Ultra-Low Power Inertial MEMS for Pervasive Wearable Computing

用于普遍可穿戴计算的超低功耗惯性 MEMS

• 批准号: 1509063
• 负责人: Roozbeh Jafari
• 金额: $ 36万
• 依托单位: University of Texas at Dallas
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-15 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1509063&HistoricalAwards=false
• 关键词: Ultra; Low; Power; Inertial; MEMS

Ultra-Low Power Inertial MEMS for Pervasive Wearable ComputingBrief description of project Goals:The project enables ultra-low power accelerometers and gyroscopes for wearable computers with prolonged battery lifetime.Abstract:Nontechnical Advances in technology have led to the development of wearable sensing, computing and communication devices, enabling a large variety of new applications in several domains, including wellness and health care. Monitoring human movements and motor functions perhaps is considered one of the most important applications. Despite their tremendous potential to impact our lives, such systems face a number of hurdles to become a reality. The enabling sensors often demand a large amount of energy, requiring sizable batteries. This creates challenges for further miniaturization. The goal of this research is to enable ultra-low power sensors and DSP's for wearable computers operating with a very small power budget enabling weeks and months of battery lifetime. The proposed research will empower a large set of applications in health care and wellness domains including gait analysis, fall prevention and monitoring physical exercise. This project will ideally reduce the size and weight of wearable computers significantly, enabling many ubiquitous health monitoring applications. It can dramatically improve the quality of health monitoring practice and medical research, empowering more applications that are not currently feasible. This project targets a very important health care application for gait monitoring. Considering the importance of wearable gait monitoring applications and our efforts in reducing the form factor of the sensors that will justify their true ubiquitous use, semiconductor companies will produce billions of chips for wearable computers.TechnicalThe proposed research takes advantage of novel electromechanical designs and state of the art micromachining technologies to fabricate contact-based (full or tunneling) inertial sensors with overall dimensions in the hundreds of microns to a few millimeters. Such devices are essentially comprised of a number of acceleration switches requiring a small bias voltage of around 1V and no steady current flow to operate. The output of the sensor is turned ON/OFF by connecting/disconnecting the bias voltage to the device output electrode depending on the accelerations and/or rotation rates the device observes. This is contrary to the existing inertial sensors that provide an analog output requiring significant further processing in the analog domain with a power budget of 1mW which turns out to be the bottleneck. The proposed new class of devices can be directly interfaced with digital readout/control electronics. The proposed research will also enable a new set of methodologies that co-jointly perform the signal processing and optimize the power of sensors and digital circuitry by controlling the sampling frequency and bit resolution of sensors in real-time. The proposed research will be validated in the context of an important health monitoring application: gait analysis using wrist-worn and shoe-worn sensors.

超低功耗惯性MEMS的普及可穿戴ComputingBrief项目目标的描述：该项目使超低功耗加速度计和陀螺仪的可穿戴计算机与延长电池寿命。摘要：非技术的技术进步导致了可穿戴传感，计算和通信设备的发展，使大量的各种新的应用在几个领域，包括健康和医疗保健。监测人体运动和运动功能可能被认为是最重要的应用之一。尽管这些系统具有影响我们生活的巨大潜力，但要成为现实还面临许多障碍。使能传感器通常需要大量的能量，需要相当大的电池。这为进一步小型化带来了挑战。这项研究的目标是使超低功耗传感器和DSP的可穿戴计算机运行在一个非常小的功率预算，使电池寿命数周和数月。拟议的研究将为医疗保健和健康领域的大量应用提供支持，包括步态分析，跌倒预防和监测体育锻炼。该项目将理想地显著减小可穿戴计算机的尺寸和重量，从而实现许多无处不在的健康监测应用。它可以大大提高健康监测实践和医学研究的质量，使更多的应用程序，目前是不可行的。该项目针对步态监测的一个非常重要的医疗保健应用。考虑到可穿戴步态监测应用的重要性，以及我们在降低传感器外形尺寸方面所做的努力，这将证明传感器真正无处不在的使用是合理的，半导体公司将为可穿戴计算机生产数十亿芯片。技术拟议的研究利用新颖的机电设计和最先进的微加工技术，（全或隧穿）惯性传感器，其总体尺寸在几百微米到几毫米之间。这种器件基本上由多个加速开关组成，需要大约1V的小偏置电压，并且没有稳定的电流流动来操作。根据设备观察到的加速度和/或旋转速率，通过连接/断开偏置电压到设备输出电极来打开/关闭传感器的输出。这与现有的惯性传感器相反，现有的惯性传感器提供的模拟输出需要在模拟域中进行大量的进一步处理，功率预算为1 mW，这是瓶颈。所提出的新类别的设备可以直接与数字读出/控制电子接口。拟议的研究还将实现一套新的方法，通过实时控制传感器的采样频率和位分辨率，共同执行信号处理并优化传感器和数字电路的功率。所提出的研究将在一个重要的健康监测应用的背景下进行验证：使用腕戴和鞋戴传感器的步态分析。