Summer Engineering Research Internship for US Students (SERIUS) Host Department: Department of Biomedical Engineering (www.bioeng.nus.edu.sg) BME Project 1 Host department Department of Biomedical Engineering Investigation of multiple strategies in modeling balloon expandable stent by finite element method In recent years, stent implantation has become one of the most popular treatment of coronary stenosis because of its high initial success rate and minimal invasive nature. Stent deployment into a diseased artery generates anomalous stress and deformation in artery walls, also there exists dogboning phenomenon resulting from nonuniform balloon stent expansion, both of them affect the progression of in stent restenosis. As the interaction of balloon stent artery system involves complex contact problem, simplified strategies such as applying uniform pressure directly on the inner surface of stent or enlarging a rigid cylinder inside the stent by displacement control is often used to model the balloon stent expansion, which is not close to the real expansion process. A three folded balloon model has been proposed to be necessary for accurate estimation of mechanic stress and reducing dogboning phenomenon, but this method costs great efforts and computational resources. This project aims to compare three different strategies mentioned above and optimize a better method to simulate the balloon stent expansion. Different balloon stent artery models will be constructed and an optimized method for simulating balloon stent expansion will be proposed, which is critical to evaluate the stent behavior so as to better design a commercial stent. Exploratory work Compare artery wall stress and dogboning phenomenon among different methods Determine a suitable balloon stent expansion modeling strategy No. of participants able to host 2 ( Assoc. Prof. LEO Hwa Liang http://www.bioeng.nus.edu.sg/biofluid_lab/index.html Be familiar Abaqus (or COMSOL) simulation process and understand the finite element analysis method
BME Project 2 Soft Pneumatic Actuator based Smart Tactile Robotic Hands for Underwater Bimanipulation Soft robotics have garnered great research interest from robotics community because they are lightweight and intrinsically safe. However, integration of non deformable sensors will impede the compliance of the soft actuators. Taking this into account, development of soft sensors with flexible and unconstrained structure is essential to enable a close loop control within the soft robot. The objective of this project is to design a low cost soft force sensor array which is constructed using a piezoresistive fabric sandwiched between printable flexible circuits. The developed sensors will be attached on a soft robotic hand to measure the grasping forces and detect slippage. The soft robotic hands will be implemented underwater to conduct bimanipulation of different objects, as part of robot based naval surveillance. Research, Developmental, Software 1. The students have to customize the design of the printable circuit and the layout of the sensors to increase its repeatability and durability. 2. The students have to calibrate the sensors and ensure that it can measure forces up to 20N accurately. 3. The students have to develop a control system that can measure the force values in real time and provide the feedback to the developed gripper and haptic glove. The students have the chances to learn different fabrication methods to manufacture soft pneumatic actuators and robotic arm control. The students will work in a team from different disciplines to meet the project s goals and demos. No. of participants able to host 2 Assistant Professor Raye Yeow Chen Hua http://www.bioeng.nus.edu.sg/eilab http://www.youtube.com/theeilab Reading list: J.H. Low, W.W. Lee, P.M. Khin, N.V. Thakor, S.L. Kukreja, H.L. Ren and C.H. Yeow. A hybrid tele manipulation system using a sensorized 3D printed soft robotic gripper and a soft fabric based haptic glove." IEEE Robotics and Automation Letters 2017. 2(2): 880 887. H.K. Yap, H.Y. Ng and C.H. Yeow. High Force Soft Printable Pneumatics for Soft Robotic Applications. Soft Robotics. 2016. J.H. Low, W.W. Lee, P.M. Khin, S.L. Kukreja, H.L. Ren, N.V. Thakor and C.H. Yeow. "A compliant modular robotic hand with fabric force sensor for multiple versatile grasping modes." 2016 6th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), Singapore, Singapore, 2016.
BME Project 3 3D Printed Soft Wearable Orthotics The objective of this project is to design, develop and 3D print soft wearable robots that can be worn to provide robot assisted rehabilitative movement to the lower limbs (e.g. hip, knee or ankle). These robots will empower stroke patients to perform activities of daily living, including walking and sit to stand. 3D printed soft wearable robots are highly customizable and can be designed to suit the patients' body dimensions. Students will be trained in the soft robot fabrication techniques, as well as control system development, programming and actuator characterization. Research, Developmental, Software 1. The students will develop a new 3D printed soft actuator design that has the capability to provide assistance to lower limb motion. 2. The students will learn to characterize the soft actuator design, in terms of bending curvature and torque output. 3. The students will develop and evaluate a fluidic control system that can control the actuators to provide motion assistance. The students have the chances to learn the 3D printing approach to manufacture soft pneumatic actuators and fluidic control. The students will work in a team from different disciplines to meet the project s goals and demos. No. of participants able to host 2 Assistant Professor Raye Yeow Chen Hua http://www.bioeng.nus.edu.sg/eilab http://www.youtube.com/theeilab Reading list: H.K. Yap, H.Y. Ng and C.H. Yeow. High Force Soft Printable Pneumatics for Soft Robotic Applications. Soft Robotics. 2016. W.K. Ang, C.H. Yeow*. A Novel Fold Based Design Approach towards Printable Soft Robotics using Flexible 3D Printing Materials. Advanced Materials Technologies 2017. [Accepted]
BME Project 4 No. of participants able to host Deep learning based motion control for minimally invasive surgery Medical data plays a significant role in image guided diagnosis, intervention and planning; however, because of the high exposure radiation, it is not desirable for children, youth, pregnant females, etc. To address these challenges, the project aims to develop deep learning based statistical atlas and motion control. This involves medical image analysis and computational programming. For more information about our lab and our related previous projects, please visit: http://bioeng.nus.edu.sg/mm/ or http://bioeng.nus.edu.sg/mm/people/undergraduates/ Exploratory Learning skills useful for the future study 1 2 (For this overall cross disciplinary project) Asst Prof Hongliang REN For more information about our research projects, please click here www.bioeng.nus.edu.sg/biomm NA
BME Project 5 No. of participants able to host Flexible Robotic System for Computer Integrated Surgery Real time vision information about the motion and 3D structure of the surgical field during Minimally Invasive Surgery (MIS) is important for enabling computer integrated surgical systems with advanced capabilities of navigation and active control. Although many endoscopic imaging techniques have been developed, there are urgent needs in steerable and controllable endoscopic imaging and manipulation system. This project aims 1. To model the mechanics of flexible and automated controllable endoscopic robot with confined configurations. 2. To perceive 3 D surgical field with advanced information processing techniques. 3. To design newly controllable structure for endoscopic imaging. 4. To validate the system in the university hospital. The project involves knowledge development in imaging, mechanics, and control in collaboration with surgeons from university hospital. The student will be practicing with various instruments, mechanical components, electronics, software, and interacting with surgeons. The student can choose a component from the big project, which fit her/his, background. For more information about our research projects, please click HERE www.bioeng.nus.edu.sg/mm Exploratory Learning skills useful for the future study 1 3 (For this overall cross disciplinary project) Asst Prof Hongliang REN For more information about our research projects, please click here www.bioeng.nus.edu.sg/biomm NA
BME Project 6 No. of participants able to host Robotic Biopsy System in Computer Assisted Interventions This project will investigate the optimal biopsy device development, planning and robotic approach for a new type of needle based tumor biopsy. The system will address clinical constraints on biopsy and trajectories by optimal path selection and coverage. The study involves hardware development, computational algorithm development based on image analysis and optimization. For more information about our lab and our related previous projects, please visit: http://bioeng.nus.edu.sg/mm/ or http://bioeng.nus.edu.sg/mm/people/undergraduates/ Exploratory Learning skills useful for the future study 1 2 (For this overall cross disciplinary project) Asst Prof Hongliang REN For more information about our research projects, please click here www.bioeng.nus.edu.sg/biomm NA
Host Departments: Department of Biomedical Engineering / Singapore Institute for Neurotechnology (SINAPSE) (www.bioeng.nus.edu.sg) / (http://www.sinapseinstitute.org/) BME Project 7 NEUROTECHNOLOGY Students will be involved in projects in the field of neuroechnology, in the following areas: 1) Neurodevice development (for brain monitoring), 2) Implantable neurotechnologies (for neural interfaces), 3) Nuroprosthesis (for restoring sensory and motor function), 4) Brain Machine Interface, 5) Cognitive Engineering, 5) Neuromorphic Engineering (neuro/bio inspired sensors and computing), 6) Experimental Neurosciences (cellular, and physiological experimentation). SINAPSE is a comprehensive institute with experimental capabilities that range from cellular to whole brain clinical neuroscience. The engineering capabilities include laboratories for development of micro/nano technologies, device development, prosthetics and robotics, virtual reality lab. The students will work in a collaborative atmosphere on specific projects at the interface of neuroscience and cutting edge technologies. The projects will be experimental as well as technology development. No. of participants able to host Maximum of 5 Depending on the specific project, the students will complete the development and testing of a device and/or conduct experimental testing. The project will end with a presentation and submission of a research paper. s Prof. Nitish Thakor Prof. Anastasisos Bezerianos Dr. In Hong Yang Dr. Aishwarya Bandla Dr. Anupam Gupta www.sinapseinstitute.org; sinapsedirector@gmail.com Depending on the selected project, the students should have an interest in the field of basic or applied neurosciences, and background in engineering disciplines with design and development skills, experimental capabilities. Computational and programming skills are desirable.
Host Departments: Department of Biomedical Engineering / Mechanobiology Institute (MBI) (www.bioeng.nus.edu.sg) / (https://mbi.nus.edu.sg/) BME Project 8 Multi functional multifocus microscopy based on phase masks To eliminate the z scanning for 3d imaging, we would like to test the capacity of multifocus microscopy (MFM) based on phase masks. Two possible systems would be built, one is MFM for whole cellular imaging, and also polarization analysis of the cellular components based on the technology. The other one is to combine single molecule localization microscopy with multifocus microscopy to realize 3D super resolution of the whole cell. Experimental Experience in building optical system and image analysis No. of participants able to host 1 Asst Prof Pakorn Tony Kanchanawong https://mbi.nus.edu.sg/pakorn tony kanchanawong/ Experiences in bioimaging, microscopy, or image analysis are recommended.