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
基本信息
- 批准号:1649167
- 负责人:
- 金额:$ 36万
- 依托单位:
- 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:2015-08-09 至 2020-07-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
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.
超低功率惯性mems用于广泛可穿戴的计算机描述项目目标:该项目可实现超低功率加速度计和陀螺仪,用于延长电池寿命的可穿戴计算机。删除:非技术技术进步导致了可穿戴,计算和通信设备的开发,包括新的多种多样的应用程序,包括多种多样的应用程序,并在各种各样的应用程序中进行了多种多样的启动。监测人类运动和运动功能可能被认为是最重要的应用之一。尽管它们具有影响我们生活的巨大潜力,但这种系统面临许多障碍,成为现实。启用传感器通常需要大量的能量,需要相当的电池。这为进一步的小型化带来了挑战。这项研究的目的是启用超低功率传感器和DSP,用于可穿戴计算机,功率预算非常小,可以使电池寿命数周和几个月。拟议的研究将赋予医疗保健和保健领域的大量应用,包括步态分析,预防和监测体育锻炼。理想情况下,该项目将大大减少可穿戴计算机的大小和重量,从而实现许多无处不在的健康监测应用程序。它可以大大提高健康监测实践和医学研究的质量,从而赋予更多目前不可行的应用程序。该项目针对步态监测非常重要的医疗保健应用。考虑到可穿戴步态监控应用的重要性以及我们在降低传感器形式的努力,这将证明其真正的无处不在使用,半导体公司将生产数十亿个用于可穿戴计算机的芯片。拟议的研究提议的研究利用了新颖的机械机械设计和整体触发器(整体上)(整体上)(整体上)的脉动(整体上)(interials)(整体上)。给几毫米。此类设备基本上由许多加速开关组成,需要小偏置电压约为1V,并且没有稳定的电流流动。通过将偏置电压连接到设备输出电极,取决于设备观察到的加速度和/或旋转率,传感器的输出将打开/关闭。这与现有的惯性传感器相反,该传感器提供了一个模拟输出,需要在模拟域中以1MW的功率预算进行进一步的处理,而模拟域中,这是瓶颈。拟议的新设备可以直接与数字读数/控制电子设备连接。拟议的研究还将启用一组新的方法,这些方法可以通过控制传感器实时的采样频率和位分辨率来共处执行信号处理,并优化传感器和数字电路的功率。拟议的研究将在重要的健康监测应用程序的背景下进行验证:使用腕部戴和鞋子的传感器进行步态分析。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Roozbeh Jafari其他文献
Pulse2AI: An Adaptive Framework to Standardize and Process Pulsatile Wearable Sensor Data for Clinical Applications
Pulse2AI:用于标准化和处理临床应用脉动可穿戴传感器数据的自适应框架
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:5.8
- 作者:
Sicong Huang;Roozbeh Jafari;Bobak J. Mortazavi - 通讯作者:
Bobak J. Mortazavi
ArterialNet: Arterial Blood Pressure Reconstruction
ArterialNet:动脉血压重建
- DOI:
10.1109/bhi58575.2023.10313518 - 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Sicong Huang;Roozbeh Jafari;Bobak J. Mortazavi - 通讯作者:
Bobak J. Mortazavi
Wearable Bioimpedance Sensor Characterization for Blood Flow Monitoring
用于血流监测的可穿戴生物阻抗传感器表征
- DOI:
10.1109/biocas58349.2023.10388901 - 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Kaan Sel;Seyed Ali Ghazi Asgar;Deen Osman;Peiyun Wu;Roozbeh Jafari - 通讯作者:
Roozbeh Jafari
Early adverse physiological event detection using commercial wearables: challenges and opportunities
使用商用可穿戴设备进行早期不良生理事件检测:挑战与机遇
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:15.2
- 作者:
Jesse Phipps;Bryant Passage;Kaan Sel;Jonathan Martinez;Milad Saadat;Teddy Koker;Natalie Damaso;Shakti Davis;Jeffrey Palmer;Kajal T. Claypool;Christopher Kiley;Roderic I Pettigrew;Roozbeh Jafari - 通讯作者:
Roozbeh Jafari
Roozbeh Jafari的其他文献
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{{ truncateString('Roozbeh Jafari', 18)}}的其他基金
RAPID: Electronic Tattoos for Detection of Pre-symptoms of Infection
RAPID:用于检测感染前期症状的电子纹身
- 批准号:
2031674 - 财政年份:2020
- 资助金额:
$ 36万 - 项目类别:
Standard Grant
Design of Motion-Artifact Robust Electronic Tattoos and Software Reconfiguration Methodologies for Bio-impedance Sensing
用于生物阻抗传感的运动神器鲁棒电子纹身和软件重构方法的设计
- 批准号:
1738293 - 财政年份:2017
- 资助金额:
$ 36万 - 项目类别:
Standard Grant
CAREER: CSR Ultra Low Power Architectures for Wearable Computing
职业:适用于可穿戴计算的 CSR 超低功耗架构
- 批准号:
1734039 - 财政年份:2016
- 资助金额:
$ 36万 - 项目类别:
Continuing Grant
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 - 财政年份:2015
- 资助金额:
$ 36万 - 项目类别:
Standard Grant
Mentorship and Student-Author Travel Grant for Wireless Health 2012 Conference
2012 年无线健康会议的指导和学生作者旅费资助
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1261409 - 财政年份:2013
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$ 36万 - 项目类别:
Standard Grant
I-Corps: Self Calibration Techniques for Robust Brain Computer Interface
I-Corps:稳健脑机接口的自校准技术
- 批准号:
1338964 - 财政年份:2013
- 资助金额:
$ 36万 - 项目类别:
Standard Grant
CAREER: CSR Ultra Low Power Architectures for Wearable Computing
职业:适用于可穿戴计算的 CSR 超低功耗架构
- 批准号:
1150079 - 财政年份:2012
- 资助金额:
$ 36万 - 项目类别:
Continuing Grant
EAGER: Methodologies for Tight Integration of Physical and Cyber Models in Power Aware Wearable Computers
EAGER:在功率感知可穿戴计算机中紧密集成物理模型和网络模型的方法
- 批准号:
1138396 - 财政年份:2011
- 资助金额:
$ 36万 - 项目类别:
Standard Grant
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