Modeling and Analysis of a SiC Microstructure-Based Capacitive Micro-Accelerometer

In this study, a comb-type capacitive accelerometer based on a silicon carbide (SiC) microstructure is presented and investigated by the finite element method (FEM). It has the advantages of low weight, small volume, and low cross-coupling. Compared with silicon(111) accelerometers with the same structure, it has a higher natural frequency. When the accelerometer vibrates, its resistive force consists of two main components: a viscous damping and an elastic damping force. It was found that viscous damping dominates at low frequency, and elastic damping dominates at high frequency. The second-order linear system of the accelerometer was analyzed in the time-frequency domain, and its dynamic characteristics were best when the gap between the capacitive plates was 1.23 μm. The range of this accelerometer was 0–100 g, which is 1.64 times that of a silicon(111) accelerometer with the same structure. In addition, the accelerometer could work normally at temperatures of up to 1200 °C, which is much higher than the working temperatures of silicon devices. Therefore, the proposed accelerometer showed superior performance compared to conventional silicon-based sensors for inertial measurements.     

基于可穿戴式传感装置的帕金森运动症状量化评估的研究进展

帕金森病(PD)运动症状的量化评估是PD诊疗中的一个难题;基于MEMS(微机电系统)运动传感器的可穿戴式装置可以跟踪PD病人设定动作和自主运动等运动信息,从而实现帕金森运动症状的实时和客观的量化评估。首先介绍MEMS运动传感器技术及用于帕金森运动症状量化评估的典型性可穿戴式系统,包括其局限性;然后对震颤/异动症、缓慢运动、肌肉僵直、姿势步态障碍等4个主要运动症状的量化评估方法及其与神经科医生临床判断相关性分别进行对比和分析;同时对PD症状波动等运动并发症对运动症状量化评估的影响进行讨论。介绍MEMS运动传感技术在PD运动症状量化评估中的应用及其精确性,为基于可穿戴式传感装置的帕金森运动症状定量评估研究提供一个基础框架。     

MEMS微针阵列干电极及其在生理电信号采集中的应用

生理电信号能直接反映人们的身体状况,且随着各种便携式设备、穿戴式设备的出现,生理电信号的采集得到越来越多的重视。近年来,许多研究人员致力于生理电信号采集电极的研究,因此基于MEMS技术的微针阵列干电极逐渐成熟。微针阵列干电极通过微针刺入被测者的皮肤,实现连续、长期、高效的生理电信号采集,由于其成本低、操作简单、不会使被测者感到不适、采集质量高等优点,逐渐取代传统湿电极而得到越来越广泛的应用。通过将微针阵列干电极与湿电极进行对比,突出微针阵列干电极的研究价值;结合国内外最新研究,综述微针阵列干电极的制作工艺、微针阵列干电极的改进技术、在生理电信号采集中的应用现状;讨论目前微针阵列干电极存在的不足,并对以后的发展趋势进行展望。     

Optimal timing of radical cystectomy in T1 high-grade bladder cancer

There has been an explosion in the development of microscopic and miniaturized technology over the past decade and we have long awaited their arrival and integration into clinical practice. We have now reached the stage where promises are beginning to be delivered. This article reviews their place in modern medicine and looks toward the future. Miniature camera robots (microrobots) provide a mobile viewing platform, enhancing a surgeon’s view. Nanorobots have arisen from the fictional world of the ‘Fantastic Voyage’ and are finally approaching clinical application. As the targeting and drive forces are further developed, these vehicles could be realistically used for delivery of agents for diagnosis and therapies. These new robots have the potential to further evolve the robotic armamentarium for surgeons.     

用于肠道药物释放和采样的遥控式微型药丸的研制

基于微机械、微电子技术的肠道微型药丸是肠道疾病诊断、治疗以及肠道代谢特性研究的有效工具.本文讨论了目前作者正在进行的用于肠道药物定点释放和采样的微型药丸的研制工作,该微型药丸以活塞工作原理为物理模型,由体外无线遥控实现药物定点释放和采样功能.实验表明,作者研制的微型药丸生物相容性好,采样和释放动作可靠,可满足小肠肠液采样和定点药物释放的实验研究需要.     

人体全消化道动力检测信号自动分析处理方法研究

消化道腔内压力检测是胃肠动力疾病诊断和胃肠动力学研究的一种主要手段。利用MEMS技术，我们开发了人体全消化道微型智能介入式诊查系统，能在正常生理状态下对全消化道压力、pH值进行长时间连续监测，解决了长期困扰医学界的压力信号的获取问题。本文着重讨论了系统的软件部分，即建立信号自动分析处理系统的必要性和方法。该系统主要实现信号的预处理、信号特征值的提取和优化、样本的分类功能，从而使测试结果可以真正应用于辅助医学诊断和研究，完善整个系统的功用。     

Optimization of the GaAs-on-Si Substrate for Microelectromechanical Systems (MEMS) Sensor Application

Resonant Tunneling Diodes (RTD) and High Electron Mobility Transistor (HEMT) based on GaAs, as the piezoresistive sensing element, exhibit extremely high sensitivity in the MEMS sensors based on GaAs. To further expand their applications to the fields of MEMS sensors based on Si, we have studied the optimization of the GaAs epitaxy layers on Si wafers. Matching superlattice and strain superlattice were used, and the surface defect density can be improved by two orders of magnitude. Combing with the Raman spectrum, the residual stress was characterized, and it can be concluded from the experimental results that the residual stress can be reduced by 50%, in comparison with the original substrate. This method gives us a solution to optimize the epitaxy GaAs layers on Si substrate, which will also optimize our future process of integration RTD and HEMT based on GaAs on Si substrate for the MEMS sensor applications.     

Micro-nanorobots: important considerations when developing novel drug delivery platforms

ABSTRACT

Introduction: There is growing emphasis on the development of bioinspired and biohybrid micro/nanorobots for the targeted drug delivery (TDD). Particularly, stimuli-responsive materials and magnetically triggered systems, identified as the most promising materials and design paradigms. Despite the advances made in fabrication and control, there remains a significant gap in clinical translation.

Areas covered: This review discusses the opportunities and challenges about micro/nanorobotics for the TDD as evolutionary evidence in bio-nanotechnology, material science, biohybrid robotics, and many more. Important consideration in context with the material’s compatibility/immunogenicity, ethics, and security risk are reported based on the development in artificial intelligence (AI)/machine learning described in literature. The versatility and sophistication of biohybrid components design are being presented, highlighting stimuli-responsive biosystems as smart mechanisms and on-board sensing and control elements.

Expert opinion: Focusing on key issues for high controllability at micro- and nano-scale systems in TDD, biohybrid integration strategies, and bioinspired key competences shall be adopted. The promising outlook portraying the commercialization potential and economic viability of micro/nanorobotics will benefit to clinical translation.     

Implantable microelectromechanical sensors for diagnostic monitoring and post‐surgical prediction of bone fracture healing

The relationship between modern clinical diagnostic data, such as from radiographs or computed tomography, and the temporal biomechanical integrity of bone fracture healing has not been well‐established. A diagnostic tool that could quantitatively describe the biomechanical stability of the fracture site in order to predict the course of healing would represent a paradigm shift in the way fracture healing is evaluated. This paper describes the development and evaluation of a wireless, biocompatible, implantable, microelectromechanical system (bioMEMS) sensor, and its implementation in a large animal (ovine) model, that utilized both normal and delayed healing variants. The in vivo data indicated that the bioMEMS sensor was capable of detecting statistically significant differences (p‐value <0.04) between the two fracture healing groups as early as 21 days post‐fracture. In addition, post‐sacrifice micro‐computed tomography, and histology data demonstrated that the two model variants represented significantly different fracture healing outcomes, providing explicit supporting evidence that the sensor has the ability to predict differential healing cascades. These data verify that the bioMEMS sensor can be used as a diagnostic tool for detecting the in vivo course of fracture healing in the acute post‐treatment period. © 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 33:1439–1446, 2015.