Journal of Medical Signals and Sensors
Volume:4 Issue: 4, Oct-Dec 2014

The purpose of this study was to estimate the torque from high‑density surface electromyography signals of biceps brachii, brachioradialis, and the medial and lateral heads of triceps brachii muscles during moderate‑to‑high isometric elbow flexion‑extension. The elbow torque was estimated in two following steps: First, surface electromyography (EMG) amplitudes were estimated using principal component analysis, and then a fuzzy model was proposed to illustrate the relationship between the EMG amplitudes and the measured torque signal. A neuro‑fuzzy method, with which the optimum number of rules could be estimated, was used to identify the model with suitable complexity. Utilizing the proposed neuro‑fuzzy model, the clinical interpretability was introduced; contrary to the previous linear and nonlinear black‑box system identification models. It also reduced the estimation error compared with that of the most recent and accurate nonlinear dynamic model introduced in the literature. The optimum number of the rules for all trials was 4 ± 1, that might be related to motor control strategies and the % variance accounted for criterion was 96.40 ± 3.38 which in fact showed considerable improvement compared with the previous methods. The proposed method is thus a promising new tool for EMG‑Torque modeling in clinical applications.

A cochlear implant is an implanted electronic device used to provide a sensation of hearing to a person who is hard of hearing. The cochlear implant is often referred to as a bionic ear. This paper presents an undecimated wavelet‑based speech coding strategy for cochlear implants, which gives a novel speech processor. The undecimated wavelet packet transform (UWPT) is computed like the wavelet packet transform except that it does not down‑sample the output at each level. The speech data used for the current study consists of 30 consonants, sampled at 16 ksps. The performance of our proposed UWPT method was compared to that of infinite impulse response (IIR) filter in terms of mean opinion score (MOS), short‑time objective intelligibility (STOI) measure and segmental signal‑to‑noise ratio (SNR). Undecimated wavelet had better segmental SNR in about 96% of the input speech data. The MOS of the proposed method was twice in comparison with that of the IIR filter‑bank. The statistical analysis revealed that the UWT‑based N‑of‑M strategy significantly improved the MOS, STOI and segmental SNR (P < 0.001) compared with what obtained with the IIR filter‑bank based strategies. The advantage of UWPT is that it is shift‑invariant which gives a dense approximation to continuous wavelet transform. Thus, the information loss is minimal and that is why the UWPT performance was better than that of traditional filter‑bank strategies in speech recognition tests. Results showed that the UWPT could be a promising method for speech coding in cochlear implants, although its computational complexity is higher than that of traditional filter‑banks

The repetitious nature of propelling a wheelchair has been associated with the high incidence of injury among manual wheelchair users (MWUs), mainly in the shoulder, elbow and wrist. Recent literature has found a link between handrim biomechanics and risk of injury to the upper extremity. The valid measurement of three‑dimensional net joint forces and torques, however, can lead to a better understanding of the mechanisms of injury, the development of prevention techniques, and the reduction of serious injuries to the joints. In this project, an instrumented wheel system was developed to measure the applied loads dynamically by the hand of the user and the angular position of the wheelchair user’s hand on the handrim during the propulsion phase. The system is composed of an experimental six‑axis load cell, and a wireless eight channel data logger mounted on a wheel hub. The angular position of the wheel is measured by an absolute magnetic encoder. The angular position of the wheelchair user’s hand on the handrim during the propulsion phase (φ) or point of force application (PFA) is calculated by means of a new‑experimental method using 36 pairs of infrared emitter/receiver diodes mounted around the handrim. In this regard, the observed data extracted from an inexperienced able‑bodied subject pushed a wheelchair with the instrumented handrim are presented to show the output behavior of the instrumented handrim. The recorded forces and torques were in agreement with previously reported magnitudes. However, this paper can provide readers with some technical insights into possible solutions for measuring the manual wheelchair propulsion biomechanical data.

The aim of this study is to provide a control software system, based on Monte Carlo simulation, and calculations of dosimetric parameters of standard and wedge radiation fi elds, using a Monte Carlo method. GATE version 6.1 (OpenGATE Collaboration), was used to simulate a compact 6 MV linear accelerator system. In order to accelerate the calculations, the phase-space technique and cluster computing (Condor version 7.2.4, Condor Team, University of Wisconsin–Madison) were used. Dosimetric parameters used intreatment planning systems for the standard and wedge radiation fi elds (10 cm × 10 cm to 30 cm × 30 cm and a 60° wedge), including the percentage depth dose and dose profi les, were measured by both computational and experimental methods. Gamma index was applied to compare calculated and measured results with 3%/3 mm criteria. Gamma index was applied to compare calculated and measured results. Almost all calculated data points have satisfi ed gamma index criteria of 3% to 3 mm. Based on the good agreement between calculated and measured results obtained for various radiation fi elds in this study, GATE may be used as a useful tool for quality control or pretreatment verifi cation procedures in radiotherapy.

Shape and movement features of sperms are important parameters for infertility study and treatment. In this article, a new method is introduced for characterizing sperms in microscopic videos. In this method, first a hypothesis framework is defined to distinguish sperms from other particles in captured video. Then decision about each hypothesis is done in following steps: Selecting some primary regions as candidates for sperms by watershed‑based segmentation, pruning of some false candidates during successive frames using graph theory concept and finally confirming correct sperms by using their movement trajectories. Performance of the proposed method is evaluated on real captured images belongs to semen with high density of sperms. The obtained results show the proposed method may detect 97% of sperms in presence of 5% false detections and track 91% of moving sperms. Furthermore, it can be shown that better characterization of sperms in proposed algorithm doesn’t lead to extracting more false sperms compared to some present approaches

In order to distinguish between benign and malignant types of pigmented skin lesions, computerized procedures have been developed for images taken by different equipment that the most available one of them is conventional digital cameras. In this research, a new procedure to detect malignant melanoma from benign pigmented lesions using macroscopic images is presented. The images are taken by conventional digital cameras with spatial resolution higher than one megapixel and by considering no constraints and special conditions during imaging. In the proposed procedure, new methods to weaken the effect of nonuniform illumination, correction the effect of thick hairs and large glows on the lesion and also, a new threshold‑based segmentation algorithm are presented. 187 features representing asymmetry, border irregularity, color variation, diameter and texture are extracted from the lesion area and after reducing the number of features using principal component analysis (PCA), lesions are determined as malignant or benign using support vector machine classifier. According to the dermatologist diagnosis, the proposed processing methods have the ability to detect lesions area with high accuracy. The evaluation measures of classification have indicated that 13 features extracted by PCA method leads to better results than all of the extracted features. These results are 82.2% of accuracy, 77% of sensitivity and 86.93% of specificity. The proposed method may help dermatologists to detect the malignant lesions in the primary stages due to the minimum constraints during imaging, the ease of usage by the public and nonexperts, and high accuracy in detection of the lesion type.

Microarray data have an important role in identification and classification of the cancer tissues. Having a few samples of microarrays in cancer researches is always one of the most concerns which lead to some problems in designing the classifiers. For this matter, preprocessing gene selection techniques should be utilized before classification to remove the noninformative genes from the microarray data. An appropriate gene selection method can significantly improve the performance of cancer classification. In this paper, we use selective independent component analysis (SICA) for decreasing the dimension of microarray data. Using this selective algorithm, we can solve the instability problem occurred in the case of employing conventional independent component analysis (ICA) methods. First, the reconstruction error and selective set are analyzed as independent components of each gene, which have a small part in making error in order to reconstruct new sample. Then, some of the modified support vector machine (υ‑SVM) algorithm sub‑classifiers are trained, simultaneously. Eventually, the best sub‑classifier with the highest recognition rate is selected. The proposed algorithm is applied on three cancer datasets (leukemia, breast cancer and lung cancer datasets), and its results are compared with other existing methods. The results illustrate that the proposed algorithm (SICA + υ‑SVM) has higher accuracy and validity in order to increase the classification accuracy. Such that, our proposed algorithm exhibits relative improvements of 3.3% in correctness rate over ICA + SVM and SVM algorithms in lung cancer dataset.

Multileaf collimator (MLC) is among the radiation field shaping systems used for conformal radiotherapy and intensity modulation radiation therapy techniques. The MLC system that has been designed and fabricated in this study includes 52 leaves, 52 stepper motors, 2 DC motors, 16 programmable logic controllers (PLCs) and one human machine interface (HMI). This system can be mounted on conventional linear accelerators (linac) as an add‑on accessory. The 52 leaves are mounted on two carriages that are moved independently. The leaves sequence acquired from the image processing of computed tomography images is used to arrange leaves. This sequence is saved in a text file. The leaves are arranged by HMI and labVIEW. Using HMI it is possible to test the operation of PLCs and manually enter the numerical values of the leaves edges. An executable file is developed by labVIEW program, which is graphically user interfaced between the operator and the MLC control system. The projected width of each leaf on the isocenter accelerator (usually at 100 cm from the source) is 10 mm. The positioning accuracy of each leaf is approximately 1.4 mm.