonometry techniques by exploring vibroacoustic properties for estimating intraocular pressure (IOP), a key diagnostic parameter for monitoring glaucoma—a significant risk factor for vision loss. Utilizing vivo porcine eyeballs, we investigated the relationship between IOP and the nonlinear vibration transfer function ratio (NVTFR). Through applying varying vibration levels and analyzing responses with transfer function analysis and univariate regression, we identified a strong negative correlation between NVTFR and IOP, evidenced by a Pearson correlation coefficient of −0.8111 and significant results from generalized linear model (GLM) regression (p-value < 0.001). These findings indicate the potential of NVTFR as a vital indicator of IOP changes. Our study highlights the feasibility of using vibroacoustic properties, specifically NVTFR, to measure IOP. While further refinement is necessary for in vivo application, this approach opens new possibilities for non-invasive and patient-friendly IOP monitoring, potentially enhancing ophthalmology diagnostic techniques and providing a foundation for future research and development in this critical area. [ABSTRACT FROM AUTHOR]

Background: Recent advancements in artificial intelligence have revolutionized dermatological diagnostics. These technologies, particularly machine learning (ML), including deep learning (DL), have shown accuracy equivalent or even superior to human experts in diagnosing skin conditions like melanoma. With the integration of ML, including DL, the development of at home skin analysis devices has become feasible. To this end, we introduced the Skinly system, a handheld device capable of evaluating various personal skin characteristics noninvasively. Materials and Methods: Equipped with a moisture sensor and a multi‐light‐source camera, Skinly can assess age‐related skin parameters and specific skin properties. Utilizing state‐of‐the‐art DL, Skinly processed vast amounts of images efficiently. The Skinly system's efficacy was validated both in the lab and at home, comparing its results to established "gold standard" methods. Results: Our findings revealed that the Skinly device can accurately measure age‐associated parameters, that is, facial age, skin evenness, and wrinkles. Furthermore, Skinly produced data consistent with established devices for parameters like glossiness, skin tone, redness, and porphyrin levels. A separate study was conducted to evaluate the effects of two moisturizing formulations on skin hydration in laboratory studies with standard instrumentation and at home with Skinly. Conclusion: Thanks to its capability for multi‐parameter measurements, the Skinly device, combined with its smartphone application, holds the potential to replace more expensive, time‐consuming diagnostic tools. Collectively, the Skinly device opens new avenues in dermatological research, offering a reliable, versatile tool for comprehensive skin analysis. [ABSTRACT FROM AUTHOR]

A proof-of-concept of a microwave imaging system for the fast detection of abdominal aortic aneurysms is shown. This experimental technology seeks to overcome the factors hampering the fast screening for these aneurysms with the usual equipment, such as high cost, long-time operation or hazardous exposure to chemical substances. The hardware system is composed of 16 twin antennas mastered by a microcontroller through a switching network, which connects the antennas to the measurement instrument for sequential measurement. The software system is run by a computer, mastering the whole system, automatizing the measurement process and running the signal processing and medical image generation algorithms. Two image generation algorithms are tested: Delay-and-Sum (DAS) and Improved Delay-and-Sum (IDAS). Own-modified versions of these algorithms adapted to the requirements of our system are proposed. The system is carefully calibrated and fine-tuned with known objects placed at known distances. An experimental proof-of-concept is shown with a human torso phantom, including an aorta phantom and an aneurysm phantom placed in different positions. The results show good imaging capabilities with the potential for detecting and locating possible abdominal aortic aneurysms and reporting acceptable errors. [ABSTRACT FROM AUTHOR]

Abstract Background Quantification of the cerebral metabolic rate of glucose (CMRGlu) by dynamic [18F]FDG PET requires invasive arterial sampling. Alternatives to using an arterial input function (AIF) include the simultaneous estimation (SIME) approach, which models the image-derived input function (IDIF) by a series of exponentials with coefficients obtained by fitting time activity curves (TACs) from multiple volumes-of-interest. A limitation of SIME is the assumption that the input function can be modelled accurately by a series of exponentials. Alternatively, we propose a SIME approach based on the two-tissue compartment model to extract a high signal-to-noise ratio (SNR) model-derived input function (MDIF) from the whole-brain TAC. The purpose of this study is to present the MDIF approach and its implementation in the analysis of animal and human data. Methods Simulations were performed to assess the accuracy of the MDIF approach. Animal experiments were conducted to compare derived MDIFs to measured AIFs (n = 5). Using dynamic [18F]FDG PET data from neurologically healthy volunteers (n = 18), the MDIF method was compared to the original SIME-IDIF. Lastly, the feasibility of extracting parametric images was investigated by implementing a variational Bayesian parameter estimation approach. Results Simulations demonstrated that the MDIF can be accurately extracted from a whole-brain TAC. Good agreement between MDIFs and measured AIFs was found in the animal experiments. Similarly, the MDIF-to-IDIF area-under-the-curve ratio from the human data was 1.02 ± 0.08, resulting in good agreement in grey matter CMRGlu: 24.5 ± 3.6 and 23.9 ± 3.2 mL/100 g/min for MDIF and IDIF, respectively. The MDIF method proved superior in characterizing the first pass of [18F]FDG. Groupwise parametric images obtained with the MDIF showed the expected spatial patterns. Conclusions A model-driven SIME method was proposed to derive high SNR input functions. Its potential was demonstrated by the good agreement between MDIFs and AIFs in animal experiments. In addition, CMRGlu estimates obtained in the human study agreed to literature values. The MDIF approach requires fewer fitting parameters than the original SIME method and has the advantage that it can model the shape of any input function. In turn, the high SNR of the MDIFs has the potential to facilitate the extraction of voxelwise parameters when combined with robust parameter estimation methods such as the variational Bayesian approach.

In fermentation processes, changes in yeast cell count and substrate concentration are indicators of yeast performance. Therefore, monitoring the composition of the biological suspension, particularly the dispersed solid phase (i.e., yeast cells) and the continuous liquid phase (i.e., medium), is a prerequisite to ensure favorable process conditions. However, the available monitoring methods are often invasive or restricted by detection limits, sampling requirements, or susceptibility to masking effects from interfering signals. In contrast, ultrasound measurements are non-invasive and provide real-time data. In this study, the suitability to characterize the dispersed and the liquid phase of yeast suspensions with ultrasound was investigated. The ultrasound signals collected from three commercially available Saccharomyces yeast were evaluated and compared. For all three yeasts, the attenuation coefficient and speed of sound increased linearly with increasing yeast concentrations (0.0–1.0 wt%) and cell counts (R2 > 0.95). Further characterization of the dispersed phase revealed that cell diameter and volume density influence the attenuation of the ultrasound signal, whereas changes in the speed of sound were partially attributed to compositional variations in the liquid phase. This demonstrates the ability of ultrasound to monitor industrial fermentations and the feasibility of developing targeted control strategies.

The glucose level in the blood is measured through invasive methods, causing discomfort in the patient, loss of sensitivity in the area where the sample is obtained, and healing problems. This article deals with the design, implementation, and evaluation of a device with an ESP-WROOM-32D microcontroller with the application of near-infrared photospectroscopy technology that uses a diode array that transmits between 830 nm and 940 nm to measure glucose levels in the blood. In addition, the system provides a webpage for the monitoring and control of diabetes mellitus for each patient; the webpage is hosted on a local Linux server with a MySQL database. The tests are conducted on 120 people with an age range of 35 to 85 years; each person undergoes two sample collections with the traditional method and two with the non-invasive method. The developed device complies with the ranges established by the American Diabetes Association: presenting a measurement error margin of close to 3% in relation to traditional blood glucose measurement devices. The purpose of the study is to design and evaluate a device that uses non-invasive technology to measure blood glucose levels. This involves constructing a non-invasive glucometer prototype that is then evaluated in a group of participants with diabetes.

This study addresses the limitations of current tonometry techniques by exploring vibroacoustic properties for estimating intraocular pressure (IOP), a key diagnostic parameter for monitoring glaucoma—a significant risk factor for vision loss. Utilizing vivo porcine eyeballs, we investigated the relationship between IOP and the nonlinear vibration transfer function ratio (NVTFR). Through applying varying vibration levels and analyzing responses with transfer function analysis and univariate regression, we identified a strong negative correlation between NVTFR and IOP, evidenced by a Pearson correlation coefficient of −0.8111 and significant results from generalized linear model (GLM) regression (p-value < 0.001). These findings indicate the potential of NVTFR as a vital indicator of IOP changes. Our study highlights the feasibility of using vibroacoustic properties, specifically NVTFR, to measure IOP. While further refinement is necessary for in vivo application, this approach opens new possibilities for non-invasive and patient-friendly IOP monitoring, potentially enhancing ophthalmology diagnostic techniques and providing a foundation for future research and development in this critical area.

Due to the advantages of ease of use, less motion disturbance, and low cost, wearable systems have been widely used in the human–machine interaction (HRI) field. However, HRI in complex clinical rehabilitation scenarios has further requirements for wearable sensor systems, which has aroused the interest of many researchers. However, the traditional wearable system has problems such as low integration, limited types of measurement data, and low accuracy, causing a gap with the actual needs of HRI. This paper will introduce the latest progress in the current wearable systems of HRI from four aspects. First of all, it introduces the breakthroughs of current research in system integration, which includes processing chips and flexible sensing modules to reduce the system's volume and increase battery life. After that, this paper reviews the latest progress of wearable systems in electrochemical measurement, which can extract single or multiple biomarkers from biological fluids such as sweat. In addition, the clinical application of non-invasive wearable systems is introduced, which solves the pain and discomfort problems caused by traditional clinical invasive measurement equipment. Finally, progress in the combination of current wearable systems and the latest machine-learning methods is shown, where higher accuracy and indirect acquisition of data that cannot be directly measured is achieved. From the evidence presented, we believe that the development trend of wearable systems in HRI is heading towards high integration, multi-electrochemical measurement data, and clinical and intelligent development. [ABSTRACT FROM AUTHOR]

A proof-of-concept of a microwave imaging system for the fast detection of abdominal aortic aneurysms is shown. This experimental technology seeks to overcome the factors hampering the fast screening for these aneurysms with the usual equipment, such as high cost, long-time operation or hazardous exposure to chemical substances. The hardware system is composed of 16 twin antennas mastered by a microcontroller through a switching network, which connects the antennas to the measurement instrument for sequential measurement. The software system is run by a computer, mastering the whole system, automatizing the measurement process and running the signal processing and medical image generation algorithms. Two image generation algorithms are tested: Delay-and-Sum (DAS) and Improved Delay-and-Sum (IDAS). Own-modified versions of these algorithms adapted to the requirements of our system are proposed. The system is carefully calibrated and fine-tuned with known objects placed at known distances. An experimental proof-of-concept is shown with a human torso phantom, including an aorta phantom and an aneurysm phantom placed in different positions. The results show good imaging capabilities with the potential for detecting and locating possible abdominal aortic aneurysms and reporting acceptable errors.

The representation of temperature measurement methods is worldwide, as is the number of industries that use them. Their utilization allows one to assess the object’s temperature relatively accurately and further according to the defined dependencies to evaluate its condition. In the medical sector, non-invasive temperature measurement methods are increasingly gaining ground. In our work, we focus on the design of a system for measuring skin temperature using digital DS18B20 thermometers. The technical design consists of the mechanical design of the sensor housing based on the requirements of healthcare professionals, the design of a 1-wire bus active pull-up driver with improved features, and the user software, allowing for the future implementation in various, not necessarily medical environments. The main contribution lies in optimizing the hardware design concerning the components’ parameters and surge protection. In the medical field, the aim was to compare changes in skin temperature in the shoulder region depending on the type of muscle contraction during static and dynamic components of movement and to record the thermal work of the muscle during activity in real-time. We experimented by applying temperature sensors to the deltoid muscle of the dominant limb in a temperature environment of 25.76 °C. In the experimental measurements, we demonstrated that during the three selected muscle work movements, there was a temperature change in the respective regions of the deltoid muscle for each of the three, which the temperature sensors could capture. Our results were statistically significant when comparing the baseline values, and the highest temperature reached. The level of significance $\alpha \leqslant 0.05$ and a low percentage of errors were valid.

The analysis of infrared spectroscopy of substances is a non-invasive measurement technique that can be used in analytics. Although the main objective of this study is to provide a review of machine learning (ML) algorithms that have been reported for analyzing near-infrared (NIR) spectroscopy from traditional machine learning methods to deep network architectures, we also provide different NIR measurement modes, instruments, signal preprocessing methods, etc. Firstly, four different measurement modes available in NIR are reviewed, different types of NIR instruments are compared, and a summary of NIR data analysis methods is provided. Secondly, the public NIR spectroscopy datasets are briefly discussed, with links provided. Thirdly, the widely used data preprocessing and feature selection algorithms that have been reported for NIR spectroscopy are presented. Then, the majority of the traditional machine learning methods and deep network architectures that are commonly employed are covered. Finally, we conclude that developing the integration of a variety of machine learning algorithms in an efficient and lightweight manner is a significant future research direction. [ABSTRACT FROM AUTHOR]

Due to the advantages of ease of use, less motion disturbance, and low cost, wearable systems have been widely used in the human–machine interaction (HRI) field. However, HRI in complex clinical rehabilitation scenarios has further requirements for wearable sensor systems, which has aroused the interest of many researchers. However, the traditional wearable system has problems such as low integration, limited types of measurement data, and low accuracy, causing a gap with the actual needs of HRI. This paper will introduce the latest progress in the current wearable systems of HRI from four aspects. First of all, it introduces the breakthroughs of current research in system integration, which includes processing chips and flexible sensing modules to reduce the system’s volume and increase battery life. After that, this paper reviews the latest progress of wearable systems in electrochemical measurement, which can extract single or multiple biomarkers from biological fluids such as sweat. In addition, the clinical application of non-invasive wearable systems is introduced, which solves the pain and discomfort problems caused by traditional clinical invasive measurement equipment. Finally, progress in the combination of current wearable systems and the latest machine-learning methods is shown, where higher accuracy and indirect acquisition of data that cannot be directly measured is achieved. From the evidence presented, we believe that the development trend of wearable systems in HRI is heading towards high integration, multi-electrochemical measurement data, and clinical and intelligent development.

Aim: To assess the usefulness and efficacy of pulse oximetry (disappearance/reappearance of plethsmographic waves) as a method of non-invasive blood pressure monitoring in neonates. Objective: To investigate the reliability of the plethysmographic wave form of the pulse oximeter to measure the systolic blood pressure. Study Setting: A prospective observational study was done to assess usefulness and efficacy of pulse oximetry (disappearance/reappearance of plethysmographic waves) as a method of non-invasive blood pressure monitoring in neonates. Material and Methods: The study was conducted among 500 neonates to investigate the reliability of the plethysmographic waveform of the pulse oximeter to measure the systolic blood pressure as it is a easy way to perform and non invasive. Statistical Analysis Used: The results will compare and analyse statistically by Pearson correlation co-efficient. Regression modeling will carried out to explain the relationship of non-invasive blood pressure with mean DP and RP and attempted to predict the non-invasive blood pressure from mean DP/mean RP. Results: The study results revealed that NIBP systolic and diastolic both correlated with DP and RP of pulse oximetry plethysmograph. Conclusion: Study concluded that pulse oximetry is a reliable tool in measuring blood pressure in neonates (appearance and disappearance of plethysmogram).

A measurement setup for localising people in indoor environment based on a system characterized by acquisition of audio files and images implemented on a sensorised social robot is proposed. The audio signal processing for human voice identification applies the segmentation methodology for the direction of arrival (DOA) estimation. The audio signal analysis evaluates the performance of beamforming algorithms and of Covariance Matrix Fitting (CMF) when optimization in beamforming algorithm and alternative microphones’ configurations have been evaluated by simulations. Tests shows an accuracy in people detection of the optimized beamforming algorithm comparable to CMF method (96.5% and 96.6% respectively) with a lower computational cost. An image acquisition procedure has been then activated on the robot and the localisation of the people is performed using YOLO-v3 algorithm. Monte Carlo method applied to evaluate the propagation of uncertainty of the whole processing system presents a global accuracy of 98.2 ± 0.8%.

Objective: Today, there are various non-invasive techniques available for the determination of blood glucose levels. In this study, the level of blood glucose was determined by developing a new device using near-infrared (NIR) wavelength, glass optical waveguide, and the phenomenon of evanescent waves. Materials and Methods: The body's interstitial fluid has made possible the development of new technology to measure the blood glucose. As a result of contacting the fingertip with the body of the borehole rod, where electromagnetic waves are reflected inside, evanescent waves penetrate from the borehole into the skin and are absorbed by the interstitial fluid. The electromagnetic wave rate absorption at the end of the borehole rod is investigated using a detection photodetector, and its relationship to the people's actual blood glucose level. Following precise optimization and design of the glucose monitoring device, a statistical population of 100 participants with a maximum blood glucose concentration of 200 mg/dL was chosen. Before measurements, participants put their index finger for 30 seconds on the device. Results: According to this experimental study, the values measured by the innovative device with Clark grid analysis were clinically acceptable in scales A and B. The Adjusted Coefficient of Determination of the data was estimated to be 0.9064. Conclusion: For future investigations, researchers are recommended to work with a larger statistical population and use error reduction trends to improve the accuracy and expand the range of measurements.

This work introduces a microwave-based system able to detect tumours in breast phantoms in a non-invasive way. The data acquisition system is composed of a hardware system which involves high-frequency components (antennas, switches and cables), a microcontroller, a vector network analyser used as measurement instrument and a computer devoted to the control and automation of the operation of the system. Concerning the software system, the computer runs a Python script which is in charge of mastering and automatising all the required stages for the data acquisition, from initialisation of the hardware system to performing and saving the measurements. We also report on the design of the high-performance broadband antenna used to carry out the measurements, as well as on the algorithm employed to build the final medical images, based on an adapted version of the so-called Improved Delay-and-Sum (IDAS) algorithm improved by a Hamming window filter and averaging preprocessing. The calibration and start-up of the system are also described. The experimental validation includes the use of different tumour models with different dielectric properties inside the breast phantom. The results show promising tumour detection capabilities, even when there is low dielectric contrast between the tumoural and healthy tissues, as is the usual case for dense breasts in young women. [ABSTRACT FROM AUTHOR]

Aim: To assess the usefulness and efficacy of pulse oximetry (disappearance/reappearance of plethsmographic waves) as a method of non-invasive blood pressure monitoring in neonates. Objective: To investigate the reliability of the plethysmographic wave form of the pulse oximeter to measure the systolic blood pressure. Study Setting: A prospective observational study was done to assess usefulness and efficacy of pulse oximetry (disappearance/reappearance of plethysmographic waves) as a method of non-invasive blood pressure monitoring in neonates. Material and Methods: The study was conducted among 500 neonates to investigate the reliability of the plethysmographic waveform of the pulse oximeter to measure the systolic blood pressure as it is a easy way to perform and non invasive. Statistical Analysis Used: The results will compare and analyse statistically by Pearson correlation co-efficient. Regression modeling will carried out to explain the relationship of non-invasive blood pressure with mean DP and RP and attempted to predict the non-invasive blood pressure from mean DP/mean RP. Results: The study results revealed that NIBP systolic and diastolic both correlated with DP and RP of pulse oximetry plethysmograph. Conclusion: Study concluded that pulse oximetry is a reliable tool in measuring blood pressure in neonates (appearance and disappearance of plethysmogram). [ABSTRACT FROM AUTHOR]

Abstract Background Trends in non-invasive measurements of blood hemoglobin (Hb) may be useful for identifying the need for transfusion in the perioperative period. Methods Crystalloid fluid (5–20 mL/kg) was administered intravenously or by mouth to 30 volunteers and 33 surgical patients in five non-randomized clinical studies where Hb was measured on 915 occasions by non-invasive (Radical-7™) and invasive methodology. The hemodilution curves were compared by volume kinetic analysis and linear regression, with the slope and scattering of the data as key outcome measures. Results The slope was 1.0, indicating unity between the two modes of measuring Hb when crystalloid fluid was infused in volunteers; however, only 40–45% of the variability in the non-invasive Hb could be explained by the invasive Hb. Patients undergoing major surgery, who showed the most pronounced hemodilution (median 24 g/L); non-invasive Hb explained 72% of the variability but indicated only half the magnitude of the invasive Hb changes (slope 0.48, P

Abstract Background Pancreatic exocrine insufficiency (PEI) is associated with the outcome of pancreatic disease. However, there is no method for assessing PEI that can be used noninvasively and easily for outpatient. It has been reported that changes in intestinal bacteria caused by PEI may increase breath hydrogen concentration (BHC) levels during glucose or lactose loading. We have evaluated the usefulness of fasting breath hydrogen concentration (FBHC) measurement without glucose loading for the evaluation of PEI. Methods Sixty patients underwent FBHC measurement, BT-PABA testing, and microbiome analysis. They were classified into PEI group (PABA excretion rate

• The float-sink motions of objects in a gas-solid fluidized bed were investigated. • A wireless sensor measures 3D position of object immersed in the fluidized bed. • The float–sink motions of objects in the fluidized bed differ markedly from those in liquids. • There are two barriers for the objects in the vertical direction in the bed. We developed a Lagrangian sensor system capable of wirelessly measuring the 3D motions of objects and applied it to examine the floating and sinking behaviors in a gas–solid fluidized bed. The system consisted of a sensor particle, comprising a 9-axis sensor and a wireless module integrated into a spherical outer shell, and three pairs of magnetic coils. By utilizing this system, we can non-invasively measure the 3D motions of objects, which cannot be observed from the outside. In this study, we examined the motions of objects with various densities in the gas–solid fluidized bed. We found the similarity and dissimilarity between the float–sink motions of objects in fluidized beds and those in liquids. The experimental results revealed that the vertical motion of an object in the fluidized bed depends on its density and can be categorized into two distinct states: floating near the surface or settling down at the bottom. However, within a specific range of object densities close to the apparent density of the fluidized bed, the object exhibited complicated motions in the bed. In such cases, slight density variations induced unpredictable changes between the floating and sinking states. The results also suggested that the settling velocity of the objects in the fluidized bed varies with their vertical positions in the bed. [Display omitted] [ABSTRACT FROM AUTHOR]

Objective: Today, there are various non-invasive techniques available for the determination of blood glucose levels. In this study, the level of blood glucose was determined by developing a new device using near-infrared (NIR) wavelength, glass optical waveguide, and the phenomenon of evanescent waves. Materials and Methods: The body's interstitial fluid has made possible the development of new technology to measure the blood glucose. As a result of contacting the fingertip with the body of the borehole rod, where electromagnetic waves are reflected inside, evanescent waves penetrate from the borehole into the skin and are absorbed by the interstitial fluid. The electromagnetic wave rate absorption at the end of the borehole rod is investigated using a detection photodetector, and its relationship to the people's actual blood glucose level. Following precise optimization and design of the glucose monitoring device, a statistical population of 100 participants with a maximum blood glucose concentration of 200 mg/dL was chosen. Before measurements, participants put their index finger for 30 seconds on the device. Results: According to this experimental study, the values measured by the innovative device with Clark grid analysis were clinically acceptable in scales A and B. The Adjusted Coefficient of Determination of the data was estimated to be 0.9064. Conclusion: For future investigations, researchers are recommended to work with a larger statistical population and use error reduction trends to improve the accuracy and expand the range of measurements. [ABSTRACT FROM AUTHOR]

Wei Liu,1 Xingquan Huang,1,2 Xiuying Zhang,1 Xiaoling Cai,1 Xueyao Han,1 Xianghai Zhou,1 Ling Chen,1 Rui Zhang,1 Siqian Gong,1 Yanai Wang,1 Linong Ji1 1Department of Endocrinology and Metabolism, Peking University People’s Hospital, Beijing, People’s Republic of China; 2Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei, People’s Republic of ChinaCorrespondence: Linong JiDepartment of Endocrinology and Metabolism, Peking University People’s Hospital, No. 11, Xi Zhi Men Nan Street, Beijing 100044, People’s Republic of ChinaTel +86-10-88324108Fax +86-10-88324371Email jiln@bjmu.edu.cnPurpose: Latent autoimmune diabetes in adults (LADA) is a slowly progressing form of immune-mediated diabetes that combines phenotypical features of both type 2 diabetes mellitus (T2DM) and type 1 diabetes mellitus (T1DM), meaning that accurate and early diagnosis of this subtype of diabetes is critical for optimal long-term management. Urinary C-peptide creatinine ratio (UCPCR) represents a non-invasive and practical method for assessing endogenous insulin production to facilitate diabetes classification. However, no study to date has reported the use of UCPCR in identifying LADA.Patients and methods: A total of 574 subjects were included in our study (42 LADA, 61 T1DM, 471 T2DM). All participants were evaluated for UCPCR and underwent clinical and laboratory evaluations. UCPCR was compared among different subtypes of diabetes using multinomial regression analysis, and a receiver operating characteristic (ROC) curve was used to identify its performance in diagnosing LADA.Results: UCPCR was lower in LADA (0.4±0.6 nmol/mmol) compared with T2DM (1.2±0.9 nmol/mmol), but higher than in T1DM (0.2±0.3 nmol/mmol) (p

The analysis of infrared spectroscopy of substances is a non-invasive measurement technique that can be used in analytics. Although the main objective of this study is to provide a review of machine learning (ML) algorithms that have been reported for analyzing near-infrared (NIR) spectroscopy from traditional machine learning methods to deep network architectures, we also provide different NIR measurement modes, instruments, signal preprocessing methods, etc. Firstly, four different measurement modes available in NIR are reviewed, different types of NIR instruments are compared, and a summary of NIR data analysis methods is provided. Secondly, the public NIR spectroscopy datasets are briefly discussed, with links provided. Thirdly, the widely used data preprocessing and feature selection algorithms that have been reported for NIR spectroscopy are presented. Then, the majority of the traditional machine learning methods and deep network architectures that are commonly employed are covered. Finally, we conclude that developing the integration of a variety of machine learning algorithms in an efficient and lightweight manner is a significant future research direction.

Backgrounds: Acute myocardial infarction (AMI) affects the autonomic nervous system (ANS) function. The aim of our study is to detect the particular patterns of ANS regulation in AMI. We hypothesize that altered ANS regulation in AMI patients causes synchronized neural discharge (clustering phenomenon) detected by non-invasive skin sympathetic nerve activity (SKNA). Methods: Forty subjects, including 20 AMI patients and 20 non-AMI controls, participated in the study. The wide-band bioelectrical signals (neuECG) were continuously recorded on the body surface for 5 min. SKNA was signal processed to depict the envelope of SKNA (eSKNA). By labeling the clusters, the AMI subjects were separated into non-AMI, non-cluster appearing (AMINCA), and cluster appearing (AMICA) groups. Results: The average eSKNA was significantly correlated with HRV low-frequency (LF) power (rho = −0.336) and high-frequency power (rho = −0.372). The cross-comparison results demonstrated that eSKNA is a valid surrogate marker to assess ANS in AMI patients. The frequency of cluster occurrence was 0.01–0.03 Hz and the amplitude was about 3 μV. The LF/HF ratio of AMICA (median: 1.877; Q1–Q3: 1.483–2.413) revealed significantly lower than AMINCA (median: 3.959; Q1–Q3: 1.840–6.562). The results suggest that the SKNA clustering is a unique temporal pattern of ANS synchronized discharge, which could indicate the lower sympathetic status (by HRV) in AMI patients. Conclusion: This is the first study to identify SKNA clustering phenomenon in AMI patients. Such a synchronized nerve discharge pattern could be detected with non-invasive SKNA signals. SKNA temporal clustering could be a novel biomarker to classify ANS regulation ability in AMI patients. Clinical and Translational Significance: SKNA is higher in AMI patients than in control and negatively correlates with parasympathetic parameters. SKNA clustering is associated with a lower LF/HF ratio that has been shown to correlate with sudden cardiac death in AMI. The lack of SKNA temporal clustering could indicate poor ANS regulation in AMI patients. [ABSTRACT FROM AUTHOR]

Background: Trends in non-invasive measurements of blood hemoglobin (Hb) may be useful for identifying the need for transfusion in the perioperative period. Methods: Crystalloid fluid (5–20 mL/kg) was administered intravenously or by mouth to 30 volunteers and 33 surgical patients in five non-randomized clinical studies where Hb was measured on 915 occasions by non-invasive (Radical-7™) and invasive methodology. The hemodilution curves were compared by volume kinetic analysis and linear regression, with the slope and scattering of the data as key outcome measures. Results: The slope was 1.0, indicating unity between the two modes of measuring Hb when crystalloid fluid was infused in volunteers; however, only 40–45% of the variability in the non-invasive Hb could be explained by the invasive Hb. Patients undergoing major surgery, who showed the most pronounced hemodilution (median 24 g/L); non-invasive Hb explained 72% of the variability but indicated only half the magnitude of the invasive Hb changes (slope 0.48, P < 0.001 versus the volunteers). Simulations based on volume kinetic parameters from the volunteers showed 25% less plasma volume expansion after infusion when based on non-invasive as compared to invasive Hb, while no difference was found during infusion. Conclusions: In volunteers the non-invasive Hb had good accuracy (low bias) but poor precision. In surgical patients the non-invasive Hb had good precision but systematically underestimated the hemodilution. Despite severe limitations, the non-invasive technology can be used to follow Hb trends during surgery if supported by occasional invasive measurements to assure acceptable quality of the hemodilution curve. Trial registrations: ControlledTrials.gov NCT01195025, NCT01062776, NCT01458678, NCT03848507, and NCT01360333 on September 3, 2010, February 4, 2010, October 25, 2011, February 20, 2019, and May 25, 2011, respectively. [ABSTRACT FROM AUTHOR]

Backgrounds: Acute myocardial infarction (AMI) affects the autonomic nervous system (ANS) function. The aim of our study is to detect the particular patterns of ANS regulation in AMI. We hypothesize that altered ANS regulation in AMI patients causes synchronized neural discharge (clustering phenomenon) detected by non-invasive skin sympathetic nerve activity (SKNA).Methods: Forty subjects, including 20 AMI patients and 20 non-AMI controls, participated in the study. The wide-band bioelectrical signals (neuECG) were continuously recorded on the body surface for 5 min. SKNA was signal processed to depict the envelope of SKNA (eSKNA). By labeling the clusters, the AMI subjects were separated into non-AMI, non-cluster appearing (AMINCA), and cluster appearing (AMICA) groups.Results: The average eSKNA was significantly correlated with HRV low-frequency (LF) power (rho = −0.336) and high-frequency power (rho = −0.372). The cross-comparison results demonstrated that eSKNA is a valid surrogate marker to assess ANS in AMI patients. The frequency of cluster occurrence was 0.01–0.03 Hz and the amplitude was about 3 μV. The LF/HF ratio of AMICA (median: 1.877; Q1–Q3: 1.483–2.413) revealed significantly lower than AMINCA (median: 3.959; Q1–Q3: 1.840–6.562). The results suggest that the SKNA clustering is a unique temporal pattern of ANS synchronized discharge, which could indicate the lower sympathetic status (by HRV) in AMI patients.Conclusion: This is the first study to identify SKNA clustering phenomenon in AMI patients. Such a synchronized nerve discharge pattern could be detected with non-invasive SKNA signals. SKNA temporal clustering could be a novel biomarker to classify ANS regulation ability in AMI patients.Clinical and Translational Significance: SKNA is higher in AMI patients than in control and negatively correlates with parasympathetic parameters. SKNA clustering is associated with a lower LF/HF ratio that has been shown to correlate with sudden cardiac death in AMI. The lack of SKNA temporal clustering could indicate poor ANS regulation in AMI patients.

Background: Arterial stiffness, measured by pulse wave velocity (PWV), is a purported mechanism linking sedentary behavior to cardiovascular disease. This secondary analysis compared associations between measured carotid–femoral PWV (cfPWV) and carotid–radial (crPWV) responses to an acute bout of prolonged sitting with mathematically estimated cfPWV (ePWV). Methods: Overweight/obese adults with elevated blood pressure were enrolled (n = 25; 42 ± 12 yrs; 64% males). Participants performed an 8 h simulated workday of mostly sitting. cfPWV and crPWV were measured while supine in the morning, midday, and afternoon. ePWV was calculated at the same timepoints using age and seated mean arterial pressure (MAP). Pearson correlation coefficients associated ePWV with cfPWV and crPWV. Generalized linear models separately examined the effects of time on cfPWV, crPWV, and ePWV. Results: ePWV significantly associated with cfPWV and crPWV (r = 0.69 and 0.55, respectively; p < 0.05) in the morning (baseline). cfPWV significantly increased over time (β = 0.52 ± 0.20 and 0.48 ± 0.21 with and without MAP adjustment, respectively; p < 0.05). In contrast, ePWV and crPWV did not significantly increase overtime (β = 0.14 ± 0.09 and 0.25 ± 0.23, respectively; p > 0.05). Conclusions: Our results suggest that, although ePWV is associated with cfPWV and crPWV at a fixed timepoint, ePWV responds differently to prolonged sitting and likely does not capture the same acute vascular responses.

This work introduces a microwave-based system able to detect tumours in breast phantoms in a non-invasive way. The data acquisition system is composed of a hardware system which involves high-frequency components (antennas, switches and cables), a microcontroller, a vector network analyser used as measurement instrument and a computer devoted to the control and automation of the operation of the system. Concerning the software system, the computer runs a Python script which is in charge of mastering and automatising all the required stages for the data acquisition, from initialisation of the hardware system to performing and saving the measurements. We also report on the design of the high-performance broadband antenna used to carry out the measurements, as well as on the algorithm employed to build the final medical images, based on an adapted version of the so-called Improved Delay-and-Sum (IDAS) algorithm improved by a Hamming window filter and averaging preprocessing. The calibration and start-up of the system are also described. The experimental validation includes the use of different tumour models with different dielectric properties inside the breast phantom. The results show promising tumour detection capabilities, even when there is low dielectric contrast between the tumoural and healthy tissues, as is the usual case for dense breasts in young women.

When a joint undergoes a range of motion, its constituents rub against each other, causing friction and thus vibrations. The vibration arthrography (VAG) technique consists of detecting, recording, and processing those vibrations to diagnose disorders. This non-invasive method could be an alternative to the currently used arthroscopy or X-rays. It has been revealed to be as accurate as these methods in terms of detecting pathologies such as osteoarthritis (OA). Moreover, vibrational analysis has highlighted some physiological signals associated with the displacement of knee joint components. Thus, vibroarthrography provides further understanding of the internal mechanisms of the knee joint. This paper aims to examine the research progress on the use of this vibration arthrography technique in diagnosing knee disorders. [ABSTRACT FROM AUTHOR]

To measure the heart rate of unrestrained sea turtles, it has been believed that a probe must be inserted inside the body owing to the presence of the shell. However, inserting the probe is invasive and difficult to apply to animals in the field. Here, we have developed a non-invasive heart rate measurement method for some species of sea turtles. In our approach, an electrocardiogram (ECG) was performed using an animal-borne ECG recorder and two electrodes--which were electrically insulated from seawater--pasted on the carapace. Based on the measured ECG, the heartbeat signals were identified with an algorithm using a band-pass filter. We implemented this algorithm in a user-friendly program package, ECGtoHR. In experiments conducted in a water tank and in a lagoon, we successfully measured the heart rate of loggerhead, olive ridley and black turtles, but not green and hawksbill turtles. The average heart rate of turtles when resting underwater was 6.2 ± 1.9 beats min-1 and that when moving at the surface was 14.0 ± 2.4 beats min-1. Our approach is particularly suitable for endangered species such as sea turtles, and has the potential to be extended to a variety of other free-ranging species. [ABSTRACT FROM AUTHOR]

Information about ploidy is important in both commercial and conservation aquaculture and fish research. Unfortunately, methods for its determination, such as karyology, determination of the amount of DNA in a cell using microdensitometry or flow cytometry and/or measuring erythrocytes in a blood smear can be stressful or even destructive. Some of these methods are also limited by the relatively large minimum size of the individual being measured. The aim of this study was to test a new low-stress method of determining ploidy by measuring the size of erythrocytes in the capillaries of a fish, including small individuals. First, we examined diploid and triploid loach (Cobitis sp.) and gibel carp, Carassius gibelio (Bloch, 1782), using flow cytometry and blood smears, with these results being used as a control. Subsequently, we measured the size of erythrocytes in the caudal fin capillaries of anesthetized fishes of known ploidy under a light microscope. For both the loaches and gibel carp, direct observation of the mean erythrocyte size in epithelial fin capillaries provided a consistent and reliable determination of ploidy when compared with the controls based on flow cytometry and blood smears. This new method allows for rapid determination of ploidy in living small fish, where collection of tissue using other methods may cause excessive stress or damage. The method outlined here simply requires the measurement of erythrocytes directly in the bloodstream of a live fish, thereby making it possible to determine ploidy without the need for blood sampling. The method described is sufficiently efficient, less demanding on equipment than many other procedures, can be used by relatively inexperienced personnel and has benefits as regards animal welfare, which is especially important for fish production facilities or when dealing with rare or endangered species. [ABSTRACT FROM AUTHOR]

Copyright of Folia Cardiologica is the property of VM Medica-VM Group (Via Medica) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

There is a lack of quantitative and non-invasive clinical biomechanical assessment tools for diabetic foot ulcers. Our previous study reported that the indentation stiffness measured by an optical coherence tomography-based air-jet indentation system in a non-contact and non-invasive manner may reflect the tensile properties of diabetic wounds. As the tensile properties are known to be contributed by type I collagen, this study was aimed to establish the correlations between the indentation stiffness, and type I collagen abundance and organisation, in order to further justify and characterise the in vivo indentation stiffness measurement in diabetic wounds. In a male streptozotocin-induced diabetic rat model, indentation stiffness, and type I collagen abundance and organisation of excisional wounds were quantified and examined using the optical coherence tomography-based air-jet indentation system and picrosirius red polarised light microscopy, respectively, on post-wounding days 3, 5, 7, 10, 14, and 21. The results showed significant negative correlations between indentation stiffness at the wound centre, and the collagen abundance and organisation. The correlations between the indentation stiffness, as well as collagen abundance and organisation of diabetic wounds suggest that the optical coherence tomography-based air-jet indentation system can potentially be used to quantitatively and non-invasively monitor diabetic wound healing in clinical settings, clinical research or preclinical research.

Background: Pancreatic exocrine insufficiency (PEI) is associated with the outcome of pancreatic disease. However, there is no method for assessing PEI that can be used noninvasively and easily for outpatient. It has been reported that changes in intestinal bacteria caused by PEI may increase breath hydrogen concentration (BHC) levels during glucose or lactose loading. We have evaluated the usefulness of fasting breath hydrogen concentration (FBHC) measurement without glucose loading for the evaluation of PEI.Methods: Sixty patients underwent FBHC measurement, BT-PABA testing, and microbiome analysis. They were classified into PEI group (PABA excretion rate < 73.4%, n = 30) and non-PEI group (n = 30). The FBHC of the two groups were compared, and the diagnostic ability of PEI by them was evaluated. The 16 s rRNA (V3-V4) from fecal samples was analyzed by MiSeq.Results: FBHC levels was higher in the PEI group 15.70 (1.4 to 77.0) ppm than in the non-PEI group 2.80 (0.7 to 28.2) ppm (P < 0.0001). FBHC was negatively correlated with PABA excretion rate (r =  - 0.523, P < 0.001). The cutoff value of FBHC of 10.7 ppm (95% CI: 0.678-0.913, P < 0.001) showed a sensitivity of 73.3% and specificity of 83.3% for PEI diagnosis. In the PEI group, there was a significant increase of relative abundance of phylum Firmicutes (P < 0.05) and the genus Clostridium (P < 0.05).Conclusion: FBHC shows good potential as a simple and repeatable test for the diagnosis of PEI. The elevated FBHC levels may be caused by hydrogen-producing bacteria such as Clostridium. [ABSTRACT FROM AUTHOR]

The development of biofilms and the related changes in porous media in the subsurface cannot be directly observed and evaluated. The primary reason that the mechanism of biofilm clogging in porous media cannot be clearly demonstrated is due to the opacity and structural complexity of three-dimensional pore space. Interest in exploring methods to overcome this limitation has been increasing. In the first part of this review, we introduce the underlying characteristics of biofilm in porous media. Then, we summarize two approaches, non-invasive measurement methods and mathematical simulation strategies, for studying fluid–biofilm–porous medium interaction with spatiotemporal resolution. We also discuss the advantages and limitations of these approaches. Lastly, we provide a perspective on opportunities for in situ monitoring at the field site. [ABSTRACT FROM AUTHOR]

Because the lips are external organs, they can be easily observed by means that are non-invasive, including simple video recording. The current paper introduces a free-of-charge, highly portable, automatic solution for extracting oral posture from digital video, based on an existing facetracking utility. We describe how this solution might benefit various lines of laboratory phonology research, including analysis of articulatory coordination and audiovisual speech, as well as phonetic fieldwork. We then provide a tutorial, framed as a simple experiment in metronomic speech. The tutorial describes how to configure the software to work with one’s digital camera of choice, how to extract relevant articulatory parameters from the face tracker, and how to approach statistical analysis. We have supplied pre-written Python scripts to aid the reader in following along with the experiment. The portability, ease, and affordability of the described solution have important implications for the accessibility of articulatory measurement, both in the lab and out in the field.

Abstract Background Blood pressure (BP) is currently the main hemodynamic parameter used to assess the influence of fluid removal during hemodialysis session. Since BP is dependent on cardiac output (CO) and total peripheral resistance (TPRI), investigating these parameters may help to better understand the influence of fluid removal on patient’s hemodynamics. We used a novel non-invasive whole-body bio-impedance cardiography device, recently validated in hemodialysis patients, to examine mechanisms of intradialytic hemodynamics in a Chinese dialysis population. Methods Chronic hemodialysis patients in Sichuan Provincial People’s Hospital were enrolled. Demographic data and dialysis prescriptions were collected. Hemodynamic measurements were made pre-treatment, every 20 min during treatment and immediately after treatment in each random dialysis session. These included blood pressure, cardiac index (CI), total peripheral resistance (TPRI) and cardiac power index (CPI). Patients were divided into 5 hemodynamic groups as per their major hemodynamic response to fluid removal: low CPI, low TPRI, high TPRI, High CPI and those with normal hemodynamics. Results Twenty-seven patients were enrolled, with 12 (44.4%) males. The average age was 65 ± 12 y. The average body mass index (BMI) was 23.7 ± 3.9 kg/m2. 12 (44.4%) patients were diabetic. Three hundred twenty-four hemodynamic measurements were made. Weight, BMI, total fluid removal, pretreatment systolic BP, CI, TPRI and CI differed significantly among the 5 hemodynamic groups.11.1% of patients had low CPI, 25.9% had low TPRI, 18.5% had high CPI, 3.7% had high TPRI and 40.7% had normal hemodynamics. Hemodynamic differences among the 5 subgroups were significant. Conclusion This technology provides multi-dimensional insight into intradialytic hemodynamic parameters, which may be more informative than blood pressure only. Using hemodynamic parameters to describe patients’ status is more specific and accurate, and could help to work out specific and effective therapeutic actions according to underlying abnormalities.

In this paper, a remote sensing method for heart rate (HR) detection is proposed via nearinfrared facial video data, which can be used for the online monitoring of the physiological parameters of the drivers and further analysis so as to enhance the driving safety. The proposed HR detection method is based on an automatic facial tracking algorithm, i.e., the Kanade-Lucas-Tomasi, to transform the facial images into time-series signals. Empirical mode decomposition, bandpass filtering and fast Fourier transformation are applied to the time-series signals for the HR extraction. Indoor experiments in different scenarios are conducted to discuss the involved impact factors, i.e., the distance between the near-infrared camera and the participant, the illumination intensity and the video duration, to acquire the optimal settings for HR measurement. It is more robust and convenient than those of the current commercial devices and webcambased HR measurement approaches, especially in complex illumination environments, such as wearing hat, glasses or makeup, with measurement accuracy 95%. Field experiments are also performed for the prognosis of physical state of the driver.

• Invasive and non-invasive CBT measurements were concurrently assessed and compared. • Non-invasive CBT measurement can serve as a general reference for sleep research. • Body fat rate and heat flux significantly affect the reliable of non-invasive CBT measurement. • Further optimization is possible in the algorithms for non-invasive CBT measurements. Core body temperature (CBT) emerges as a pivotal physiological marker in sleep research, and the commonly employed invasive CBT measurements significantly disrupt the sleep process itself. Non-invasive CBT measurement offers a viable solution to this challenge but lack validation. In this sleep study, simultaneous invasive and non-invasive measurements of CBT were conducted on 14 subjects. Ingestible capsule was chosen to represent invasive measurement, while external GreenTeg patch was selected as representative device for non-invasive measurement. Quantitative comparisons of two measurements were conducted from four perspectives: correlation, consistency, difference, and stability, and results indicated: (1) A significant correlation was observed between two real-time measurements, and correlation became stronger as ambient temperature decreased. (2) Consistency of most data group can be acceptable as most of them fell within the 95% agreement range. (3) Non-invasive instrument exhibited substantial error for unstable core temperature, yet displayed relatively small error for stable core temperature. (4) Stability of difference between two measurements was poor during 64.3% of the time intervals, and this performance deteriorated further in unstable state. In summary, existing non-invasive measurement can serve as a reference for sleep research, but caution is warranted when applying it to real-time and unstable analyses. Additionally, feasibility of algorithm optimization makes the future of non-invasive measurements promising. [ABSTRACT FROM AUTHOR]

Intra-abdominal hypertension, defined as an intra-abdominal pressure (IAP) equal to or above 12 mmHg is one of the major risk-factors for increased morbidity (organ failure) and mortality in critically ill patients. Therefore, IAP monitoring is highly recommended in intensive care unit (ICU) patients to predict development of abdominal compartment syndrome and to provide a better care for patients hospitalized in the ICU. The IAP measurement through the bladder is the actual reference standard advocated by the abdominal compartment society; however, this measurement technique is cumbersome, non-continuous, and carries a potential risk for urinary tract infections and urethral injury. Using microwave reflectometry has been proposed as one of the most promising IAP measurement alternatives. In this study, a novel radar-based method known as transient radar method (TRM) has been used to monitor the IAP in an in vitro model with an advanced abdominal wall phantom. In the second part of the study, further regression analyses have been done to calibrate the TRM system and measure the absolute value of IAP. A correlation of –0.97 with a p-value of 0.0001 was found between the IAP and the reflection response of the abdominal wall phantom. Additionally, a quadratic relation with a bias of −0.06 mmHg was found between IAP obtained from the TRM technique and the IAP values recorded by a pressure gauge. This study showed a promising future for further developing the TRM technique to use it in clinical monitoring.

When a joint undergoes a range of motion, its constituents rub against each other, causing friction and thus vibrations. The vibration arthrography (VAG) technique consists of detecting, recording, and processing those vibrations to diagnose disorders. This non-invasive method could be an alternative to the currently used arthroscopy or X-rays. It has been revealed to be as accurate as these methods in terms of detecting pathologies such as osteoarthritis (OA). Moreover, vibrational analysis has highlighted some physiological signals associated with the displacement of knee joint components. Thus, vibroarthrography provides further understanding of the internal mechanisms of the knee joint. This paper aims to examine the research progress on the use of this vibration arthrography technique in diagnosing knee disorders.

Nowadays, the application of advanced technologies in modern production systems is the main trend of development and technological progress in many industrial sectors. It is due to the still growing trends of energy-saving and production quality enhancement. Wherever in the production process, the phase mixture is transported and it is not optimal or not economical, there is a need to develop a system which would be able to prevent any construction disaster, unexpected production line stopping or situation where for reasons of bad flow parameters, the final product is defective. This paper studies various sensors, measurement techniques and computer methods for signal processing and analysis to diagnose and control two-phase flows. Due to the possibility that the invasive measurement disturbs the process and changes it parameters and behaviour especially in the location just after the measurement point and simultaneously does not provide any information about these changes it is unreliable for the diagnosis or control. Therefore, the non-invasive techniques commonly used for measurement of flows parameters are described. Depending on the industrial demands, many applications examples for non-invasive two-phase flows measurement and monitoring are given. This description for identifying the flow parameters is divided into features categories of this phenomenon as void fraction distribution, velocity profile and flow regime. However, from these methods the high accuracy and short processing time are expected. The continued observation and monitoring of the process deliver knowledge about the dynamic states of the flow to control it more efficiently. Therefore, the development of advanced process control is one of the most important challenges to keep the flow regime on the given level and for instant and long-term energy saving, quality improvement. [ABSTRACT FROM AUTHOR]

Objective: This paper introduces a primer in the health care practice, namely a mathematical model and methodology for detecting and analysing nociceptor stimulation followed by related tissue memory effects. Methods: Noninvasive nociceptor stimulus protocol and prototype device for measuring bioimpedance is provided. Various time instants, sensor location, and stimulus train have been analysed. Results: The method and model indicate that nociceptor stimulation perceived as pain in awake healthy volunteers is noninvasively detected. The existence of a memory effect is proven from data. Sensor location had minimal effect on detection level, while day-to-day variability was observed without being significant. Conclusion: Following the experimental study, the model enables a comprehensive management of chronic pain patients, and possibly other analgesia, or pain related regulatory loops. Significance: A device and methodology for noninvasive for detecting nociception stimulation have been developed. The proposed method and models have been validated on healthy volunteers. [ABSTRACT FROM AUTHOR]