CAREER: Enhancing ambient capacitive sensing through improved resolution and multi-modal sensor fusion

职业：通过提高分辨率和多模式传感器融合增强环境电容传感

• 批准号: 2237945
• 负责人: Alexander Nelson
• 金额: $ 50万
• 依托单位: University of Arkansas
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-15 至 2028-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2237945&HistoricalAwards=false
• 关键词: CAREER; Enhancing; ambient; capacitive; sensing

One important part of recovering from strokes and managing other nervous system conditions is neurorehabilitation to help people recover from physical impairments to their posture and mobility. During rehabilitation sessions, therapists carefully monitor motions and give feedback to improve motor function and control. Being able to continue this monitoring and feedback outside of rehabilitation sessions could be a valuable addition to therapy; however, existing technologies for continuous body pose and motion estimation have many limitations. This proposal’s goal is to develop new techniques for pose and motion estimation based on capacitive sensor arrays (CSAs), a common technology used in devices such as smartphones. These new techniques will examine how both sensors in the environment and flexible, body-worn sensors can be used to better estimate pose and motion. The work will include developing new ways to configure and deploy CSAs, process the signals they send back, and combine multiple types of sensors. The project will focus on upper body pose and motion detection, particularly people’s arms, but the insights and methods are likely to apply to a wide range of medical applications and more generally provide new ways to interact with computers. In particular, the outcomes of the work may both help therapists develop new training procedures and support remote physical therapy that would make it more accessible to people who live in non-urban areas.This project seeks to demonstrate the feasibility of embedded and wearable CSAs and e-field sensors to provide accurate, continuous pose estimation beyond the state of the art. To do this, the team will address existing open challenges of non-touch wearable CSAs; namely 1) improving sensor resolution, 2) reducing error due to variable positioning, and 3) compensating for electrode shift. Specifically, sensor resolution in wearable systems will be improved by creating tailored capacitive arrays for pose estimation, augmenting the resolution of the sensors and improving noise filtering through deep transfer learning, and compensating for errors by augmenting the data with additional sensing mechanisms. These contributions will be evaluated through task-based remote neurorehabilitation training for people with upper limb impairments, which is currently lacking support for long-term and in-the-wild motor assessment. If successful, the work promises to increase the duration, quality, and accessibility of neurorehabilitation for the nearly 800,000 individuals experiencing strokes each year in the U.S. alone.This project is jointly funded by Human Centered Computing (HCC) and the Established Program to Stimulate Competitive Research (EPSCoR).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

中风和其他神经系统疾病康复的一个重要部分是神经康复，帮助人们从身体损伤中恢复姿势和活动能力。在康复治疗期间，治疗师会仔细监测运动并提供反馈，以改善运动功能和控制能力。康复训练之外的监测和反馈可能是治疗的一个有价值的补充；然而，现有的连续身体姿势和运动估计技术有许多局限性，该提案的目标是开发基于电容传感器阵列（CSAs）的姿势和运动估计新技术。 ),这些新技术将研究如何使用环境中的传感器和灵活的穿戴式传感器来更好地估计姿势和运动。这项工作将包括开发配置和部署 CSA 的新方法。 ，处理它们发回的信号，并结合多种类型的传感器，该项目将重点关注上身姿势和运动检测，特别是人的手臂，但这些见解和方法可能适用于广泛的医疗应用。提供与计算机交互的新方式，特别是结果。这项工作的一部分既可以帮助治疗师开发新的培训程序，也可以支持远程物理治疗，使居住在非城市地区的人们更容易获得治疗。该项目旨在证明嵌入式和可穿戴式 CSA 和电场传感器的可行性提供超越现有技术的准确、连续的姿态估计为此，该团队将解决非触摸式可穿戴 CSA 的现有挑战，即 1) 提高传感器分辨率，2) 减少由于可变定位引起的误差，以及 3)补偿电极位移。这些贡献将通过创建用于姿态估计的定制电容阵列、增强传感器的分辨率、通过深度迁移学习改进噪声过滤、以及通过基于任务的远程评估的附加传感机制来增强数据来专门补偿错误来改进。针对上肢障碍人士的神经康复训练，目前缺乏长期和野外运动评估的支持，如果成功，这项工作有望提高训练的持续时间、质量和可及性。仅在美国，每年就有近 800,000 名中风患者接受神经康复治疗。该项目由以人为中心的计算 (HCC) 和刺激竞争性研究既定计划 (EPSCoR) 联合资助。该奖项反映了 NSF 的法定使命，并被认为是值得的通过使用基金会的智力优势和更广泛的影响审查标准进行评估来获得支持。