Lei Miao

Signal reconstruction of the slow wave and spike potential from electrogastrogram.

The gastric slow wave and the spike potential can correspondingly represent the rhythm and the intensity of stomach motility. Because of the filtering effect of biological tissue, electrogastrogram (EGG) cannot measure the spike potential on the abdominal surface in the time domain. Thus, currently the parameters of EGG adopted by clinical applications are only the characteristics of the slow wave, such as the dominant frequency, the dominant power and the instability coefficients. The limitation of excluding the spike potential analyses hinders EGG from being a diagnosis to comprehensively reveal the motility status of the stomach. To overcome this defect, this paper a) presents an EGG reconstruction method utilizing the specified signal components decomposed by the discrete wavelet packet transform, and b) obtains a frequency band for the human gastric spike potential through fasting and postprandial cutaneous EGG experiments for twenty-five human volunteers. The results indicate the lower bound of the human gastric spike potential frequency is 0.96±0.20 Hz (58±12 cpm), and the upper bound is 1.17±0.23 Hz (70±14 cpm), both of which have not been reported before to the best of our knowledge. As an auxiliary validation of the proposed method, synchronous serosa-surface EGG acquisitions are carried out for two dogs. The frequency band results for the gastric spike potential of the two dogs are respectively 0.83-0.90 Hz (50-54 cpm) and 1.05-1.32 Hz (63-79 cpm). They lie in the reference range 50-80 cpm proposed in previous literature, showing the feasibility of the reconstruction method in this paper.

Processing and analysis of bio-signals from human stomach

In this article, the electrogastrography is utilized to detect slow wave of gastric digest motility after test meal. In order to extract useful information, this study used multi-resolution method with the Daubechies wavelet function to decompose EGG signal into 9 layers. We reconstructed the slow wave with decomposed signal after digital signal processing to achieve method of the slow wave detection of EGG. During strong contraction of stomach, there is a significant increase in frequency spectrum and power spectrum of the slow wave frequency region. And power spectrum of time windows of slow wave bandwidth increases clearly. The contribution of this paper was that the filter of CWT and Fourier transform was used to obtain the bandwidth of slow wave, and the proposed method was compared with Chebyshev filter. By calculation and analysis of experimental data, the EGG slow wave detection method of wavelet-based motility of gastric digestion was verified to be effective, and also provided a better clinical method to monitor the state of stomach activities. This method is also can be applied to human medical sensor network which includes electrogastrography, electrocardiogram, thermometer, sphygmomanometer.

Accurate estimation of tip shape for reconstructing AFM image

AFM image is often distorted due to the influence of the tip shape. This problem has become one of the major obstacles in nano-observation. Therefore it is necessary to develop a compensation method to improve the quality of the AFM image. The common used method today is image reconstruction with deconvolution operator based on the tip shape built through blind tip estimation algorithm. However, the current algorithm has difficulties in getting the optimal noise threshold, which is essential for reducing the noise influence during the tip evaluation. This paper proposed a new method to solve this problem, through which the optimal threshold can be easily determined based on the comparison of tip section profile Pα and tip standard profile Ps. The experimental results validate the effect of the proposed method, and it also shows that the image quality has been greatly improved.

Feedback control implementation for AFM contact-mode scanner

The atomic force microscope (AFM) has become a standard technique to measure the topography properties of sample surfaces with nanometer resolution. And the AFM tip based Nano manipulation system plays an important role in the field of Nano research. However, nearly all the systems are designed in the commercial AFM machine, in which the software and hardware is not open to perform the Nano manipulation related research. This paper describes a feedback control system implementation for AFM contact-mode scanner, as part of work in building a Nano manipulation system. With PSD sensor and piezoceramic driver, we designed an embedded control system to fulfill the scanning experiments. The imaging results of silicon steps using regular PED feedback control scheme show that the scanning performance is limited by the inherent piezoelectric actuator nonlinear characteristics. In order to achieve better scanning image, we add a Preisach model based feedforward loop into the PED feedback controller to compensate for the hysteresis effect of the piezoceramic actuator, and the performance has been improved moderately. This AFM platform will be used as a testbed for future research work and experiments on AFM scan and manipulation.

Design the Nano manipulation system based on AFM: A system view with force feedback research

The main goal of Nano technology is to analyze and understand the matter at the atomic and molecular level. While the researchers of Nano technology are lack of an efficient tool which can manipulate the material such as CNT to accomplish the CNT-FET or CNT-sensor. The manipulation robot based on AFM tip can perform the nano manipulation with the enhanced reality. This paper shows a system view of the Nano manipulation system and the system design of the manipulation system. We can build nano manipulation robot based on the system we design with the help of haptic device.

Analysis of depth from defocus measurements for micro-imaging and 3D micro-visual reconstruction

Based on fuzzy measurement of microscopic optical images, analysis of the focused and defocused characteristics of the images was performed, and a method based on Depth from Defocus (DFD) is developed for micro scale image analysis and reconstruction. In this method, we use gradient operators as the measurement operator. With the establishment of relationship between the defocus measurement and the depth transformation of the micro image sequence, we obtained the depth information of the target-object. As a test of validity of our method, we also performed an experiment to measure the parallelism of a micro manipulation platform. In additional, we also reconstructed micro contour images using the DFD method and the experiment results showed that the method is valid for 3D reconstruction of microscope images.

Measurement the displacement of the micro robotic gripper using microscopic images

This paper reports on the construction of the computer Micro vision system to measure the displacement of the micro robotic gripper. Sum-Modified-Laplacian based focus measure is used in region of interest of microscopic images, which may be used as focus measure. We got the value of the displacement using estimation method with the value of focus measure.

Towards Automating Micro Cellular Detection Process Using Micro Vortex Pump Arrays

This paper reports a polymer based microfluidic analysis system integrated with a surface plasmon resonance (SPR) biosensor for detecting the specific binding of biomolecules and qualitatively monitoring of cell adhesion on the sensor surface. Micropumps, microchannels, and SPR biosensor were integrated into a single polymer (PMMA) based microfluidic system. The integrated system has been studied in its potential application in bio-molecules detection and drug discovery. Two experiments, 1) monitoring the reaction between BSA-BSA antibody, and 2) monitoring the activities of living cells in the presence or absence of trypsin in RPMI-1640 medium, were conducted to show the feasibility of real-time cellular and molecular detection. Based on these successful experimental results we have also developed a computer-controllable vortex micropump system that will eventually automate many bio-molecular detection and drug discovery processes.