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Asl, Hamed Jabbari,Kim, Myeong Ok,Yoon, Jungwon American Scientific Publishers 2016 Journal of nanoscience and nanotechnology Vol.16 No.8
<P>The x-space reconstruction method for magnetic particle imaging (MPI) is a fast and robust method which provides the possibility for real-time imaging of the magnetic nanoparticle tracers. One limitation of this method is the requirement to utilize the complete MPI signal. The necessary filtering action in the MPI, removes the first harmonic information which affects the linearity and shift invariance (LSI) characteristics of the image. In this paper, LSI properties of the x-space imaging, necessary for medical diagnosis applications, is analyzed. It is shown that filtering the output signal causes an image loss which depends on the trajectory of the drive field where, for a harmonic drive field, its value is constant and can be compensated in 1D imaging. The findings of this paper reveal the importance of the method of applying the driving field in multidimensional x-space in order to keep the LSI properties.</P>
An Analytical Approach for Fast Recovery of the LSI Properties in Magnetic Particle Imaging
Jabbari Asl, Hamed,Yoon, Jungwon Hindawi Publishing Corporation 2016 International journal of biomedical imaging Vol.2016 No.-
<P>Linearity and shift invariance (LSI) characteristics of magnetic particle imaging (MPI) are important properties for quantitative medical diagnosis applications. The MPI image equations have been theoretically shown to exhibit LSI; however, in practice, the necessary filtering action removes the first harmonic information, which destroys the LSI characteristics. This lost information can be constant in the <I>x</I>-space reconstruction method. Available recovery algorithms, which are based on signal matching of multiple partial field of views (pFOVs), require much processing time and<I> a priori</I> information at the start of imaging. In this paper, a fast analytical recovery algorithm is proposed to restore the LSI properties of the <I>x</I>-space MPI images, representable as an image of discrete concentrations of magnetic material. The method utilizes the one-dimensional (1D) <I>x</I>-space imaging kernel and properties of the image and lost image equations. The approach does not require overlapping of pFOVs, and its complexity depends only on a small-sized system of linear equations; therefore, it can reduce the processing time. Moreover, the algorithm only needs<I> a priori</I> information which can be obtained at one imaging process. Considering different particle distributions, several simulations are conducted, and results of 1D and 2D imaging demonstrate the effectiveness of the proposed approach.</P>
Stable Assist-as-Needed Controller Design for a Planar Cable-Driven Robotic System
Hamed Jabbari Asl,윤정원 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.6
Robot-assisted rehabilitation systems have shown promising advantages over traditional therapist-basedmethods. The type of the controller has an important role in the efficiency of such systems. In this regard, thispaper presents a new assist-as-needed (AAN) controller for 4-cable planar robots. The main purpose is to designa bounded-input AAN controller with an adjustable assistance level and a guaranteed closed-loop stability. Theproposed controller involves the advantages of both the model-based and non-model-based AAN controllers, and inthis way can increase the efficiency of rehabilitation. The controller aims to follow a desired trajectory by allowingan adjustable tracking error, which enables the human subject to freely move the target limb inside this error area. This feature of the controller gives an important advantage over the existing model-based controllers. The controlleralso compensates for the dynamic modeling uncertainties of the system through an adaptive neural network. Theadaptive term includes a forgetting factor to adjust the assistance level of neural network term. The stability of theclosed-loop system is analysed, and the uniformly ultimately bounded stability is proven. The effectiveness of theproposed control scheme is validated through simulations conducted for gait rehabilitation.
Band-Stop Filter Analysis and Design for 1D Magnetic Particle Imaging Hybrid System
Le, Tuan-Anh,Asl, Hamed Jabbari,Do, Ton Duc,Kim, Myeong Ok,Yoon, Jungwon American Scientific Publishers 2016 Journal of Nanoscience and Nanotechnology Vol.16 No.8
<P>When converting the received signal from an analog signal into a digital signal, the analog-to-digital converter (ADC) is not capable of resolving both signals: the particle signal u(P)(t) and the excitation signal u(E)(t), so our system needs a band-stop filter (BSF) to filter out the excitation signal from the received signal before using the ADC. In this paper, we numerically investigate the filtering method and the effect of BSF on the MPI imaging. It is shown that the attenuation level of the filter is important in order to make the possibility of the restoring the linearity and shift invariance properties of the MPI image. These properties are important in diagnosis medical applications. Finally, we propose guidelines for designing the BSF.</P>