I-Corps: Intelligent wireless sensor network platform for extended human health monitoring

I-Corps：用于扩展人体健康监测的智能无线传感器网络平台

• 批准号: 2305389
• 负责人: Jan Rabaey
• 金额: $ 5万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2305389&HistoricalAwards=false
• 关键词: Corps; Intelligent; wireless; sensor; network

The broader impact/commercial potential of this I-Corps project is the development of a generic health monitoring platform that enables intelligent monitoring of physiological signals. This project aims to improve the battery life and privacy of wearable devices, enabling long-term monitoring for both personal health and medical conditions. The system applies to a variety of bio-parametric signals which could be used for general consumer health monitoring that informs users of their own health, motivating lifestyle changes, and detecting emergency conditions. The system also has applications in intensive care to improve the comfort of patients that are being monitored in the long-term by removing wires while maintaining a long lifetime. Monitoring of specific signals such as stress, emotion, sound, and motion can provide utility for military applications including soldier monitoring in the battlefield, soldier training, and post-traumatic diseases. The system could also be customized for specialized athletic sport monitoring or even for specialized medical conditions. For example, patients with chronic conditions like stroke recurrence could benefit from heart monitoring, temperature monitoring can predict immune response to viruses so patients can get treatment, and respiration tracking can predict the risk of an asthma attack. Overall, the system has the potential to improve health monitoring for the general public, and the ability for patients with chronic conditions to get treatment in advance of critical events.This I-Corps project is based on the development of an intelligent wireless sensor network platform for extended human health monitoring through in-sensor machine learning. The technology uses emerging brain-inspired Hyperdimensional Computing, which is characterized by very low computational complexity, to minimize net power consumption improving network lifetime, security, and privacy. The technology enables integration of a large number of low-power distributed sensors that wirelessly communicate intelligently detected events/classes. Current systems either transmit data to another device for processing, which is very costly in terms of power, or attempt to process locally with algorithms that are more expensive than the amount saved by reducing transmission. To solve these problems, this project utilizes the emerging brain-inspired Hyperdimensional Computing paradigm to minimize net power consumption of in-sensor computation. This paradigm represents information with fully binary vectors and thus the encoding of data patterns involves only simple binary operators such as right shifts, making it extremely computationally simple. The representation can be used for classification tasks through encoding training data into a prototype vector per class and then, during inference, comparing similarly encoded input data against the trained prototypes to find the closest class. Using this technology, this project can significantly improve sensor lifetime and also provide security and privacy due to the local computation. This project aims to develop a platform that takes advantage of these various elements for long-term monitoring.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.

这个I-Corps项目的更广泛的影响/商业潜力是开发一个通用的健康监测平台，能够智能监测生理信号。该项目旨在提高可穿戴设备的电池寿命和隐私，从而实现对个人健康和医疗状况的长期监测。该系统适用于各种生物参数信号，可用于一般消费者健康监测，告知用户自己的健康状况，激励生活方式的改变，并检测紧急情况。该系统还可应用于重症监护，通过移除导线同时保持较长的使用寿命来改善长期监测的患者的舒适度。对诸如压力、情绪、声音和运动的特定信号的监测可以为军事应用提供实用性，包括战场上的士兵监测、士兵训练和创伤后疾病。该系统还可以针对专门的体育运动监测或甚至针对专门的医疗状况进行定制。例如，患有中风复发等慢性疾病的患者可以从心脏监测中受益，温度监测可以预测对病毒的免疫反应，以便患者可以得到治疗，呼吸跟踪可以预测哮喘发作的风险。总的来说，该系统有潜力改善公众的健康监测，以及慢性病患者在关键事件发生前获得治疗的能力。这个I-Corps项目是基于智能无线传感器网络平台的开发，通过传感器内机器学习进行扩展的人类健康监测。该技术使用新兴的大脑启发超维计算，其特点是计算复杂度非常低，以最大限度地减少净功耗，提高网络寿命，安全性和隐私。该技术可以集成大量低功耗分布式传感器，这些传感器可以无线通信智能检测到的事件/类别。当前的系统要么将数据传输到另一个设备进行处理，这在功率方面非常昂贵，要么尝试使用比通过减少传输节省的量更昂贵的算法进行本地处理。为了解决这些问题，该项目利用新兴的大脑启发超维计算范式，以最大限度地减少传感器内计算的净功耗。这种范式用完全二进制向量表示信息，因此数据模式的编码只涉及简单的二进制运算符，如右移位，使其在计算上非常简单。该表示可以用于分类任务，通过将训练数据编码到每个类的原型向量中，然后在推理期间，将类似编码的输入数据与训练的原型进行比较，以找到最接近的类。使用这种技术，该项目可以显着提高传感器的寿命，并提供安全性和隐私，由于本地计算。该项目旨在开发一个平台，利用这些不同的元素进行长期监测。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。