Ultra-Low Power Inertial MEMS for Pervasive Wearable Computing

用于普及可穿戴计算的超低功耗惯性MEMS项目目标简介：该项目实现了用于可穿戴计算机的超低功耗加速度计和陀螺仪，延长了电池寿命。摘要：技术上的非技术进步导致了可穿戴传感、计算和通信设备的发展，使许多领域的新应用得以实现，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。尽管它们有巨大的潜力影响我们的生活，但要成为现实，这些系统面临着许多障碍。使能传感器通常需要大量的能量，需要相当大的电池。这给进一步的小型化带来了挑战。这项研究的目标是为可穿戴计算机启用超低功率传感器和DSP，使其能够以非常小的电力预算运行，从而实现数周至数月的电池寿命。这项拟议的研究将支持医疗保健和健康领域的大量应用，包括步态分析、预防摔倒和监测体育锻炼。该项目将理想地显著减小可穿戴计算机的大小和重量，使许多无处不在的健康监测应用成为可能。它可以显著提高健康监测实践和医学研究的质量，使更多目前不可行的应用程序得以实现。该项目的目标是步态监测的一个非常重要的医疗保健应用。考虑到可穿戴式步态监测应用的重要性，以及我们在降低传感器外形系数方面所做的努力，半导体公司将为可穿戴式计算机生产数十亿个芯片。技术拟议的研究利用新颖的机电设计和最先进的微机械加工技术来制造基于接触式(全尺寸或隧道式)惯性传感器，总尺寸从数百微米到几毫米。这类器件基本上由许多加速开关组成，需要1V左右的小偏置电压，并且没有稳定的电流才能运行。根据器件观察到的加速度和/或旋转速度，通过将偏置电压连接/断开到器件输出电极来打开/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进行大量的进一步处理，而1 mW的功率预算被证明是瓶颈。建议的新型设备可以直接与数字读出/控制电子设备接口。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。拟议的研究将在一个重要的健康监测应用程序的背景下得到验证：使用手腕和鞋子穿着的传感器进行步态分析。

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.