Journal of Medical and Biological Engineering

PURPOSE: Kretschmann-configuration has been used as a subwavelength framework to detect tiny ‎alterations of the refractive index of biomaterials. However, most of the theoretical assessment of such configuration ‎is usually based on the plane wave excitation transfer matrix method (TMM) of prism-‎coupled to thin metal film supporting plasmonic modes. Accordingly, a better theoretical framework ‎than the plane wave approximation is indispensable for reliable and accurate assessments and ‎simulations...

PURPOSE: To evaluate the classification performance of structured report features, radiomics, and machine learning (ML) models to differentiate between Coronavirus Disease 2019 (COVID-19) and other types of pneumonia using chest computed tomography (CT) scans. METHODS: Sixty-four COVID-19 subjects and 64 subjects with non-COVID-19 pneumonia were selected. The data was split into two independent cohorts: one for the structured report, radiomic feature selection and model building ( n  = 73), and another for model validation ( n  = 55)...

PURPOSE: Coronavirus 2019 (COVID-19) had major social, medical, and economic impacts globally. The study aims to develop a deep-learning model that can predict the severity of COVID-19 in patients based on CT images of their lungs. METHODS: COVID-19 causes lung infections, and qRT-PCR is an essential tool used to detect virus infection. However, qRT-PCR is inadequate for detecting the severity of the disease and the extent to which it affects the lung. In this paper, we aim to determine the severity level of COVID-19 by studying lung CT scans of people diagnosed with the virus...

Three-dimensional (3D) ultrasound localization microscopy (ULM) using a 2-D matrix probe and microbubbles (MBs) has been recently proposed to visualize microvasculature beyond the ultrasound diffraction limit in three spatial dimensions. However, 3D ULM suffers from several limitations: (1) high system complexity due to numerous channel counts, (2) complex MB flow dynamics in 3D, and (3) extremely long acquisition time. To reduce the system complexity while maintaining high image quality, we used a sub-aperture process to reduce received channel counts...

PURPOSE: In this paper, a new automated procedure based on deep learning methods for schizophrenia diagnosis is presented. METHODS: To this aim, electroencephalogram signals obtained using a 32-channel helmet are prominently used to analyze high temporal resolution information from the brain. By these means, the data collected is employed to evaluate the class likelihoods using a neuronal network based on radial basis functions and a fuzzy means algorithm. RESULTS: The results obtained with real datasets validate the high accuracy of the proposed classification method...

Purpose: Depression is a common mental illness worldwide and has become an important public health problem. The current clinical diagnosis of depression mainly relies on the doctor's experience and subjective diagnosis, which results in the low diagnostic efficiency and insufficient objectivity of diagnostic results. Therefore, establishing a physiological and psychological model for computer-aided diagnosis is an urgent task. In order to solve the above problems, this article uses a convolutional neural network (CNN) to identify depression based on electrocardiogram (ECG)...

Purpose: Human respiratory aerosols may have important implications for transmission of pathogens. The study of aerosol production during vigorous breathing activities such as exercise is limited. In particular, data on aerosol production during cardiopulmonary exercise testing (CPET) are lacking. Methods: In this pilot project, we used a high-powered, pulsed Nd:YAG laser to illuminate a region of interest in front of two healthy adult subjects during CPET. Subjects exercised to the point of respiratory compensation...

Purpose: Respiratory rate can provide auxiliary information on the physiological changes within the human body, such as physical and emotional stress. In a clinical setup, the abnormal respiratory rate can be indicative of the deterioration of the patient's condition. Most of the existing algorithms for the estimation of respiratory rate using photoplethysmography (PPG) are sensitive to external noise and may require the selection of certain algorithm-specific parameters, through the trial-and-error method...

Purpose: Image registration is important in medical applications accomplished by improving healthcare technology in recent years. Various studies have been proposed in medical applications, including clinical track of events and updating the treatment plan for radiotherapy and surgery. This study presents a fully automatic registration system for chest X-ray images to generate fusion results for difference analysis. Using the accurate alignment of the proposed system, the fusion result indicates the differences in the thoracic area during the treatment process...

Purpose: This study aimed to develop and evaluate the feasibility and preliminary efficiency of a methodology to measure the mindfulness state using a wearable device ("Cap") capable of monitoring students' levels of full attention by means of real-time measured heart rate variability (HRV). Methods: The device was developed to export the data to the user's smartphone via Bluetooth, which in turn stores the securely accessible data in the cloud. The autonomous wearable device consists of electronic boards of the Arduino platform that detect the period in milliseconds between two subsequent referential R peaks of the QRS complex wave through infrared oxygenation sensor...

Purpose: Sleep is an important human activity. Comfortable sensing and accurate analysis in sleep monitoring is beneficial to many healthcare and medical applications. From 2020, owing to the COVID‑19 pandemic that spreads between people when they come into close physical contact with one another, the willingness to go to hospital for receiving care has reduced; care-at-home is the trend in modern healthcare. Therefore, a home-use and real-time sleep-staging system is developed in this paper...

Purpose: In early 2020, the world is amid a significant pandemic due to the novel coronavirus disease outbreak, commonly called the COVID-19. Coronavirus is a lung infection disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 virus (SARS-CoV-2). Because of its high transmission rate, it is crucial to detect cases as soon as possible to effectively control the spread of this pandemic and treat patients in the early stages. RT-PCR-based kits are the current standard kits used for COVID-19 diagnosis, but these tests take much time despite their high precision...

Purpose: In this paper, the transfer learning method has been implemented to chest X-ray (CXR) and computed tomography (CT) bio-images of diverse kinds of lungs maladies, including CORONAVIRUS 2019 (COVID-19). COVID-19 identification is a difficult assignment that constantly demands a careful analysis of a patient's clinical images, as COVID-19 is found to be very alike to pneumonic viral lung infection. In this paper, a transfer learning model to accelerate prediction processes and to assist medical professionals is proposed...

Purpose: Anxiety disorder is one of the psychiatric disorders that involves extreme fear or worry, which can change the balance of chemicals in the brain. To the best of our knowledge, the evaluation of anxiety state is still based on some subjective questionnaires and there is no objective standard assessment yet. Unlike other methods, our approach focuses on study the neural changes to identify and classify the anxiety state using electroencephalography (EEG) signals. Methods: We designed a closed neurofeedback experiment that contains three experimental stages to adjust subjects' mental state...

Purpose: The positive end-expiratory pressure (PEEP) level with best respiratory system compliance (Crs) is frequently used for PEEP selection in acute respiratory distress syndrome (ARDS) patients. On occasion, two similar best Crs (where the difference between the Crs of two PEEP levels is < 1 ml/cm H2 O) may be identified during decremental PEEP titration. Selecting PEEP under such conditions is challenging. The aim of this study was to provide supplementary rationale for PEEP selection by assessing the global and regional ventilation distributions between two PEEP levels in this situation...

PURPOSE: Electrocardiogram (ECG) is one of the most essential tools for detecting heart problems. Till today most of the ECG records are available in paper form. It can be challenging and time-consuming to manually assess the ECG paper records. Hence, automated diagnosis and analysis are possible if we digitize such paper ECG records. METHODS: The proposed work aims to convert ECG paper records into a 1-D signal and generate an accurate diagnosis of heart-related problems using deep learning...

Purpose: There is an annual incidence of 50,000 glioma cases in Europe. The optimal treatment strategy is highly personalised, depending on tumour type, grade, spatial localization, and the degree of tissue infiltration. In research settings, advanced magnetic resonance imaging (MRI) has shown great promise as a tool to inform personalised treatment decisions. However, the use of advanced MRI in clinical practice remains scarce due to the downstream effects of siloed glioma imaging research with limited representation of MRI specialists in established consortia; and the associated lack of available tools and expertise in clinical settings...

Purpose: The purpose of this study is to quantify the motion dynamics of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Methods: Three physical models of Newton's and Stokes's laws with(out) air resistance in the calm air are used to determine the falling time and velocity regimes of SARS-CoV-2 with(out) a respiratory water droplet of 1 to 2000 micrometers (µm) in diameter of an infected person of 0.5 to 2.6 m in height. Results: The horizontal distance travelled by SARS-CoV-2 in free fall from 1...

Purpose: To improve the three dimensional (3D) and two dimensional (2D) image correlation and differentiation of 3D endoluminal lesions in the traditional surface rendering (SR) computed tomographic endoscopy (CTE), a target gray level mapping (TGM) technique is developed and applied to computed tomographic colonography (CTC) in this study. Methods: A study of sixty-two various endoluminal lesions from thirty patients (13 males, 17 females; age range 31-90 years) was approved by our institutional review board and evaluated retrospectively...

Purpose: Hospitalization at Home (HaH) has proven to be more efficient and effective than conventional one, but it also requires a higher number of resources and specialised personnel. Information technologies can make this process scalable and allow physicians and nurses to deliver remote healthcare services for patients hospitalized at home. However, a correct and satisfactory usage of technology requires an adequate training of professionals and patients. This paper describes a new model for training healthcare professionals on managing remote ICT-based services for Hospitalization at Home...