Biomedical Engineering: Applications, Basis and Communications

The objective of this paper is to classify Brain Computer Interfacing (BCI) competition III, dataset IIIA with low computational complexity and high classification accuracy rate. This study presents the investigation of self-filtering (SF) as a pre-processing technique and Wigner trispectrum as feature extraction technique followed by the proposed $K$-means clustering SVM (KC-SVM) classifier. KC-SVM is an improved form of classifier, which comprises KC-SVM with 10-fold cross validation technique. To analyze each stage of classification, different evaluation indexes of respective methods are considered. Substantial improvement on the performance of proposed classification method is scrutinized. Performance measurement accuracy 98.1%, Kappa coefficient 0.94, mutual information of feature vectors 0.14 and Fisher score 6.5 are achieved for considered dataset. In summary, this paper demonstrates that the classification accuracy of proposed classifier together with SF and Wigner–Ville Trispectrum (WT) satisfies the required criteria of classification.

Objective: The quantification of inter-segmental spine joint reaction forces during common workplace physical demands. Background: Many spine reaction force models have focused on the L5/S1 or L4/L5 joints to quantify the vertebral joint reaction forces. However, the L5/S1 or L4/L5 approach neglects most of the intervertebral joints. Methods: The current study presents a clinically applicable and noninvasive model which calculates the spinal joint reaction forces at six different regions of the spine. Subjects completed four ambulatory activities of daily living: level walking, obstacle crossing, stair ascent, and stair descent. Results: Peak joint spinal reaction forces were compared between tasks and spine regions. Differences existed in the bodyweight normalized vertical joint reaction forces where the walking (8.05$\pm$3.19N/kg) task had significantly smaller peak reaction forces than the stair descent (12.12$\pm$1.32N/kg) agreeing with lower extremity data comparing walking and stair descent tasks. Conclusion: This method appears to be effective in estimating the joint reaction forces using a segmental spine model. The results suggesting the main effect of peak reactions forces in the segmental spine can be influenced by task.

Recognition and compensation of undesired nonlinearity is one of the important subjects in the field of digital signal processing. The Volterra model is widely used for nonlinearity identification in practical applications. The current tendency in the digital systems design is the identification and compensation of unwanted nonlinearities. In this paper, we employed a nonlinear noise estimation approach for electroencephalogram (EEG) signal based on a combination of linear predictive coding (LPC) and Volterra filter that is a new and good way to estimate noise in EEG signal. We initially used LPC filter to estimate the noise present in EEG signal (correlated and uncorrelated noise) plus the uncorrelated portion of the signal (the part of the signal that has no linear relation to its past samples). After that, we employed nonlinear Volterra model to estimate the existing noise in EEG signal (correlated and uncorrelated noise). We show that by employing the cascade of LPC and Volterra filter, we can considerably improve the signal-to-noise ratio (SNR) in EEG signal by the ratio of at least 1.94. Also, we compared the simulation results to the case where we used just Volterra filter. In comparison with just Volterra filter, we have a significant increase in the SNR.

A major aim of gene therapy is the efficient and specific delivery of therapeutic gene into the desired target tissues. Development of reliable vectors is a major challenge in gene therapy. The aim of this study is to develop calcium phosphate nanoparticles as novel non-viral vectors for the gene delivery system. Calcium phosphate nanoparticles were prepared by water-in-oil microemulsion method with a water to surfactant molar ratio, Wo $=$ 2–10.

This paper studies the design and synthesis of ultra-low size, highly monodispersed DNA doped calcium phosphate nanoparticles of size around 100nm in diameter. The structure of DNA-calcium phosphate nanocomplex observed by TEM was displayed as a shell-like structure. This study used pEGFP as a reporter gene. The encapsulating efficiency to encapsulate DNA inside the nanoparticles was greater than 80%. In the MTT test, both calcium phosphate nanoparticles and DNA-calcium phosphate nanocomplex have no negative effect for 293T cells. By gel electrophoresis of free and entrapped pEGFP DNA, the DNA encapsulated inside the nanoparticles was protected from the external DNaseI environment. In vitro transfection studies in 293T cell-line, the DNA-calcium phosphate nanocomplex could be used safely to transfer the encapsulated DNA into the 293T cells and expression green fluorescent protein. The characteristic of DNA-calcium phosphate nanocomplex to deliver DNA belongs to slow release. The property of DNA-calcium phosphate nanocomplex was fit in the requirement of non-viral vectors for the gene delivery system.

Traditionally, gait analysis models the trunk as one rigid body segment. This approach has limitations; it does not capture all the movements of this area of the body throughout locomotion. Lower-extremity-gait kinematics do not routinely change in healthy non-elderly adults in different decades of life; however, it is unknown if trunk kinematics will be altered during different activities of daily living as a function of age. The purpose of this study was to determine if a previously validated multi-segmented trunk model would detect trunk movement variations in non-elderly healthy adults in different decades of life. Thirty-four non-elderly healthy adults in various decades of life (20–29 years, 30–39 years, 40–49 years, and 50–59 years) completed two tasks of ambulatory daily living (level walking and stair descent). Trunk maximum angle during the gait cycle, timing of the trunk maximum angle during the gait cycle and trunk range of motion were examined using analysis of variance procedures. Findings are that age group did not affect the trunk kinematics of individuals in different decades of life, but that may not represent the experiences of elderly individuals.

Decomposition of local field potential (LFP) signals with different oscillatory rhythms is useful for analysis of various neuronal activities in mice. In this paper, we first removed the power-line interference with high signal fidelity by using a notch filter with infinite impulse response. Next, we applied the ensemble empirical mode decomposition (EEMD) method to separate the LFP signal into low-frequency, Delta, Theta, Beta, Gamma, Ripple, and high-frequency oscillations, in the form of different intrinsic mode functions (IMFs). The LFP signal components with different frequency bands were identified and then reconstructed from the IMFs within the same frequency range by analyzing their power spectral ratios (PSRs). Then, normalized autocorrelation functions of the resting respiratory signal and the reconstructed Delta oscillations were computed to estimate the corresponding power spectral densities by means of the Fourier transform. The results of LFP signal decomposition and oscillatory rhythm reconstruction demonstrated the effectiveness of the EEMD and PSR analysis methods. The coherence analysis results indicate that the primary periodicity peak of the Delta LFP component is definitely linked to that of resting respiration in an awake mouse. Our major contribution is to establish a novel LFP signal separation and identification procedure by combining the EEMD method with appropriate parameter setting and the power spectral analysis approach.

A mechanical lung simulator is an important tool to simulate the severity of lung disease. In this paper, a lung simulator is proposed, which is composed of a glass bottle, a pressure sensor, copper wool, etc. Its working mechanism is based upon the ideal gas equation. The glass bottle simulates human lung, and copper wool is used to quickly keep gas temperature in the bottle stable. The main issue discussed is about how much copper wool is appropriate to approximate isothermal conditions when copper wool is uniformly placed in the lung simulator. Three aspects including (1) theoretical fluid analysis, computation, and derivation based upon the ideal gas equation; (2) three-dimensional geometric meshing and numerical simulation based upon the ANSYS FLUENT; and (3) the experiment reveals that copper wool corresponding to 2–3% by volume of the lung simulator is enough to quickly keep gas temperature in the lung simulator stable and to realize quasi-isothermal conditions.

Arteries in the upper limb play important roles in the circulation system of the human body. In particular, the radial artery has received considerable attention in traditional Chinese medicine for thousands of years. Here, a 3D model for the arm arteries has been created uncomplicated, in a Chinese adult’s left hand, from the magnetic resonance imaging data, using professional modeling software to restore the basic structure of the arm artery in human body, before being imported to Ansys software for simulation. Blood model has been only simulated, and using the blood density of constant parameter and viscosity using the Carreau fluid model, and using viscous-laminar model of Fluent to obtain the velocity profile, static pressure and shear stress in the brachial, interosseous, ulnar, radial and palmar arch arteries. In particular, the brachial and bifurcations have the high pressure and velocity profiles. The simulation results obtained here are also validated by those published in the literature and proved the ulnar artery prevails over the radial artery as a blood supplier to the vessels in the wrist and hand.