Cerebral aneurysm is common lesion among adult population. Current methods for treating the disease have several limitations. Inspired by fern leaves, we have developed a new stent, called leaf stent,which can provide a tailored coverage at the neck of an aneurysm and thus prevent the blood from entering the aneurysm. It alone can be used to treat the cerebral aneurysm and therefore overcomes problems existing in current treating methods. The paper focuses on the numerical simulation of the leaf stents. The mechanical behaviour of the stent in various designs has been investigated using the finite element method. It has been found that certain designs provide adequate radial force and have excellent longitudinal flexibility. The
performance of certain leaf stents is comparable and even superior to those of the commercially available cerebral stents such as the Neuroform stent and the Enterprise stent, commonly used for stent assisted coiling, while at the same time, providing sufficient coverage to isolate the aneurysm without using coils.
cerebral aneurysm; leaf stent; nitinol; FEA (or finite element analysis); radial force; longitudinal flexibility; stent-artery interaction.
Xiang Zhou and Zhong You: 1Department of Engineering Science, University of Oxford, UK, OX3 7DQ
James Byrne, M.D.: Department of Neuroradiology, Nuffield Department of Surgery, University of Oxford, UK, OX3 9DU
The microcantilever (MCL) sensor is one of the most promising platforms for next-generation label-free biosensing applications. It outperforms conventional label-free detection methods in terms of portability and parallelization. In this paper, an overview of recent advances in our understanding of the coupling between
biomolecular interactions and MCL responses is given. A dual compact optical MCL sensing platform was built
to enable biosensing experiments both in gas-phase environments and in solutions. The thermal bimorph effect
was found to be an effective nanomanipulator for the MCL platform calibration. The study of the alkanethiol
self-assembly monolayer (SAM) chain length effect revealed that 1-octanethiol (C8H17SH) induced a larger deflection than that from 1-dodecanethiol (C12H25SH) in solutions. Using the clinically relevant biomarker Creactive
protein (CRP), we revealed that the analytical sensitivity of the MCL reached a diagnostic level of 1~500
Chuin-Shan Chen, Tzu-Hsuan Chang, Chia-Ching Chou and
Shu-Wei Chang: Department of Civil Engineering, National Taiwan University, Taipei 10617, Taiwan
Shu Kuan and Long-Sun Huang: Institute of Applied Mechanics, National Taiwan University, Taipei 10617, Taiwan
We are developing a biomimetic robot based on the Sea Lamprey. The robot consists of a ylindrical electronics bay propelled by an undulatory body axis. Shape memory alloy (SMA) actuators enerate propagating flexion waves in five undulatory segments of a polyurethane strip. The behavior of the robot is controlled by an electronic nervous system (ENS) composed of networks of discrete-time map-based
neurons and synapses that execute on a digital signal processing chip. Motor neuron action potentials gate
power transistors that apply current to the SMA actuators. The ENS consists of a set of segmental centralpattern generators (CPGs), modulated by layered command and coordinating neuron networks, that integrate input from exteroceptive sensors including a compass, accelerometers, inclinometers and a short baseline sonar array (SBA). The CPGs instantiate the 3-element hemi-segmental network model established from physiological studies. Anterior and posterior propagating pathways between CPGs mediate intersegmental coordination to generate flexion waves for forward and backward swimming. The command network mediates layered exteroceptive reflexes for homing, primary orientation, and impediment compensation. The SBA allows
homing on a sonar beacon by indicating deviations in azimuth and inclination. Inclinometers actuate a bending
segment between the hull and undulator to allow climb and dive. Accelerometers can distinguish collisions from impediment to allow compensatory reflexes. Modulatory commands mediate speed control and turning. A SBA communications interface is being developed to allow supervised reactive autonomy.
central pattern generator; biomimetic; autonomy; electronic neurons; robotics.
A Westphal and J Ayers:Department of Biology and Marine Science Center, Northeastern University, East Point,
Nahant, MA 01908, USA
N.F. Rulkov: Information Systems Laboratories, Inc., 10070 Barnes Canyon Road, San Diego CA 92121, USA, Institute for Nonlinear Science, UCSD, 9500 Gilman Dr., La Jolla, CA 92093, USA
D Brady: Department of Electrical and Computer Engineering, Northeastern University, 360 Huntington Ave.Boston, MA 02115, USA
M Hunt: Ariel Inc. Santa Ysabel, CA 92070, USA
Human state in human-machine systems highly affects the overall system performance, and should be detected and monitored. Physiological cues are essential indicators of human state and useful for the purpose of monitoring. The study presented in this paper was focused on developing a bio-inspired sensing system, i.e., Nano-Skin, to non-intrusively measure physiological cues on human-machine contact surfaces to detect human state. The paper is presented in three parts. The first part is to analyze the relationship between human state and physiological cues, and to introduce the conceptual design of Nano-Skin. Generally, heart rate, skin conductance, skin temperature, operating force, blood alcohol concentration, sweat rate, and electromyography are closely related with human state. They can be measured through human-machine contact
surfaces using Nano-Skin. The second part is to discuss the technologies for skin temperature measurement. The third part is to introduce the design and manufacture of the Nano-Skin for skin temperature measurement. Experiments were performed to verify the performance of the Nano-Skin in temperature measurement. Overall, the study concludes that Nano-Skin is a promising product for measuring physiological cues on human-machine contact surfaces to detect human state.
human-machine contact; human state detection; physiological cues; sensors; MEMS; NEMS.
Hongjie Leng and Yingzi Lin: Department of Mechanical & Industrial Engineering, Northeastern University, Boston, USA
This paper presents an emergent pattern recognition approach based on the immune network theory and hierarchical clustering algorithms. The immune network allows its components to change and learn patterns by changing the strength of connections between individual components. The presented immunenetwork-based approach achieves emergent pattern recognition by dynamically generating an internal image for the input data patterns. The members (feature vectors for each data pattern) of the internal image are produced by an immune network model to form a network of antibody memory cells. To classify antibody memory cells to different data patterns, hierarchical clustering algorithms are used to create an antibody memory cell clustering. In addition, evaluation graphs and L method are used to determine the best number of
clusters for the antibody memory cell clustering. The presented immune-network-based emergent pattern recognition (INEPR) algorithm can automatically generate an internal image mapping to the input data patterns without the need of specifying the number of patterns in advance. The INEPR algorithm has been tested using a benchmark civil structure. The test results show that the INEPR algorithm is able to recognize new structural damage patterns.
Bo Chen: Department of Mechanical Engineering - Engineering Mechanics, Michigan Technological University, 815 R.L. Smith Building, 1400 Townsend Drive, Houghton, MI 49931, USA, Department of Electrical and Computer Engineering, Michigan Technological University, USA
Chuanzhi Zang: Department of Mechanical Engineering - Engineering Mechanics, Michigan Technological University,
815 R.L. Smith Building, 1400 Townsend Drive, Houghton, MI 49931, USA, Shenyang Institute of Automation, Chinese Academy of Science, Nanta Street 114, Shenyang, Liaoning, P.R. China, 110016
This paper presents a flexible low-profile antenna sensor for fatigue crack detection and monitoring. The sensor was inspired by the sense of pain in bio-systems as a protection mechanism. Because the antenna sensor does not need wiring for power supply or data transmission, it is an ideal candidate as sensing elements for the implementation of engineering sensor skins with a dense sensor distribution. Based on the principle of microstrip patch antenna, the antenna sensor is essentially an electromagnetic cavity that radiates at certain resonant frequencies. By implementing a metallic structure as the ground plane of the antenna sensor, crack development in the metallic structure due to fatigue loading can be detected from the resonant frequency shift of the antenna sensor. A monostatic microwave radar system was developed to
interrogate the antenna sensor remotely. Fabrication and characterization of the antenna sensor for crack monitoring as well as the implementation of the remote interrogation system are presented.
A bio-inspired two-mode structural health monitoring (SHM) system based on the Naive Bayes(NB) classification method is discussed in this paper. To implement the molecular biology based Deoxyribonucleic acid (DNA) array concept in structural health monitoring, which has been demonstrated to
be superior in disease detection, two types of array expression data have been proposed for the development of
the SHM algorithm. For the micro-vibration mode, a two-tier auto-regression with exogenous (AR-ARX) process is used to extract the expression array from the recorded structural time history while an ARX process is applied for the analysis of the earthquake mode. The health condition of the structure is then determined using the NB classification method. In addition, the union concept in probability is used to improve the accuracy of the system. To verify the performance and reliability of the SHM algorithm, a downscaled eight-storey steel building located at the shaking table of the National Center for Research on Earthquake Engineering (NCREE) was used as the benchmark structure. The structural response from different damage levels and locations was collected and incorporated in the database to aid the structural health monitoring process.
Preliminary verification has demonstrated that the structure health condition can be precisely detected by the
proposed algorithm. To implement the developed SHM system in a practical application, a SHM prototype consisting of the input sensing module, the transmission module, and the SHM platform was developed. The vibration data were first measured by the deployed sensor, and subsequently the SHM mode corresponding to the desired excitation is chosen automatically to quickly evaluate the health condition of the structure. Test results from the ambient vibration and shaking table test showed that the condition and location of the benchmark structure damage can be successfully detected by the proposed SHM prototype system, and the
information is instantaneously transmitted to a remote server to facilitate real-time monitoring. Implementing
the bio-inspired two-mode SHM practically has been successfully demonstrated.
structural health monitoring; naive bayes; bio-inspired; prototype system.
Tzu-Kang Lin: National Center for Research on Earthquake Engineering, Taiwan
Li-Chen Yu, Chang-Hung Ku and Kuo-Chun Chang: Department of Civil Engineering, National Taiwan University, Taiwan
Anne Kiremidjian: Department of Civil and Environmental Engineering, Stanford University, USA
Polymeric thin-film assemblies whose bulk electrical conductivity and mechanical performance have been enhanced by single-walled carbon nanotubes are proposed for measuring strain and corrosion activity in metallic structural systems. Similar to the dermatological system found in animals, the proposed self-sensing thin-film assembly supports spatial strain and pH sensing via localized changes in electrical conductivity. Specifically, electrical impedance tomography (EIT) is used to create detailed mappings of film conductivity over its complete surface area using electrical measurements taken at the film boundary. While EIT is a powerful means of mapping the sensing skin
structural health monitoring; sensing skin; wireless sensor; carbon nanotube; bio-inspired sensing; impedance tomography.
Sukhoon Pyo: Dept. of Civil & Environmental Engineering, University of Michigan, Ann Arbor, MI 48109, USA
Kenneth J. Loh: Dept. of Civil & Environmental Engineering, University of California, Davis, CA 95616, USA
Tsung-Chin Hou: Dept. of Civil Engineering, National Cheng Kung University(NCKU), Tainan, Taiwan
Erik Jarva: Dept. of Electrical Engineering & Computer Science, University of Michigan, Ann Arbor, MI 48109, USA
Jerome P. Lynch: Dept. of Civil & Environmental Engineering, University of Michigan, Ann Arbor, MI 48109, USA, Dept. of Electrical Engineering & Computer Science, University of Michigan, Ann Arbor, MI 48109, USA