I-Corps: Brain Health Monitoring via Phenotyping Electroencephalogram Data

这个i-Corps项目是基于深度学习算法开发的，该算法使用来自睡眠障碍和其他神经疾病患者的数据。我们创建了一个独特的深度神经网络，由卷积和递归模块组成，并在一组独特的10,000个临床多导睡眠图(PSG)结果上训练该模型，这是迄今为止世界上收集的临床多导睡眠图(PSG)的最大集合。这个I-Corps项目的更广泛影响/商业潜力围绕其简单性和准确性。对患者的好处是使他们和他们的家人能够舒适地进行准确的家庭测试。与此同时，医生将收到关于患者的实时诊断信息，从而更早地进行治疗。对于保险提供商和医院来说，随着结果的改善和所需资源和人员的减少，成本将大幅降低。除了医疗保健行业，我们的项目还将很好地转化为普通人群，在这些人群中，可穿戴设备和健康跟踪设备正变得司空见惯。能够评估一个人的睡眠框架，准确描述包括睡眠分期在内的多种特征，对消费者具有吸引力。该奖项反映了NSF的法定使命，并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，被认为值得支持。

This I-Corps project is based on deep learning algorithms developed using data from patients with sleep disorders and other neurological conditions. We created a unique deep neural network, composed of both a convolutional and recurrent modules, and trained the model on a unique set of 10,000 clinical polysomnography (PSG) results, the world's largest collection of clinical PSGs assembled to date.The broader impact/commercial potential of this I-Corps project revolves around its simplicity and accuracy. The benefit for patients is to enable them and their family members to perform accurate home testing with comfort. Meanwhile, physicians would receive real time diagnostic information about their patients, leading to earlier treatment. For insurance providers and hospitals, costs are drastically reduced as outcomes improve and fewer resources and staff are required. Apart from the healthcare industry, our project would also translate well into the general population, where wearables and health tracking devices are becoming commonplace. Being able to review the framework of one's sleep, with an accurate depiction of multiple characteristics including sleep staging, appeals to the consumer.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.