I-Corps: A smart ring for finger motion analytics and healthcare applications

这个I-Corps项目的更广泛的影响/商业潜力是开发一个智能戒指，该戒指具有集成传感器，用于延展实境和智能医疗保健。所提出的技术可用于远程监测患者的健康生物特征数据，包括心率、氧饱和度、血压、血糖、血液酒精浓度和室内位置。这可以改善健康问题的早期检测，跟踪和改善健康和保健，并减少用于监测患者的人力资源。 此外，所提出的智能戒指技术可以用于帮助失聪和听力困难的个体与听力正常的个体进行通信。 所提出的技术设计了一个集成的手语识别（SLR）系统。 目前，美国的聋人和重听人口约为1000万，全球约为4.66亿，但不存在有效的沟通工具。 这项技术可以满足聋人和听力障碍社区的重要需求。这个I-Corps项目是基于3D手指运动跟踪智能戒指的开发。 所提出的技术是通过将使用片上系统（SoC）架构的低成本、现成的电子元件集成到可以以环形形状因子弯曲的柔性印刷电路板中来设计的。内置惯性测量单元（IMU）和光电容积描记（PPG）传感器，用于实现运动分析，如手语识别和医疗保健应用，如心率、血氧饱和度、血压、血液酒精浓度和血糖。硬件被封装在3D打印的防水外壳中，可以与皮肤平滑接触。总的来说，它的重量约为2.5克，电池续航时间为一周，可以舒适地长期佩戴，包括睡觉和游泳。结果表明，使用稀疏的戒指放在几个手指上的手指运动跟踪24个自由度的可行性。这是一个无约束的问题，没有格式良好的方程，因为传感器没有放置在每个手指或关节。深度学习技术用于学习传感器数据和手指运动之间的映射，利用不同手指运动之间的相关性来解决无约束问题。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而被认为值得支持。

The broader impact/commercial potential of this I-Corps project is the development of a smart ring with integrated sensors for applications in extended reality and smart healthcare. The proposed technology may be used to monitor patients’ health biometric data including heart rate, oxygen saturation, blood pressure, blood glucose, blood alcohol concentration and indoor location remotely. This may improve early detection of health issues, track and improve health and wellness, and reduce human resources devoted to the monitoring of patients. In addition, the proposed smart ring technology may be used to help deaf and hard of hearing individuals communicate with hearing individuals. The proposed technology is designed with an integrated sign language recognition (SLR) system. Currently, the population of deaf and hard of hearing individuals is about 10 million in the US and 466 million globally, however, an efficient communication tool does not exist. The proposed technology could serve an important need for the deaf and hard of hearing community.This I-Corps project is based on the development of a 3D finger motion tracking smart ring. The proposed technology is designed by integrating low-cost, off-the-shelf electronic components using system-on-a-chip (SoC) architecture into a flexible printed circuit board that can bend in the form factor of a ring. Inertial measurement unit (IMU) and photoplethysmography (PPG) sensors are embedded for enabling motion analytics such as sign language recognition and healthcare applications such as heart rate, oxygen saturation, blood pressure, blood alcohol concentration and blood glucose. The hardware is enclosed in a 3D-printed waterproof case that allows smooth contact with the skin. Overall, the form factor weighs about 2.5 g with a week of battery life for comfortable and long-term wearing including while sleeping and swimming. Results show the feasibility of tracking 24 degrees of freedom of finger motion using sparse rings placed on a few fingers. This is an unconstrained problem without well-formed equations because the sensors are not placed on every finger or joint. Deep learning techniques are utilized to learn the mapping between sensor data and finger motion that exploit correlations between motion of different fingers to solve the unconstrained problem.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.