Journal of Medical Signals and Sensors
Volume:6 Issue: 2, Apr-Jun 2016

The prediction of the joint angle position, especially during tremor bursts, can be useful for detecting, tracking, and forecasting tremors. Thus, this research proposes a new model for predicting the wrist joint position during rhythmic bursts and inter‑burst intervals. Since a tremor is an approximately rhythmic and roughly sinusoidal movement, neural oscillators have been selected to underlie the proposed model. Two neural oscillators were adopted. Electromyogram (EMG) signals were recorded from the extensor carpi radialis and flexor carpi radialis muscles concurrent with the joint angle signals of a stroke subject in an arm constant‑posture. The output frequency of each oscillator was equal to the frequency corresponding to the maximum value of power spectrum related to the rhythmic wrist joint angle signals which had been recorded during a postural tremor. The phase shift between the outputs of the two oscillators was equal to the phase shift between the muscle activation of the wrist flexor and extensor muscles. The difference between the two oscillators’ output signals was considered the main pattern. Along with a proportional compensator, an adaptive neural controller has adjusted the amplitude of the main pattern in such a way so as to minimize the wrist joint prediction error during a stroke patient’s tremor burst and a healthy subject’s generated artificial tremor. In regard to the range of wrist joint movement during the observed rhythmic motions, a calculated prediction error is deemed acceptable.

Nowadays, the world is faced with diverse challenging issues which lead to the development of communities to discuss about the matter and provide solutions for them. Academic research centers are then established to puzzle out the raised questions with reliance on expert opinions and studies in response to the current prevailing needs.
Islamic Republic of Iran blessed with knowledgeable academic resources, is currently growing fast in research[1]. A great number of centers are already dedicated to research, commonly with the focus on a specific area. However, the real maturity in research centers demands accurate and precise definition of the goals and solidarity to approach the target. Such a mature center can be expected to deliver valuable products in a predetermined time. It is expected that designing a roadmap would be helpful in achieving such a maturity.

A multi‑parameter quantification method was implemented to quantify retinal vascular injuries in microscopic images of clinically relevant eye diseases. This method was applied to wholemount retinal trypsin digest images of diabetic Akita/, and bcl‑2 knocked out mice models. Five unique features of retinal vasculature were extracted to monitor early structural changes and retinopathy, as well as quantifying the disease progression. Our approach was validated through simulations of retinal images. Results showed fewer number of cells (P = 5.1205e‑05), greater population ratios of endothelial cell to pericytes (PC) (P = 5.1772e‑04; an indicator of PC loss), higher fractal dimension (P = 8.2202e‑05), smaller vessel coverage (P = 1.4214e‑05), and greater number of acellular capillaries (P = 7.0414e‑04) for diabetic retina as compared to normal retina. Quantification using the present method would be helpful in evaluating physiological and pathological retinopathy in a high‑throughput and reproducible manner.

In this paper, an efficient algorithm is proposed for detection of vertical root fractures (VRFs) in periapical (PA), and cone-beam computed tomography (CBCT) radiographs of nonendodontically treated premolar teeth. PA and CBCT images are divided into some sub-categories based on the fracture space between the two fragments as small, medium, and large for PAs and large for CBCTs. These graphics are first denoised using the combination of block matching 3-D filtering, and principle component analysis model. Then, we proposed an adaptive thresholding algorithm based on the modified Wellner model to segment the fracture and canal. Finally, VRFs are identified with a high accuracy through applying continuous wavelet transform on the segmented radiographs and choosing the most optimal value for sub-images based on the lowest interclass variance. Performance of the proposed algorithm is evaluated utilizing the different tested criteria. Results illustrate that the range of specificity deviations for PA and CBCT radiographs are 99.69 ± 0.22 and 99.02 ± 0.77, respectively. Furthermore, the sensitivity changes from 61.90 to 77.39 in the case of PA and from 79.54 to 100 in the case of CBCT. Based on our statistical evaluation, the CBCT imaging has the better performance in comparison with PA ones, so this technique could be a useful tool for clinical applications in determining the VRFs.

High‑intensity focused ultrasound (HIFU) is a novel treatment modality used by scientists and clinicians in the recent decades. This modality has had a great and significant success as a noninvasive surgery technique applicable in tissue ablation therapy and cancer treatment. In this study, radio frequency (RF) ultrasound signals were acquired and registered in three stages of before, during, and after HIFU exposures. Different features of RF time series signals including the sum of amplitude spectrum in the four quarters of the frequency range, the slope, and intercept of the best‑fit line to the entire power spectrum and the Shannon entropy were utilized to distinguish between the HIFU‑induced thermal lesion and the normal tissue. We also examined the RF data, frame by frame to identify exposure effects on the formation and characteristics of an HIFU thermal lesion at different time steps throughout the treatment. The results obtained showed that the spectrum frequency quarters and the slope and intercept of the best fit line to the entire power spectrum both increased two times during the HIFU exposures. The Shannon entropy, however, decreased after the exposures. In conclusion, different characteristics of RF time series signal possess promising features that can be used to characterize ablated and nonablated tissues and to distinguish them from each other in a quasi‑quantitative fashion.

The goal is assessing the diffusion magnetic resonance imaging (dMRI) method effi ciency in characterizing focal hepatic lesions (FHLs). About 28-FHL patients were studied in Radiology and Clinical Imaging Department of our University Hospital using 1.5 Tesla MRI system between January 2010 and June 2011. Patients underwent hepatic MRI consisting of dynamic T1- and T2-weighted imaging. The dMRI was performed with b-values of 200 s/mm2 and 600 s/mm2 . About 42 lesions measuring more than 1 cm were studied including the variation of the signal according to the b-value and the apparent diffusion coeffi cient (ADC). The diagnostic imaging reference was based on standard MRI techniques data for typical lesions and on histology after surgical biopsy for atypical lesions. About 38 lesions were assessed including 13 benign lesions consisting of 1 focal nodular hyperplasia, 8 angiomas, and 4 cysts. About 25 malignant lesions included 11 hepatocellular carcinoma, 9 hepatic metastases, 1 cholangiocarcinoma, and 4 lymphomas. dMRI of soft lesions demonstrated higher ADC of 2.26 ± 0.75 mm2 /s, whereas solid lesions showed lower ADC 1.19 ± 0.33 mm2 /s with signifi cant difference (P = 0.05). Discrete values collections were noticed. These results were correlated to standard MRI and histological fi ndings. Sensitivity of 93% and specifi city of 84% were found in diagnoses of malignant tumors with an ADC threshold of 1.6 × 10−3 mm2 /s. dMRI is important characterization method of FHL. However, it should not be used as single criteria of hepatic lesions malignity. MRI, clinical, and biological data must be correlated. Signifi cant difference was found between benign and solid malignant lesions without threshold ADC values. Hence, it is diffi cult to confi rm ADC threshold differentiating the lesion classifi cation.

Osseointegration has been the concern of implantology for many years. Researchers have used various ceramic coatings for this purpose; however, piezoelectric ceramics (e.g., barium titanate [BTO]) are a novel fi eld of interest. In this regard, BTO (BaTiO3 , BTO) coating was fabricated by electrophoretic deposition on Ti6Al4V medical alloy, using sol-gel-synthesized nanometer BTO powder. Structure and morphologies were studied using X-ray diffraction and scanning electron microscopy (SEM), respectively. Bioactivity response of coated samples while immersion in simulated body fl uid (SBF) was evaluated by SEM and inductively coupled plasma (ICP) analysis. Cell compatibility was also studied via 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium assay and SEM imaging. Results showed homogenous coating with cubic structure and crystallite size of about 41 nm. SEM images indicated apatite formation on the coating after 7 days of SBF immersion, and ICP analysis approved ions concentration decrement in SBF. Cells showed fl attened morphology in intimate contact with coating after 7 days of culture. Altogether, coated samples demonstrated appropriate bioactivity and biocompatibility.

A multiple colorimetric assay has been introduced to evaluate the proliferation and determination of survival fraction (SF) of irradiated cells. The estimation of SF based on the cell‑growth curve information is the major advantage of this assay. In this study, the utility of multiple‑MTS assay for the SF estimation of irradiated HT‑29 colon cancer cells, which were plated before irradiation, was evaluated. The SF of HT‑29 colon cancer cells under irradiation with 9 MV photon was estimated using multiple‑MTS assay and colony assay. Finally, the correlation between two assays was evaluated. Results showed that there are no significant differences between the SF obtained by two assays at different radiation doses (P > 0.05), and the survival curves have quite similar trends. In conclusion, multiple MTS‑assay can be a reliable method to determine the SF of irradiated colon cancer cells that plated before irradiation.