Journal of Medical Signals and Sensors
Volume:10 Issue: 4, Oct-Dec 2020

The obstructive sleep apnea (OSA) detection has become a hot research topic because of the high risk of this disease. In this paper, we tested some powerful and low computational signal processing techniques for this task and compared their results with the recent achievements in OSA detection.

The Dual-tree complex wavelet transform (DT-CWT) is used in this paper to extract feature coefficients. From these coefficients, eight non-linear features are extracted and then reduced by the Multi-cluster feature selection (MCFS) algorithm. The remaining features are applied to the hybrid “K-means, RLS” RBF network which is a low computational rival for the Support vector machine (SVM) networks family. Results and

The results showed suitable OSA detection percentage near 96% with a reduced complexity of nearly one third of the previously presented SVM based methods.

A simple data collection approach based on electroencephalogram (EEG) measurements has been proposed in this study to implement a brain–computer interface, i.e., thought-controlled wheelchair navigation system with communication assistance.

The EEG signals are recorded for seven simple tasks using the designed data acquisition procedure. These seven tasks are conceivably used to control wheelchair movement and interact with others using any odd-ball paradigm. The proposed system records EEG signals from 10 individuals at eight-channel locations, during which the individual executes seven different mental tasks. The acquired brainwave patterns have been processed to eliminate noise, including artifacts and powerline noise, and are then partitioned into six different frequency bands. The proposed cross-correlation procedure then employs the segmented frequency bands from each channel to extract features. The cross‑correlation procedure was used to obtain the coefficients in the frequency domain from consecutive frame samples. Then, the statistical measures (“minimum,” “mean,” “maximum,” and “standard deviation”) were derived from the cross‑correlated signals. Finally, the extracted feature sets were validated through online sequential-extreme learning machine algorithm. Results and

The results of the classification networks were compared with each set of features, and the results indicated that μ (r) feature set based on cross-correlation signals had the best performance with a recognition rate of 91.93%.

This study presents a new and innovative experimental method, including software and its prerequisite instruments, to use image processing techniques for crown preparation analysis.

A platform was designed and constructed to take images from artificial teeth in different angles and directions and to process and analyze them by the proposed method to evaluate the quality and quantity of crown preparation. For each tooth, two series of images were taken from the artificial teeth before and after preparation, and image series were registered by two semi‑automated and automated methods to transform them into one coordinate system. Region of interest was segmented by user interaction, and tooth region was segmented by substeps such as transformation to hue, saturation, and value color space, edge detection, morphology operations, and contour extraction. Finally, the amount and angle of crown preparation were computed and compared with standard measures to evaluate the quality of crown preparation. The proposed method was applied to a local dataset collected from Isfahan University of Medical Sciences.

Difference between the angle of crown preparation computed by the proposed method and that of the experts showed a mean absolute error of 7.17°. The correlation between the segmented regions by the proposed method and those of the experts was also evaluated by the Intersection over Union (IOU) criterion. The best and worst performances achieved in cases by IOU were 0.94 and 0.76, respectively. Finally, the segmentation results of the proposed method indicated an average IOU of 0.89 in all images.

Students can use this method as an assessment tool in preclinical tooth preparation to compare their crown work with standard parameters.

In this paper, we have presented a new custom smart CMOS image sensor (CIS) for low power wireless capsule endoscopy.

The proposed new smart CIS includes a 256 × 256 current mode pixels array with a new on-chip adaptive neuro-fuzzy inference system that has been used to diagnosing bleeding images. We use a new pinned photodiode to realize the current mode of active pixels in the standard CMOS process. The proposed chip has been implemented in 0.18 µm CMOS 1P6M TSMC RF technology with a die area of 7 mm × 8 mm. Results and

A built‑in smart bleeding detection system on CIS leads to decrease in the RF transmitter power consumption near zero. The average power dissipation of the proposed smart CIS is 610 µW.

Spironolactone (SP) is a lipophilic aldosterone receptor antagonist that few studies have reported its effect on cardiac remodeling. In addition, fewer researches have considered its influence on cardiomyocyte viability and potential benefits for myocardial tissue remodeling.

In this study, stearic acid (SA) (solid lipid) and oleic acid (OA) (liquid lipid) were utilized to produce nanostructured lipid carries (NLCs) (various ratios of SA to OA and water amount, F1: 80:20 [30 ml water], F2: 80:20 [60 ml water], F3: 70:30 [30 ml water], and F4: 70:30 [60 ml water]) containing SP and their particle size, polydispersity index, zeta potential, entrapment efficiency, and release profile were measured. The purpose of encapsulating SP in NLCs was to provide a sustain release system. Meanwhile, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay with different concentrations of SP-loaded NLCs (SP-NLCs) was conducted to evaluate the cytotoxicity of the NLCs on rat myocardium cells (H9C2).

Increase of oil content to 10 wt% reduced the particle size from 486 nm (F1) to 205 nm (F2). Zeta potential of the samples at around −10 mV indicated their agglomeration tendency. After 48 h, SP-NLCs with the concentrations of 5 and 25 µM showed significant improvement in cell viability while the same amount of free SP‑induced cytotoxic effect on the cells. SP-NLCs with higher concentration (50 µM) depicted cytotoxic effect on H9C2 cells.

It can be concluded that 25 µM SP‑NLCs with sustain release profile had a beneficial effect on cardiomyocytes and can be used as a mean to improve cardiac tissue regeneration.

Intima, media, and adventitia are three layers of arteries. They have different structures and different mechanical properties. Damage to intima layer of arteries leads to an inflammatory response, which is usually the reason for atherosclerosis plaque formation. Atherosclerosis plaques mainly consist of smooth muscle cells and calcium. However, plaque geometry and mechanical properties change during time. Blood flow is the source of biomechanical stress to the plaques. Maximum stress that atherosclerosis plaque can burden before its rupture depends on fibrous cap thickness, lipid core, calcification, and artery stenosis. When atherosclerotic plaque ruptures, the blood would be in contact with coagulation factors. That is why plaque rupture is one of the main causes of fatality.

In this article, the coronary artery was modeled by ANSYS. First, fibrous cap thickness was increased from 40 µm to 250 µm by keeping other parameters constant. Then, the lipid pool percentage was incremented from 10% to 90% by keeping other parameters unchanged. Furthermore, for investigating the influence of calcium in plaque vulnerability, calcium was modeled in both agglomerated and microcalcium form.

It is proved that atherosclerosis plaque stress decreases exponentially as cap thickness increases. Larger lipid pool leads to more vulnerable plaques. In addition, the analysis showed maximum plaque stress usually increases in calcified plaque as compared with noncalcified plaque.

The plaque stress is dependent on whether calcium is agglomerated near the lumen or far from it. However, in both cases, the deposition of more calcium in calcified plaque reduces maximum plaque stress.

Feature reproducibility is a critical issue in quantitative radiomic studies. The aim of this study is to assess how radiographic radiomic textures behave against changes in phantom materials, their arrangements, and focal spot size.

A phantom with detachable parts was made using wood, sponge, Plexiglas, and rubber. Each material had 1 cm thickness and was imaged for consecutive time. The phantom also was imaged by change in the arrangement of its materials. Imaging was done with two focal spot sizes including 0.6 and 1.2 mm. All images were acquired with a digital radiography machine. Several texture features were extracted from the same size region of interest in all images. To assess reproducibility, coefficient of variation (COV), intraclass correlation coefficient (ICC), and Bland–Altman tests were used.

Results show that 59%, 50%, and 4.5% of all features are most reproducible (COV ≤5%) against change in focal spot size, material arrangements, and phantom’s materials, respectively. Results on Bland–Altman analysis showed that there is just a nonreproducible feature against change in the focal spot size. On the ICC results, we observed that the ICCs for more features are >0.90 and there were few features with ICC lower than 0.90.

We showed that radiomic textures are vulnerable against changes in materials, arrangement, and different focal spot sizes. These results suggest that a careful analysis of the effects of these parameters is essential before any radiomic clinical application.

Various factors effecting deposited energy and dose enhancement ratio (DER) in the simplified model of cell caused by the interaction of a cluster of gold nanoparticles (GNPs) with electron beams were assessed, and the results were compared with other sources through Geant4 Monte Carlo simulation toolkit.

The effect of added GNPs on the DNA strand breaks level, irradiated to electron, proton, and alpha beams, is assessed.

Presence of GNPs in the cell makes DER value more pronounced for low-energy photons rather than electron beam. Moreover, the results of DER values did not show any significant increase in absorbed dose in the presence of GNP for proton and alpha beam. Moreover, the results of DNA break with GNPs for proton and alpha beam were negligible. It is demonstrated that as the sizes of the GNPs increase, the DER is enlarged until a certain size for 40 keV photons, while there is no striking change for 50 keV electron beam when the size of the GNPs changes. The results indicate that although energy deposited in the cell for electron beam is more than low-energy photon, DER values are low compared to photon.

Larger GNPs do not show any preference over smaller ones when irradiated through electron beams. It is proved that GNPs do not significantly increase single‑strand breaks (SSBs) and double-strand breaks during electron irradiation, while there exists a direct relationship between SSB and energy