Biomedical Engineering: Applications, Basis and Communications

Background and Purpose. Aneurysm geometry often dictates the success of coil embolization. A strong hemodynamic force or high intra-aneurysmal flow may indicate a high probability of recanalization. It is necessary to develop a tool that can predict and estimate the level of hemodynamic forces that coils are subject to during the procedure. Methods. A compartment model is developed to estimate the intra-aneurysmal flow after coil embolization from digital fluoroscopy. The model is based on the measured signal intensity curves for the aneurysm and adjacent artery and derives the amount of intra-aneurysmal flow reduction. A clinical case of a carotid aneurysm was used for demonstration of its ability. Results. Intra-aneurysmal flow was reduced by 70% after coil embolization, and the estimated porosity was 60%. Flow reduction was confirmed by computational fluid dynamics simulations that modeled the coiled aneurysm as a porous medium. Conclusion. Intra-aneurysmal flow reduction may be used to predict the outcome of coil embolization or possible aneurysm recurrence. A sustained high intra-aneurysmal flow prohibits complete embolization and allows recanalization of the aneurysm. The compartment model provides a reasonable estimate of intra-aneurysmal flow and hemodynamic forces on the coils.

New techniques for the prediction of tumour behaviour are needed as statistical analysis has a poor accuracy and is not applicable to the individual. Artificial intelligence (AI) may provide these suitable methods. We have previously shown that the predictive accuracies of neuro-fuzzy modelling (NFM) and artificial neural networks (ANN), two methods of AI, are superior to traditional statistical methods for the behaviour of bladder cancer (Catto et al, 2003). In this paper, we explain the AI techniques required to produce these predictive models. We used 9 parameters, which were a combination of experimental molecular biomarkers and conventional clinicopathological data, to predict the risk of tumour progression in a population of 109 patients with bladder cancer, NFM, using fuzzy logic to model data, achieved similar or superior predictive accuracy to ANN, which required cross-validation. However, unlike the impenetrable opaque structure of neural networks, the rules of NFM are transparent, enabling validation from clinical knowledge and the manipulation of input variables to allow exploratory predictions.

In this study, we evaluate the accuracy of classifiers for classification of ultrasonic liver tissues. Two different statistic classifiers and three various artificial neural networks are included: Bayes classifier, k-nearest neighbor classifier, Back-propagation neural networks, probabilistic neural network and modified probabilistic neural network. These five different classifiers were investigated to determine their ability to classify various categories of ultrasonic liver images. The investigation was performed on the basis of the same feature vector. For statistic classifiers the classification accuracy is at most 90.7% and with artificial neural networks the accuracy is at least 92%. The experimental results illustrated that artificial neural networks are an attractive alternative to conventional statistic techniques when dealing with classification task. Moreover, the feature vector based on fractal geometry and wavelet transform can provide good discriminant ability for ultrasonic liver images under study.

Sequence alignment is a fundamental and important tool for sequence data analysis in molecular biology. Many applications in molecular biology require the detection of a similarity pattern displayed by a number of DNA and protein sequences. Visual front-ends are useful for an intuitive viewing of alignment and help to analyze the structure, functions, and evolution of the DNA and protein. In this paper, we designed and implemented an interactive system for data visualization in DNA and proteins, which can be used in determining a sequence alignment, similarity search of sequence data, and function interference. Experimental results show that a user can easily operate the system after one hour's practice on the proposed system, which provides a clean output, easy identification of similarity and visualization of alignment data.

Tooth colorimeter provides the determination of patient's tooth shade, and assists dentists, technicians and patients in satisfying the clinical needs for dental medicine. The traditional visual matching approaches of tooth shade tabs had some limitations that are based on subjective color perception and could be easily affected by environmental factors. In this research, we have developed a fiber optics spectroscopic tooth colorimeter with white LED, instead of the tungsten lamp to improve the size and heat problems. We have also developed a Whiteness-Yellowness index to simplify the tooth color information and have achieved an objectively and quantitatively tooth color representation.

The body movement is one of the most important factors to evaluate the sleep quality. In general, the sleep motion is hardly investigated, and it must take a long time to observe the motion of the patient in terms of a pre-recoded video storage media with high speed playing. This paper proposes an image-based solution to recognize the sleep motions. We use the contact free and IR-based night vision camera to capture the video frames during the sleep of the patient. The video frames are used to recognize the body positions and the body directions such as the “body up”, “body down”, “body right”, and “body left”. In addition to the image processing, the proposed artificial neural network (ANN) sleep motion recognition solution is composed of two neural networks. These two neural networks are organized as in a cascade configuration. The first ANN model is used to identify the body position features from the images; and the follower ANN model is constructed based on the features that are identified by the first ANN model to recognize the body direction. Finally, the implementations and the practical results of this work are all illustrated in this paper.

The main purpose of this paper is to investigate the intensity distribution and the temperature responses when ultrasound beams are used for the intact brain tumor hyperthermia. A search method is developed to search for the appropriate transducer diameter and the input power level that induce a well focused high intensity region and an effective thermal dose region to enhance the goodness of the brain ultrasound hyperthermia treatments. This work employs a simplified model of a scanned ultrasound transducer power deposition (a cone with convergent/divergent shape). Multiple reflections and transmissions occurring at the interfaces are taken into consideration of calculating the intensity distribution as an ultrasound plane wave propagates through skull bone into brain tissue. The distributions of ultrasound intensity, specific absorption rate ratio, and temperature are used to determine the appropriateness of the transducer diameter and the input power level for a yielded set of tumor conditions. Simulation results demonstrate that (1) the maximum intensity ratio in the tumor region is larger than that in the bone region for all frequencies; (2) the treatments for larger tumors become more difficult to solve if the ratio of the diameter of transducer to the tumor diameter is less than 10 when one tries to use only high intensity ultrasound exposure to cause small lesions due to the cavitation effects. Results demonstrate the feasibility of inducing both a well focused high intensity region to produce local cavitation lesions and an effective thermal dose region to enhance the goodness of the intact brain ultrasound hyperthermia treatments. The results of this study can be a guideline for designing an optimal ultrasound heating system, arranging the transducers, and implementing further treatment planning for the transcranial brain tumor hyperthermia.

Being a common daily activity, stair locomotion places much higher loads on the lower limb than level walking does so a better understanding of the biomechanics of this activity is important for evaluation and treatment for patients with lower limb problems. The purpose of the present study was to investigate the three-dimensional dynamics and coordination of the joints of the lower limb during the stance phase of stair ascent and descent. Ten normal young adult subjects were recruited to ascend and descend stairs in a gait laboratory where the three-dimensional kinematic and kinetic data as well as muscle electromyography (EMG) were collected. The sagittal ranges of motion during stance phase of stair ascent were from 1.85° extension to 53.5° flexion for the hip, 13.1° to 60.1° flexion for the knee and 13.8° dorsiflexion to 14.0° plantarflexion for the ankle. Corresponding data for stair descent were 4.78( to 13.16( flexion for the hip, 8.3° to 77.6° flexion for the knee and 18.3° dorsiflexion to 27.4° plantarflexion for the ankle. Maximum extensor moments of 8.5% and 15.6% (Nm/BW/LL) were required at the hip and knee respectively during loading response while 19.4% (Nm/BW/LL) at the ankle shortly before toe-off. During stair descent, maximum extensor moments of about 4.4% were required at the hip during loading response and before toe-off while 13.3% and 15.2% (Nm/BW/LL) at the knee and ankle respectively before toe-off The joint angles, moments, and powers in the frontal and transverse planes were relatively small, except for hip abduction. The hip abductor moments and powers were significantly bigger than those of the knee and ankle in both stair activities. Joint powers and the corresponding muscle activation patterns in stair ascent were significantly different from those in descent, with concentric powers generated mostly during stair ascent and with eccentric powers stair descent. The differences of the movements of the lower limb during stair ascent and descent were due to different safety requirements and kinematic and kinetic constraints from the stairs. The complete description of the biomechanics of the lower extremity while performing stair locomotion will be helpful for the planning and evaluation of treatment programs for patients with lower limb problems.