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Bladder Volume Awareness for Individuals Living with Spinal Cord Injury

脊髓损伤患者的膀胱容量意识

基本信息

批准号：
1937158
负责人：
Soheil Ghiasi
金额：
$ 38.99万
依托单位：
University of California-Davis
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-03-01 至 2024-02-29
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1937158&HistoricalAwards=false
关键词：
Bladder Volume Awareness Individuals Living

项目摘要

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.

在美国，大约有30万人患有脊髓损伤（SCI）。虽然这些人中的许多人在行动方面有明显的限制，但公众不知道的是，几乎所有人都缺乏对膀胱的控制，不得不使用导尿管，通常每天4到6次，以排空膀胱。这种高频率的排空增加了“伤害的侮辱”。一个常见的问题是，坐在轮椅上厕所很困难，或者要求护理人员帮助发现膀胱中只有少量的尿液，或者没有及时去厕所，因为膀胱太满而漏尿。膀胱充盈感的缺乏是脊髓损伤患者的主要问题，严重影响了患者的社会活动和生活质量，增加了患者的护理复杂性和成本。为了解决这一问题，该项目旨在制造一种非侵入式可穿戴设备，可以让SCI患者在衣服下小心翼翼地佩戴，以便在开始寻找浴室进行自我或辅助导尿时及时接收（或发送给护理人员）警报。每当脊髓损伤患者或其护理人员对该装置的性能提供反馈时，该装置的准确性就会自动地逐步提高。此外，该项目还包括具体的教育和外展活动，这些活动将研究成果纳入课程，并招募和留住来自代表性不足背景的学生进入STEM教育。特别值得注意的是，通过加州大学戴维斯分校的CSTEM中心和萨克拉门托地区科学与工程博览会，他们努力接触当地的高中生和中学生、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，这通常导致通常不需要或太晚的预定导尿。因此，本项目的目标是开发一种非侵入性的贴片式设备，SCI患者可以佩戴该设备，以便在开始寻找浴室进行导尿时及时收到警报。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，利用一组发光二极管（led）和固定距离的光电探测器来推断膀胱空间扩张的信息。该装置利用的基本物理原理是测量波长上的背散射光，其中水具有适当的吸收系数，而其他组织发色团不具有高度吸收（例如，975 nm）。该设备将被设计为佩戴在骨盆区域的下腹，在电池的支持下至少可以运行一整天，非常灵活，面积大约是信用卡的两倍，厚度只有几毫米。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。光在膀胱模型中的传播蒙特卡罗模拟将用于估计候选设计的质量，并将开发基于LED/探测器数量和探头尺寸的成本函数。第二个目标是建立和训练用于膀胱填充状态预测的机器学习模型。在确定应该使用哪些特征和算法时，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。算法将首先研究其输出离散结果的能力，例如，警报（膀胱体积足够高）或无警报（膀胱体积过低）。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期望的精度水平，那么将使用使用不同核选择的核技巧的更复杂的非线性支持向量机。同样，回归方法的可能性，可以预测膀胱容量从收集的特征将进行研究。算法也将被设计为自动和自适应地确定下一次测量漫射光信号的时间实例，并结合用户的反馈，以不断提高设备的预测精度。第三个目标是评估该方法在25名健康和25名SCI人类受试者的短期和长期研究中的可行性。评估计划包括收集患者/护理人员对用户在使用设备时可能面临的实际问题的真实反馈，并收集足够数量的数据用于开发预测模型。该奖项反映了美国国家科学基金会的法定使命，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。