Biomedical Engineering: Applications, Basis and Communications

To determine the dynamic axial rotation movement of human upper extremity, we developed a combined skin- and scapula-based marker system in which the scapula motion was detected with a marker set attached to an intracortical pin on the acromion. The subject performed axial rotation with the arm in 5 different positions. The total rotation range varied greatly if the arm was in different position. The pattern of axial rotation of each segment also changed. The upper extremity rotates total 376° at 90° abduction and only 257° at full abduction. The forearm usually contributed about 140°, so the differences mainly came from the scapulothoracic and the glenohumeral joints. The scapulothoracic joint axially rotated 66° with the arm in backward extension while only rotated 19° with the arm in 90° forward flexion. The glenohumeral joint rotated maximally, 143° with the arm at 90° abduction, while minimally, 69° with the arm at maximal abduction.

In this study, we describe a modification of the conventional microarray format. 20-mer oligonucleotide probes and singly labeled 20-mer targets, representative of the T-cell acute lymphocytic leukemia 1 (TAL1) gene, has been used to elucidate the performance of this hybridization approach. DNA microarray is integrated with microfluidic channel on a poly(methyl methacrylate) (PMMA) to generate non-uniform zeta potential inside the channel. A microtrench is designed and fabricated on a PMMA chip using a widely available CO₂ laser scriber The electroosmotic mixing effect induced by the non-uniform zeta potential is utilized to enhance the DNA-DNA hybridization. The flow field in microfluidic channel is measured by particle image velocimetry (PIV). The enhanced signal to noise (S/B) ratio and reduced hybridization time is observed when the electroosmotic mixing is applied in the DNA-DNA hybridization.

The object of this paper is to present a low-lost vision-based computer interface which allows people with disabilities to use their head movements to manipulate computers. Our system requires only one low-cost web camera and a personal computer. Several experiments were conducted to test the performance of the proposed human-computer interface.

The aim of this study is to develop a non-continuous droplet manipulation technology in contrast to conventional continuous flow micro-fluidic systems. The droplets were manipulated based on the proposed opto-wetting effect. In addition, an experimental ultraviolet (UV) light actuated droplet manipulation system was developed for verifying the opto-wetting droplet manipulation. The proposed opto-wetting effect was achieved by utilizing ultraviolet to activate oxidation-reduction mechanism of nano-TiO₂ photo catalyst coated base material. The water-affinity of the base material will changed due to the decreased free-energy of the material surface. Therefore, the contact angle between the liquid droplet and base material will also be changed which facilitates droplet manipulability. The main components of the proposed ultraviolet (UV) light actuated droplet manipulation system include ultraviolet masking device, moving platform and main frame structure. System software and user interface were designed by using Microsoft Visual Basic 6.0 toolkit. Upon completion of the proposed system, experiments were carried out to verify system functionalities. Follow by the controlled variable optimization using Taguchi method and liquid droplet manipulation experiments. The experiment results indicate that by exposure to 6.8mW UV light, the surface tension and hydrophilic property of nano-TiO₂ (anatase type, 3.5% concentration, PH 1.5, and with average particle size of 69 nm) coated base material will changed. The change of surface tension and hydrophilic property were critical for droplet manipulation. The moving speed of the liquid droplet was measured as 3.33mm/sec. The results suggest that the opto-wetting system may be effective to overcome the shortcoming of traditional opto-electrowetting technique. The proposed opto-wetting droplet manipulation system could potentially applied for manipulating biomedical or pathological test specimens in the future.

The support vector machine (SVM) is a new learning method and has shown comparable or better results than the neural networks on some applications. In this paper, we applied SVM to classify multiple cancer types by gene expression profiles and exploit some strategies of the SVM method, including fuzzy logic and statistical theories. Using the proposed strategies and outlier detection methods, the FSVM (fuzzy support vector machine) can achieve a comparable or better performance than other methods, and provide a more flexible architecture to discriminate against SRBCT and non-SRBCT samples.

In the past 30 years, the progress in optical engineering, computer science and electronic techniques have made the endoscopy an invaluable tool in both internal clinics and surgical operation. As its applications increase exponentially, it has even become a specialized division in the clinical medicine. In order to obtain a larger field of view inside a small and narrow gastrointestinal tract, an endoscope is usually equipped with a wide-angle lens (Fish eye lens). Thus, an acquired image is often with certain degree of shape distortion. The distortion gets even more serious as the objects extend outward from the center of the lens in radial. This paper discusses the effect of such distortion and the correction of the effect. By using a calibration pattern, the nonlinear distortion is corrected with a simple mathematic model for the endoscope image. Once the endoscopic lens is calibrated, the same mathematic model can be utilized repeatedly for the images captured by that endoscope.

After capturing the calibration pattern using an endoscopic instrument, digital image processing techniques are applied to extract the calibration pattern from the distorted image. We propose a second order mathematic model and consider the parameters of optical lens. The coordinates of each dot in the calibration pattern are the input to the mathematic model for the correction of endoscope images. The experimental results show that the correction method is effective. For example, by comparing to the original calibration pattern image, the average errors in area calculation are 76.46% and 4.68% for the distorted and the corrected images, respectively.

Total hip arthroplasty is a common surgery for diseased hip joint in recent years. Although the operation receives good success, failure factors of the total hip prosthesis, however, include infection, dislocation, stem fracture and loosening. Concentrating on Sigma Medical Supplies Corporation total hip prosthesis, we use ANSYS finite element method software to establish an analysis model and simulate stress distribution of the stem and the cement. Design parameters of the stem are improved in order to make the stress a minimum and prolong the life of use. With the analysis results, we note that the geometry of contracting stem end is apt to make stress value rise. On the contrary, the extreme stress value can reduce around 73.4% when stem end diameter expands 15%.

Similarity or distance measures play important role in the performance of algorithms for ECG clustering problems. This paper compares four similarity measures such as the city block (L₁-norm), Euclidean (L₂-norm), normalized correlation coefficient, and simplified grey relational grade for clustering of QRS complexes. Performances of the measures include classification accuracy, threshold value selection, noise robustness, execution time, and the capability of automated selection of templates. The clustering algorithm used is the so-called two-step unsupervised method. The best out of the 10 independent runs of the clustering algorithm with randomly selected initial template beat for each run is used to compare the performances of each similarity measure. To investigate the capability of automated selection of templates for ECG classification algorithms, we use the cluster centers generated by the clustering algorithm with various measures as templates. Four sets of templates are obtained, each set for a measure. And the four sets of templates are used in the k-nearest neighbor classification method to evaluate the performance of the templates. Tested with MIT/BIH arrhythmia data, we observe that the simplified grey relational grade outperforms the other measures in classification accuracy, threshold value selection, noise robustness, and the capability of automated selection of templates.