A review on quantitative ultrasound of fast and slow waves

Offering inexpensive, widely available and safe method to evaluate the bone condition as a prevention step to predict bone fracture which caused by Osteoporosis disease makes ultrasound becomes an alternative method beside X-ray based bone densitometry. Conventional quantitative ultrasound (QUS) applies the analysis of attenuation and velocity to estimate bone health with several measurement techniques which analyzes different types of ultrasound waves and bones. However, most of the QUS results still does not match the accuracy of the Dual X-ray absorptiometry due to the interaction of ultrasound and bone microstructure are not fully exploited. The Biot’s theory has predicted that, porous medium like a cancellous bone supporting two types of longitudinal wave known as fast and slow wave which depends on the type of medium travelled. Both experiment and simulation were conducted to investigate the correlation of fast and slow waves individually with a variety of cancellous bone condition. Some of the analysis methods are based on conventional QUS methods. The fast and slow wave relates more to the microstructure of the cancellous bone compared to overall waves. In addition, overall waves had been proven to consist of fast and slow wave and can be separated using Bayesian methods. Overall waves also found to suffer artifact such as phase cancellation and negative dispersion that could cause confusion in analyzing the parameters of ultrasound wave with bone structure. In vivo application based on fast and slow wave analysis is able to produce results based on mass density which can be compared directly and have high correlation with X-ray based bone densitometry. The recent backscattered simulation result indicates that, fast and slow waves can be reflected inside the cancellous bone might offer a new method to evaluate bone especially in crucial skeletal parts

Sonar assistive device for visually impaired people

An affordable sonar assistive device was developed to facilitate the visually impaired people to walk inside or outside their homes. The device uses a sonar technology where each ultrasonic sensor consists of a transmitter and a receiver. The transmitter will transmit a signal to an obstacle in front of it and when the signal reaches an obstacle, the signal is reflected back. The reflected signal is then received by the receiver. The system of Arduino Pro Mini will then evaluate the echo to identify the presence t of the obstacles. This ultrasonic sensor can detect obstacles as far as 4 meters. Hands-on testing was conducted to identify visually impaired people needs and to provide them an opportunity to use the device. The users were interviewed to find out about their experience. The results clearly show that 90% of the users were satisfied with the features of the device and they were also confident of using the device to detect different types of obstacles

Microfluidic Channel Geometry and Fluid Velocity Investigation for Single Cell Hydrodynamic Trapping

Microfluidic technology has been applied widely for separating and trapping various type of cells. This technology has open ways to study and understand the biological systems, the mechanism of diseases, developing the therapeutic drugs, strategy to cure diseases and also in developing the biomarker for early disease diagnosis. Hydrodynamic cell trapping offers a great opportunity to direct, position, and trap particles or cells in small volume liquids, a crucial requirement for efficient single cell analysis. The challenges in hydrodynamic trapping are the need for control precisely the microfluidic multiple streams and a precise geometry design required to allow successful trapping. To address this limitation, the single cell hydrodynamic trapping finite element simulation was developed to determine the efficiency of single cell traps of variable geometries. A series of simulation studies were performed to analyze the effect of the trap hole size, channel’s height and fluid’s flow profiles to the appropriate for efficient single cell trapping. From the simulation, increasing the trap hole size has resulted in a gradually decreased of the fluid velocity in the trap channel. Furthermore, the fluid velocity in trap channel was found increasing with the increment of the HChannel. Single cell trapping channel with the HHole of 4 μm and HChannel of 15 μm produced the highest velocity in the trap channel compared to other geometry tests. This finite element model could be utilised as a guideline for designing and developing a chip to reduce the costly and time-consuming trialand-error fabrication process

Identification of electrooculography signals frequency energy distribution using wavelet algorithm

Problem statement: The time frequency analysis of non-stationary signals has been the considerable research effort in recent years. Wavelet transform is one of the favored tool for the analyzing the biomedical signals. Approach: We describe the identification of Electro-Oculograph (EOG) signals of eye movement potentials by using wavelet algorithm which gives a lot of information than FFT. The capability of wavelet transform was to distribute the signal energy with the change of time in different frequency bands. This will showed the characteristic of the signals since energy was an important physical variable in signal analysis. The EOG signals were captured using electrodes placed on the forehead around the eyes to record the eye movements. The wavelet features used to determine the characteristic of eye movement waveform. This technique adopted because it was a non-invasive, inexpensive and accurate. The new technology enhancement has allowed the EOG signals captured using the Neuronal EEG-9200. The recorded data was composed of an eye movement toward four directions, i.e., downward, upward, leftward and rightward. The proposed analysis for each eyes signal is analyzed by using Wavelet Transform (WT) with energy algorithm and by comparing the energy distribution with the change of time and frequency of each signal. Results: A wavelet Scalogram was plotted to display the different percentages of energy for each wavelet coefficient towards different movement. Conclusion: From the result, it is proved that the different EOG signals exhibit differences in signals energy with their corresponding scale such as leftward with scale 6 (8-16Hz), rightward with scale 8 (2-4Hz), downward with scale 9 (1-2Hz) and upward with level 7 (4-8Hz). Statistically, the results in this study indicate that there are 93% (averages) significance differences in the extracted features of wavelet Scalogram analysis

Multiviews reconstruction for prosthetic design

Existing methods that use a fringe projection technique for prosthetic designs produce good results for the trunk and lower limbs; however, the devices used for this purpose are expensive. This paper investigates the use of an inexpensive passive method involving 3D surface reconstruction from video images taken at multiple views. The method that focuses on fitting the reference model of an object to the target data is presented. For an upper dummy limb, the fitting of the model with the data shows a satisfactory result. The results of 15 measurements of different length between both reconstructed and actual dummy limb are highly correlate . The methodology developed is shown to be useful for prosthetic designers as an alternative to manual impression during the design

Gaze at desired destination, and wheelchair will navigate towards it. New technique to guide wheelchair motion based on EOG signals

In this work, we propose new method beside the classic method, to control the motorized wheelchair using EOG signals. The new method allows the user to look around freely while the wheelchair navigates automatically to the desired goal point. Only EOG signals are used to control the wheelchair, eye gazing and blinking. The user can still choose to control the wheelchair using the classic manual method in case the environment and obstacles structure does not help with the auto navigation method. In the new auto navigation method the micro controller can know the goal point direction and distance by calculating the gaze angle that the user is gazing at. Tangent Bug algorithm is used to navigate the wheelchair in Auto controlling method. Experimental results are similar to simulated with minimum error, due to minimal positioning and sensing errors