EEG-based brain-computer interface methods with the aim of rehabilitating advanced stage ALS patients.

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease that leads to progressive muscle weakness and paralysis, ultimately resulting in the loss of ability to communicate and control the environment. EEG-based Brain-Computer Interface (BCI) methods have shown promise in providing communication and control with the aim of rehabilitating ALS patients. In particular, P300-based BCI has been widely studied and used for ALS rehabilitation. Other EEG-based BCI methods, such as Motor Imagery (MI) based BCI and Hybrid BCI, have also shown promise in ALS rehabilitation. Nonetheless, EEG-based BCI methods hold great potential for improvement. This review article introduces and reviews FFT, WPD, CSP, CSSP, CSP, and GC feature extraction methods. The Common Spatial Pattern (CSP) is an efficient and common technique for extracting data properties used in BCI systems. In addition, Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Neural Networks (NN), and Deep Learning (DL) classification methods were introduced and reviewed. SVM is the most appropriate classifier due to its insensitivity to the curse of dimensionality. Also, DL is used in the design of BCI systems and is a good choice for BCI systems based on motor imagery with big datasets. Despite the progress made in the field, there are still challenges to overcome, such as improving the accuracy and reliability of EEG signal detection and developing more intuitive and user-friendly interfaces By using BCI, disabled patients can communicate with their caregivers and control their environment using various devices, including wheelchairs, and robotic arms.

Electroencephalography (EEG)-based Brain-Computer Interface (BCI) methods have shown promise in providing communication and control for Amyotrophic Lateral Sclerosis (ALS) patients.EEG constitutes the most significant input in BCIs and can be successfully used in the neuro-rehabilitation of patients with stroke symptoms and amyotrophic lateral sclerosis.EEG based BCIs have the potential to provide a means of communication and control for individuals with severe disabilities.a variety of EEG-based BCI methods have been developed with the aim of rehabilitating disabled patients.

A Compact and Lightweight Rehabilitative Exoskeleton to Restore Grasping Functions for People with Hand Paralysis.

Millions of individuals suffer from upper extremity paralysis caused by neurological disorders including stroke, traumatic brain injury, or spinal cord injury. Robotic hand exoskeletons can substitute the missing motor control and help restore the functions in daily operations. However, most of the hand exoskeletons are bulky, stationary, and cumbersome to use. We have modified a recent existing design (Tenoexo) to prototype a motorized, lightweight, fully wearable rehabilitative hand exoskeleton by combining rigid parts with a soft mechanism capable of producing various grasps needed for the execution of daily tasks. Mechanical evaluation of our exoskeleton showed that it can produce fingertip force up to 8 N and can cover 91.5° of range of motion in just 3 s. We further tested the performance of the developed robotic exoskeleton in two quadriplegics with chronic hand paralysis and observed immediate success on independent grasping of different daily objects. The results suggested that our exoskeleton is a viable option for hand function assistance, allowing patients to regain lost finger control for everyday activities.

2D Statistical Lung Shape Analysis Using Chest Radiographs: Modelling and Segmentation.

Accurate information of the lung shape analysis and its anatomical variations is very noticeable in medical imaging. The normal variations of the lung shape can be interpreted as a normal lung. In contrast, abnormal variations of the lung shape can be a result of one of the pulmonary diseases. The goal of this study is twofold: (1) represent two lung shape models which are different at the reference points in registration process considering to show their impact on estimating the inter-patient 2D lung shape variations and (2) using the obtained models in lung field segmentation by utilizing active shape model (ASM) technique. The represented models which showed the inter-patient 2D lung shape variations in two different forms are fully compared and evaluated. The results show that the models along with standard principal component analysis (PCA) can be able to explain more than 95% of total variations in all cases using only first 7 principal component (PC) modes for both lungs. Both models are used in ASM-based segmentation technique for lung field segmentation. The segmentation results are evaluated using leave-one-out cross validation technique. According to the experimental results, the proposed method has average dice similarity coefficient of 97.1% and 96.1% for the right and the left lung, respectively. The results show that the proposed segmentation method is more stable and accurate than other model-based techniques to inter-patient lung field segmentation.

Contour-based lung shape analysis in order to tuberculosis detection: modeling and feature description.

Statistical shape analysis of lung is a reliable alternative method for diagnosing pulmonary diseases such as tuberculosis (TB). The 2D contour-based lung shape analysis is investigated and developed using Fourier descriptors (FDs). The proposed 2D lung shape analysis is carried out in threefold: (1) represent the normal and the abnormal (i.e. pulmonary tuberculosis (PTB)) lung shape models using Fourier descriptors modeling (FDM) framework from chest X-ray (CXR) images, (2) estimate and compare the 2D inter-patient lung shape variations for the normal and abnormal lungs by applying principal component analysis (PCA) techniques, and (3) describe the optimal type of contour-based feature vectors to train a classifier in order to detect TB using one publicly available dataset-namely the Montgomery dataset. Since almost all of the previous works in lung shape analysis are content-based analysis, we proposed contour-based lung shape analysis for statistical modeling and feature description of PTB cases. The results show that the proposed approach is able to explain more than 95% of total variations in both of the normal and PTB cases using only 6 and 7 principal component modes for the right and the left lungs, respectively. In case of PTB detection, using 138 lung cases (80 normal and 58 PTB cases), we achieved the accuracy (ACC) and the area under the curve (AUC) of 82.03% and 88.75%, respectively. In comparison with existing state-of-art studies in the same dataset, the proposed approach is a very promising supplement for diagnosis of PTB disease. The method is robust and valuable for application in 2D automatic segmentation, classification, and atlas registration. Moreover, the approach could be used for any kind of pulmonary diseases. Graphical abstract Contour-based lung shape analysis in order to detect tuberculosis: modeling and feature description.

Early diagnosis of skin cancer by ultrasound frequency analysis.

The diagnosis of cancer by modern computer tools, at the very first stages of the incident, is a very important issue that has involved many researchers. In the meantime, skin cancer is a great deal of research because many people are involved with it. The purpose of this paper is to introduce an innovative method based on tissue frequency analyzes to obtain the accurate and real-time evaluation of skin cancers. According to the Biological resonance theory, body cells have natural and unique frequencies based on their biological fluctuations, which, if the structure, profile and cellular status change, its frequency also varies. This concept and theory is considered as the basis for analyzing skin tissue health in the proposed method. Reflected ultrasound waves from tissue have been processed and studied based on frequency analysis as a new method for early detection and diagnosis of accurate location and type of skin diseases. The developed algorithm was approved through 400 patients from CRED; its ability to evaluate benign and malignant skin lesions was shown (AUC = 0.959), with comparable clinical precision; as for the selected threshold, sensitivity, and specificity were 93.8% and 97.3%, respectively. Therefore, this method can detect skin malignancy with an accurate, noninvasive and real-time procedure.

Fast Padé transform for increasing the signal to noise ratio of spectra provided by STEAM pulse sequence.

BACKGROUND/OBJECTIVE: There are two routine pulse-sequences for single voxel spectroscopy (SVS), point resolved spectroscopy (PRESS) and stimulated echo acquisition mode (STEAM). Although STEAM has several advantages in comparison to PRESS, signal/noise ratio (SNR) superiority of PRESS makes it the first choice for SVS. Application of fast Padé transform (FPT) instead of Fast Furrier transform (FFT) might increase the SNR of the signal produced by STEAM pulse-sequence and therefore allows the benefits of its advantages. We aimed to evaluate and compare the noise root mean square (RMS) and SNR provided by STEAM pulse-sequence using both FPT and FFT. MATERIALS AND METHOD: A gelatin-based phantom was constructed in a 19-cm acrylic cylinder. The phantom had two normal/tumoral parts. The SVS was performed using a 3T MRI scanner. STEAM pulse-sequence were used with the following parameters: TR = 2000 ms, TM = 10 ms, and three TEs of 20, 135 and 270 ms with two data-points of 1024 and 512 and voxel-size of 1 cm3. The raw data were extracted and processed using both FFT and FPT estimators to produce the spectrum. The noise RMS and SNR of Cho and Cr metabolites were assessed. RESULTS: According to the results, noise RMS of spectra provided by FPT were decreased between 3619.01-14252.94% in comparison to FFT (p< 0.00001). The SNR of Cr1 and Cho peaks of the spectra provided by FPT were increased more than 96.80 and 97.18, respectively (0.00006

Cell damaging by irradiating non-thermal plasma to the water: Mathematical modeling of chemical processes.

Recently non-thermal plasma (NTP) is applied for many therapeutic applications. By NTP irradiating to the tissues or cell-lines, the water molecules (H2O) would be also activated leading to generate hydrogen peroxide (H2O2). By irradiating plasma to bio-solution, its main output including vacuum UV to UV causes the photolysis of H2O leading to generate hydroxyl (OH) molecules in couple forms with ability to convert to H2O2. Additionally, other plasma's output the oxygen atoms could also penetrate under the liquid's surface and react with H2O to generate H2O2. In NTP applications for killing unwanted-cells of microorganisms (e.g. sterilization) or cancerous tissues, the H2O2 molecule is the main reactive species for cell death via inducing DNA damage in mammalian cells. In this paper we proposed a mathematical model for NTP application describing the formation of hydroxyls in the bio solution and other subsequent reactions leading to DNA damage in vitro. The instant concentrations of the OH and H2O2, the main species for DNA oxidation were obtained and investigated in this simulation. In order to validate the model, the cellular response to NTP stimulation was compared with some experimental findings from viewpoint of DNA damage to show the significant consistency.

Inter-Patient Modelling of 2D Lung Variations from Chest X-Ray Imaging via Fourier Descriptors.

Detailed knowledge of anatomical lung variation is very important in medical image processing. Normal variations of lung consistent with the maintenance of pulmonary health and abnormal lung variations can be as a result of a pulmonary disease. Inter-patient lung variations can be due to the several factors such as sex, age, height, weight and type of disease. This study tries to show the inter-patient lung variations by using one of the shape-based descriptions techniques which is called Fourier descriptors. Shape-based description is an important approach to construct an object according to its parametric values. A different types of techniques are reported in the literature that aim to represent objects based on their shapes; each of these techniques has its cons and pros. Fourier descriptors, a simple yet powerful technique, has interesting properties such as rotational, scale, and translational invariance and these are powerful features for the recognition of two-dimensional connected shapes. In this paper, we use 380 CXR (Chest X-ray) images as a training set to construct the statistical mean model of lung contour. For modelling, the first step is evaluation of lung contour approximation and characterization to get the good spatial and frequency resolution. In the second step, all of the lung contours registered to show the variation and make a mean shape (i.e. lungs). And the final step is calculating the dispersion (i.e. covariance matrix) and analyzing by principle components. The proposed technique used to create the inter-patient statistical model and provide statistical parameters for application in segmentation, classification, 2D atlas based registration, etc. In this paper, we presented an approach for creating 2D modelling of human lungs from CXR image archives and reported some interesting statistical parameters to analysis the left and the right lung shape.

The Scatter Search Based Algorithm for Beam Angle Optimization in Intensity-Modulated Radiation Therapy.

This article introduces a new framework for beam angle optimization (BAO) in intensity-modulated radiation therapy (IMRT) using the Scatter Search Based Algorithm. The potential benefits of plans employing the coplanar optimized beam sets are also examined. In the proposed beam angle selection algorithm, the problem is solved in two steps. Initially, the gantry angles are selected using the Scatter Search Based Algorithm, which is a global optimization method. Then, for each beam configuration, the intensity profile is calculated by the conjugate gradient method to score each beam angle set chosen. A simulated phantom case with obvious optimal beam angles was used to benchmark the validity of the presented algorithm. Two clinical cases (TG-119 phantom and prostate cases) were examined to prepare a dose volume histogram (DVH) and determine the dose distribution to evaluate efficiency of the algorithm. A clinical plan with the optimized beam configuration was compared with an equiangular plan to determine the efficiency of the proposed algorithm. The BAO plans yielded significant improvements in the DVHs and dose distributions compared to the equispaced coplanar beams for each case. The proposed algorithm showed its potential to effectively select the beam direction for IMRT inverse planning at different tumor sites.

Upper Limb Neuromuscular Activities and Synergies Comparison between Elite and Nonelite Athletics in Badminton Overhead Forehand Smash.

This study is aimed at comparing muscle activations and synergies in badminton forehand overhead smash (BFOS) between elite and nonelite players to clarify how the central nervous system (CNS) controls neuromuscular synergy and activation to generate complex overhead movements. EMG of five upper limb muscles was recorded through surface electromyography (EMG) electrodes from twenty players. Athletics is divided into two groups: elite and nonelite. Eventually, nonnegative matrix factorization (NNMF) was utilized to the calculated electromyography signals for muscle synergy comparison. Similarities between elite and nonelite groups were calculated by scalar product method. Results presented that three muscles synergies could sufficiently delineate the found electromyography signals for elite and nonelite players. Individual muscle patterns were moderately to highly similar between elite and nonelite groups (between-group similarity range: 0.52 to 0.90). In addition, high similarities between groups were found for the shape of synergy activation coefficients (range: 0.85 to 0.89). These results indicate that the synergistic organization of muscle coordination during badminton forehand overhead smash is not profoundly affected by expertise.

Estimation of phase signal change in neuronal current MRI for evoke response of tactile detection with realistic somatosensory laminar network model.

Magnetic field generated by neuronal activity could alter magnetic resonance imaging (MRI) signals but detection of such signal is under debate. Previous researches proposed that magnitude signal change is below current detectable level, but phase signal change (PSC) may be measurable with current MRI systems. Optimal imaging parameters like echo time, voxel size and external field direction, could increase the probability of detection of this small signal change. We simulate a voxel of cortical column to determine effect of such parameters on PSC signal. We extended a laminar network model for somatosensory cortex to find neuronal current in each segment of pyramidal neurons (PN). 60,000 PNs of simulated network were positioned randomly in a voxel. Biot-savart law applied to calculate neuronal magnetic field and additional phase. The procedure repeated for eleven neuronal arrangements in the voxel. PSC signal variation with the echo time and voxel size was assessed. The simulated results show that PSC signal increases with echo time, especially 100/80 ms after stimulus for gradient echo/spin echo sequence. It can be up to 0.1 mrad for echo time = 175 ms and voxel size = 1.48 × 1.48 × 2.18 mm(3). With echo time less than 25 ms after stimulus, it was just acquired effects of physiological noise on PSC signal. The absolute value of the signal increased with decrease of voxel size, but its components had complex variation. External field orthogonal to local surface of cortex maximizes the signal. Expected PSC signal for tactile detection in the somatosensory cortex increase with echo time and have no oscillation.

Computational Modeling of Neuronal Current MRI Signals with Rat Somatosensory Cortical Neurons.

Magnetic field generated by active neurons has recently been considered to determine location of neuronal activity directly with magnetic resonance imaging (MRI), but controversial results have been reported about detection of such small magnetic fields. In this study, multiple neuronal morphologies of rat tissue were modeled to investigate better estimation of MRI signal change produced by neuronal magnetic field (NMF). Ten pyramidal neurons from layer II to VI of rat somatosensory area with realistic morphology, biophysics, and neuronal density were modeled to simulate NMF of neuronal tissue, from which effects of NMF on MRI signals were obtained. Neuronal current MRI signals, which consist of relative magnitude signal change (RMSC) and phase signal change (PSC), were at least three and one orders of magnitude less than a tissue with single neuron type, respectively. Also, a reduction in voxel size could increase signal alterations. Furthermore, with selection of zenith angle of external main magnetic field related to tissue surface near to 90°, RMSC could be maximized. This value for PSC would be 90° for small voxel size and zero degree for large ones.

Impact of various color LED flashlights and different lighting source to skin distances on the manual and the computer-aided detection of basal cell carcinoma borders.

BACKGROUND/AIMS: Quantitative analysis based on digital skin image has been proven to be helpful in dermatology. Moreover, the borders of the basal cell carcinoma (BCC) lesions have been challenging borders for the automatic detection methods. In this work, a computer-aided dermatoscopy system was proposed to enhance the clinical detection of BCC lesion borders. METHODS: Fifty cases of BCC were selected and 2000 pictures were taken. The lesion images data were obtained with eight colors of flashlights and in five different lighting source to skin distances (SSDs). Then, the image-processing techniques were used for automatic detection of lesion borders. Further, the dermatologists marked the lesions on the obtained photos. RESULTS: Considerable differences between the obtained values referring to the photographs that were taken at super blue and aqua green color lighting were observed for most of the BCC borders. It was observed that by changing the SSD, an optimum distance could be found where that the accuracy of the detection reaches to a maximum value. CONCLUSION: This study clearly indicates that by changing SSD and lighting color, manual and automatic detection of BCC lesions borders can be enhanced.

Measuring Left Ventricular Volumes in Two-Dimensional Echocardiography Image Sequence Using Level-set Method for Automatic Detection of End-Diastole and End-systole Frames.

BACKGROUND: Identifying End-Diastole (ED) and End-Systole (ES) frames is highly important in the process of evaluating cardiac function and measuring global parameters accurately, such as Ejection Fraction (EF), Cardiac Output (CO) and Stroke Volume. OBJECTIVES: The current study aimed to develop a new method based on measuring volume changes in Left Ventricle (LV) during cardiac cycle. MATERIAL AND METHODS: For this purpose, the Level Set method was used both in detecting endocardium border and quantifying cardiac function of all frames. RESULTS: Demonstrating LV volumes displays ED and ES frames and the volumes used in calculating the required parameters. CONCLUSIONS: Since ES and ED frames exist in iso-volumic phases of the cardiac cycle with minimum and maximum values of LV volume signals, such peaks can be utilized in finding related frames.

Evaluation of radiogallium-labeled, folate-embedded superparamagnetic nanoparticles in fibrosarcoma-bearing mice.

CONTEXT: Elevated expression of the folate receptor (FR) occurs in many human malignancies. Thus, folate targeting is widely utilized in drug delivery purposes specially using nano-radioactive agents. AIMS: In this work, we report production and biological evaluation of gallium-67 labeled superparamagnetic iron oxide nanoparticles, embedded by folic acid ( 67 Ga-SPION-folate) complex especially in tumor-bearing mice for tumor imaging studies. SETTINGS AND DESIGN: The structure of SPION-folate was confirmed by X-ray diffraction (XRD), transmission electron microscopy (TEM) and foureir transform infrared spectroscopy (FT-IR) analyses. The radiolabeled SPION-folate formation was confirmed by instant thin layer chromatography (ITLC). Tumor induction was performed by the use of poly-aromatic hydrocarbon injection in rodents as reported previously. MATERIALS AND METHODS: [ 67 Ga]-SPION-folate was shown to possess a particle size of ≈ 5-10 nm using instrumental methods followed by ITLC test. Biocompatibility of the compound was investigated using an 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay followed by stability tests and tumor accumulation studies in fibrosarcoma-bearing mice after subcutaneous (s.c.) application. STATISTICAL ANALYSIS USED: All values were expressed as mean ± standard deviation (mean ± SD) and the data were compared using Student t-test. Statistical significance was defined as P<0.05. RESULTS: [ 67 Ga]-SPION-folate was prepared by a modified co-precipitation method possessing a particle size of ≈ 5-10 nm using instrumental methods (>95% radiochemical purity). Biodistribution studies demonstrated tumor:blood, tumor:bone and tumor:muscle ratios of 4.23, 4.98 and 11.54 respectively after 24 h. CONCLUSIONS: Due to the nano-scale size and high-penetrative property of the developed folate-containing nano-complex, this system can be an interesting drug delivery modality with therapeutic applications and folate receptor-targeting behavior, while possessing paramagnetic properties for thermotherapy.

Radiological image enhancement by X-ray choppers.

A new scatter control technology consisting a pair of X-ray choppers is being developed to provide improved radiographic contrast and measure geometrical distribution of scattered photons. By placing the choppers (which are rotating by different angular velocities) in two sides of the static object in direction of X-rays, the beam is position-encoded by two frequencies f1 and f2 due to the chopping velocities. The chopped beams reaching to image detectors generate a dynamic image consisting blinking pixels, while some non-chopped beams provide constant gray level of pixels. By extracting the gray value varying with compound frequency f1+f2 or f1-f2, the correct pathways of the beam are really selected, which have no scatter; whilst other provided frequencies including zero, f1, and f2 are due to scattered radiations. Hence, after video capturing by a digital fluoroscopy and digital image processing, an image is obtained which has better contrast in a region under both choppers. Using an assembled prototype device for a constructed phantom showed significantly image improvement.

Noninvasive detection of coronary artery disease by arterio-oscillo-graphy.

Coronary artery disease (CAD) causes oscillations in peripheral arteries. Oscillations of the walls of the brachial arteries of 51 patients were recorded [together with the electrocardiogram (ECG)] by an accelerometer at different cuff pressures. By analyzing the energy of the oscillations in the 30-250 Hz band, 16 of 22 patients with CAD and 26 of 29 non-CAD subjects were classified correctly, independent of the ECG, and with no effect of heart murmurs.

Conceptual modeling of cardiovascular sounds.

In this paper, it is shown that the main source of mechanical energy of cardiovascular (CV) system i.e., rhythmic heart contraction is transformed to the oscillations of the CV walls and blood flow, and finally CV acoustical waves. These waves propagate through both blood flow (hemodynamical pathways) and tissues (viscoelastical pathways) toward the skin. Nonetheless, the CV walls could be assumed as the source of acoustical waves, since they act as the interface between blood flows and other tissues including skin. After obtaining the approximate accelerations of CV walls from pressure-flow (PF) models, we also needed to model the viscoelastical pathways until the skin. Some improvements on PF models were fulfilled to present small variations of blood pressure such as dicrotic notch. The turbulence occurrence was also noticed to and conceptually modeled. The total homomorphic model could conceptually show the relations of CV sounds with CV characterizations and tissue specifications. Thus, it could be helpful to assess CV system in order to diagnose CV diseases via CV sounds. The CV sounds recorded from the skin of any place (e.g., chest or arm) could be simulated via this model, if the hemodynamical and viscoelastical parameters especially for the region under that place are obtained.

Identification of brachial artery characteristic using a cuff for noninvasive detection of coronary artery disease.

How could a cuff cause a peripheral artery to enter its resonance mode? How could the arterial oscillations be used to evaluate the arteries and to diagnose coronary artery disease (CAD)? This paper answers. A conceptual model representing the role of cuff-artery connection to produce a step-like (sharpened) pressure stimulator is also introduced. The arterial dynamic response is recorded noninvasively in the form of arterio- oscillo-gram (AOG) via an accelerometer. Only, the big oscillatory parts of AOG are used to assess the arterial structure. Due to CAD correlation with peripheral arteriosclerosis, the CAD can also be diagnosed by analyzing AOG peaks. For every person of 51 samples including 22 CAD, 22 normal and 7 heart murmur (HM) patients, the mean of five largest peak durations is calculated. The more severity of CAD causes the less duration time. Hence, simply, by defining a threshold of 9.25 ms, two CAD and non-CAD groups were classified with accuracies of 77% (17/22), and 82% (17/22 for normal, and 7/7 for HM), respectively. This simple noninvasive method mainly aims the vascular characteristics evaluation, thus it does not have the usual limitations of other CAD detection methods.