Bladder Volume Awareness for Individuals Living with Spinal Cord Injury

在美国，大约有30万人患有脊髓损伤（SCI）的后果。虽然这些人中的许多人在移动性方面有明显的限制，但公众不知道的是，几乎所有人都缺乏对膀胱的控制，并且必须使用导管，通常每天4至6次，以排空膀胱。如此频繁的清空更是雪上加霜。“一个常见的问题是，坐在轮椅上去浴室很困难，或者请求护理人员的帮助，只在膀胱里找到少量的尿液，或者因为膀胱太满而不能及时去浴室，导致尿液泄漏。缺乏膀胱充盈感是SCI患者的一个主要问题，这大大减少了他们的社会活动和生活质量，并增加了他们的护理复杂性和成本。为了解决这个问题，该项目旨在建立一个非侵入性的可穿戴设备，它可以被SCI患者谨慎地戴在衣服下面，以接收（或发送给他们的护理人员）开始寻找浴室进行自我或辅助导管插入的及时警报。 每当SCI受试者或他/她的护理者提供关于其性能的反馈时，该设备的准确性将自动地并且逐渐地改进。 此外，该项目还包括具体的教育和外联活动，这些活动是通过将研究成果纳入课程以及招募和保留来自代表性不足背景的学生进入STEM教育来推动的。特别值得注意的是，通过加州大学戴维斯分校CSTEM中心和萨克拉门托地区科学工程博览会，努力接触当地的高中和初中学生，家长和他们的老师&。大多数脊髓损伤（SCI）患者患有神经源性下尿路功能障碍（NLUTD），缺乏对膀胱的感觉和控制，这通常会导致计划的导管插入术通常不需要或为时已晚。 因此，该项目的目标是开发一种非侵入性的贴片式设备，可以由SCI患者佩戴，以便在开始寻找浴室进行导管插入时及时收到警报。该研究计划有三个目标：第一个目标是利用近红外光谱（NIRS）的原理来构建一种设备，该设备利用发光二极管（LED）阵列和固定距离的光电探测器来推断有关膀胱空间扩张的信息。该装置利用的基本物理原理是测量在水具有适当吸收系数的波长处的反向散射光，而其他组织发色团不是高度吸收的（例如，975 nm）。 该设备将被设计为谨慎地佩戴在骨盆区域的下腹上，依靠电池运行至少一整天，非常灵活，面积约为信用卡的两倍，并且只有几毫米厚。 将研究系统复杂性和对患者有用性之间的基本权衡，例如，光学探头中LED和光电探测器的数量、LED驱动电流和电池尺寸。将使用膀胱模型中光传播的蒙特卡罗模拟来估计候选设计的质量，并将开发基于LED/探测器数量和探针尺寸的成本函数。 第二个目标是建立和训练用于膀胱充盈状态预测的机器学习模型。 在确定应使用哪些功能和算法时，将考虑算法复杂性、预测准确性、能耗和对SCI患者的价值主张之间的设计权衡。 首先将研究算法输出离散结果的能力，例如，警报（膀胱容量足够高）或无警报（膀胱容量过低）。如果相对简单的算法，如逻辑回归和线性支持向量机（SVM）不能使用合理数量的特征达到所需的准确度水平，则将使用使用具有不同内核选择的内核技巧的更复杂的非线性SVM。 类似地，将研究可以从收集的特征预测膀胱体积的回归方法的可能性。算法还将被设计为自动和自适应地确定测量漫射光信号的下一个时间实例，并结合用户的反馈，以不断提高设备的预测精度。 第三个目标是在25名健康和25名SCI人类受试者的短期和一天的研究中评估该方法的可行性。评估计划包括收集真实的患者/护理人员对实际问题的反馈，这些问题是用户在使用设备时将面临的，并收集足够数量的数据用于开发预测模型。该奖项反映了NSF的法定使命，并被认为值得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来支持。

Approximately 300,000 individuals in the US suffer from the consequences of spinal cord injury (SCI). Although many of these individuals have obvious limitations in mobility, unbeknownst to the general public is that nearly all lack control of their bladder and have to use catheters, typically 4 to 6 times per day, to empty their bladder. This high frequency of emptying adds "insult to injury." A common problem is making the difficult trip to the bathroom in a wheelchair or requesting help from a caregiver to only find a small amount of urine in the bladder, or not making it to the bathroom in time and leaking urine because the bladder was too full. Lack of the bladder fullness sensation is a major problem for individuals living with SCI, which significantly reduces their social activities and quality of life and increases their care complexity and cost. To address this problem, the project aims to build a non-invasive wearable device, which can be discreetly worn by SCI patients under their clothing, to receive (or to send to their caregivers) timely alerts for starting to look for a bathroom to perform self- or assisted-catheterization. The accuracy of the device will automatically and incrementally improve every time the SCI subject or his/her caregiver provides feedback on its performance. Furthermore, the project includes specific education and outreach activities that are driven by integration of research results into courses and recruitment and retention of students from underrepresented backgrounds into STEM education. Of particular note are efforts to reach out to local high school and middle school students, parents, and their teachers via the UC-Davis CSTEM center and the Sacramento Regional Science & Engineering Fair.Most individuals living with spinal cord injury (SCI) have neurogenic lower urinary tract dysfunction (NLUTD) and lack sensation and control of their bladder, which typically leads to scheduled catheterizations that are often not needed or are too late. Thus, the goal of this project is to develop a non-invasive, patch-like device that can be worn by SCI patients to receive timely alerts for starting to look for a bathroom to perform catheterization. The Research Plan is organized under three aims: The FIRST Aim is to leverage the principles of near infrared spectroscopy (NIRS)to build a device that utilizes an array of light-emitting diodes (LEDs) and photodetectors with fixed distances to infer information about spatial expansion of the bladder. The underlying physical principle exploited by the device is measurement of back scattered light at wavelengths for which water has an appropriate absorption coefficient, while other tissue chromophores are not highly absorptive (e.g., 975 nm). The device will be designed to be worn discreetly on the lower abdomen in the pelvic area, to run on the battery for at least a full waking day, to be very flexible, to have an area about twice that of a credit card, and to be only a few millimeters thick. The fundamental tradeoffs between system complexity and usefulness to patients will be investigated, e.g., the number of LEDs and photodetectors in the optical probe, the LED driving current and the battery size. Monte Carlo simulations of light propagation in bladder models will be used to estimate the quality of design candidates, and a cost function based on the number of LED/detectors and probe size will be developed. The SECOND Aim is to build and train machine learning models for bladder fill state prediction. Design tradeoffs among algorithm complexity, prediction accuracy, energy consumptions, and value proposition to SCI patients will be considered in determining what features and algorithms should be used. Algorithms will first be investigated for their ability to output discrete outcomes, e.g., alert (bladder volume is high enough) or no alert (bladder volume is too low). If relatively simple algorithms such as logistic regression and linear support vector machine (SVM) do not achieve the desired level of accuracy using a reasonable number of features, more sophisticated nonlinear SVMs using kernel trick with different choices of kernels will be used. Similarly, the possibility of regression methods that can predict the bladder volume from the collected features will be investigated. Algorithms will also be designed to automatically and adaptively determine the next time instance for measuring the diffuse optical signal and to incorporate the user's feedback to continuously improve the device's prediction accuracy. The THIRD Aim is to evaluate the feasibility of the approach in both short and day-long studies in 25 healthy and 25 SCI human subjects. The evaluation plan includes collecting real patient/caregiver feedback on practical issues that users will face as the device is used and to collect sufficient amount of data for development of predictive models.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.