Power-aware sensor interfacing and signal processing using nonlinear analog techniques

使用非线性模拟技术的功耗感知传感器接口和信号处理

• 批准号: 1128478
• 负责人: Kofi Odame
• 金额: $ 32.14万
• 依托单位: Dartmouth College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1128478&HistoricalAwards=false
• 关键词: Power; aware; sensor; interfacing; signal

The objective of this research is to discover a new class of ultra low power sensors. The approach is to develop nonlinear adaptive schemes that circumvent the tradeoffs faced by linear, time-invariant systems. This research aims at facilitating applications like mobile health, which rely on sensors with a limited power budget. In particular, this research will enable the brain-controlled cochlear implant - a next generation neural prosthetic that addresses the long-standing problem of speech intelligibility in a noisy background.Intellectual Merit: Nonlinear analysis can identify those regions of sensor data that are critical for an application's computations and state changes. Further, an adaptive system can adjust its parameters and resource consumption to specifically accommodate such computationally-relevant data, while discarding the remaining, less relevant data. These nonlinear and adaptive schemes result in very power-efficient sensors, and the proposed project will realize them by methodically harnessing the inherent nonlinear dynamics of analog components. In this way, the project aims to advance the field of low power sensor design.Broader Impacts: The mobile health devices that this project enables will promote a preventative, decentralized model of health-care delivery. This could allay the rising cost of health care. The project will integrate nonlinear systems thinking into engineering teaching through outreach programs and interdisciplinary workshops that are already thriving at Dartmouth College. The project's health applications will demonstrate that engineering is a human-focused occupation. This is relevant to women and minorities who, it has been suggested, avoid engineering because of its perceived disconnect with direct human concerns.

这项研究的目的是发现一种新型超低功耗传感器。该方法旨在开发非线性自适应方案，以规避线性时不变系统所面临的权衡。这项研究旨在促进移动健康等依赖于功率预算有限的传感器的应用。特别是，这项研究将使大脑控制的人工耳蜗成为可能，这是一种下一代神经假体，可以解决嘈杂背景下长期存在的语音清晰度问题。 智力优点：非线性分析可以识别对应用程序的计算和状态变化至关重要的传感器数据区域。此外，自适应系统可以调整其参数和资源消耗，以专门适应此类计算相关的数据，同时丢弃剩余的不太相关的数据。这些非线性和自适应方案产生了非常节能的传感器，并且所提出的项目将通过系统地利用模拟组件固有的非线性动力学来实现它们。通过这种方式，该项目旨在推进低功耗传感器设计领域的发展。 更广泛的影响：该项目支持的移动医疗设备将促进预防性、分散的医疗保健服务模式。这可以缓解不断上涨的医疗费用。该项目将通过达特茅斯学院已经蓬勃发展的外展计划和跨学科研讨会，将非线性系统思维整合到工程教学中。该项目的健康应用将证明工程是一项以人为本的职业。这与女性和少数族裔有关，有人建议她们避免工程学，因为人们认为工程学与人类的直接关注脱节。