Automated Seizure Detection for Home Seizure Monitoring with Epilog Sensors

摘要 AURA是一个数字健康平台，它使用Epiog™，这是一种微型、无线、可穿戴的脑电传感器，戴在 发际线以下的头皮可以记录临床和亚临床癫痫发作。在被初步诊断为癫痫后， 癫痫专家将使用有关患者癫痫发作的已知信息来指导最佳头皮位置，以放置 Epiog EEG传感器(A)。脑电数据被连续传输(B)到个人智能手机上的Aura应用程序(C) 使用安全蓝牙TM，通过WiFi(D)与Aura云平台(E)通信。癫痫脑电信号是 对癫痫发作进行分析，并与癫痫专家(F)共享每日数字发作日记，并将其推回 AURA APP(G)。Epiog每天充电，并可重复使用一年。Epiog被设计为谨慎的，允许 在日常生活的方方面面持续使用。 数据是S的10个片段，显示了伴有运动障碍和完整意识(ILAE)的局灶性癫痫发作的开始 1a1)由安放在左前额上的埃皮特尔的单通道癫痫传感器记录。病人住进了医院。 用于视频脑电监测，作为标准护理。这次癫痫发作由三位癫痫专家独立核实。 在第一阶段，基于机器学习的自动化癫痫检测算法将首先在 Aura Cloud可以在癫痫脑电波中检测癫痫发作，包括一个人可能不自觉地知道自己是癫痫发作 发作(占所有癫痫发作的50%)，如在睡觉时。AURA将运行这些专门为 Epiog的单通道脑电提供了每日的数字癫痫日记。 在第二阶段，Aura系统将作为基于脑电的自动化系统进入FDA批准的临床验证试验 家居癫痫检测和报警系统。在早期的第二阶段，Aura将作为一种医疗产品进行商业化 支持设备的服务业务模式。癫痫患者的自付费用平均为 380美元/年。有了长期的、可重现的脑电，癫痫专家现在将有一个更精确、更定量的 记录癫痫发作次数，使他们能够更快、更成功地适应患者的治疗以改善 生活质量。AURA将让癫痫患者恢复他们的生活。AURA提供了你所在的位置的确定性 当你需要的时候。在整个第二阶段，生理、心理、行为和环境因素 将在Aura应用程序中结合起来，从300名患者收集27,000天的多模式数据，以创建 史无前例的已知可导致癫痫发作的特征数据集。 这些数据将在第三阶段用于创建一个强大的、可穿戴的癫痫发作预测系统，该系统使用人工智能 结合多种模式癫痫发作诱发因素的情报，创造每小时癫痫发作的概率。 AURA将深刻地扰乱癫痫的管理方式，并提高癫痫患者的生活质量。

ABSTRACT Aura is a digital health platform that uses Epilog™, a miniature, wireless, wearable EEG sensor worn on the scalp below hairline that can record clinical and subclinical seizures. After an initial diagnosis of epilepsy, an epileptologist will use known information about patients’ seizures to guide the best scalp location to place the Epilog EEG sensor (A). EEG data is continuously transferred (B) to the Aura app on a person’s smartphone (C) using secure BluetoothTM where it communicates over WiFi (D) to the Aura cloud platform (E). Epilog EEG is analyzed for seizures and a daily digital seizure diary is shared with epileptologists (F) and pushed back to the Aura app (G). Epilog is recharged daily, and reusable for a year. Epilog is designed to be discreet, allowing for continuous use in all facets of daily life. Data are a 10 s snippet of the beginning of a focal seizure with motor impairment and intact awareness (ILAE 1A1) recorded from Epitel’s single-channel Epilog sensor placed on the left forehead. The patient was admitted for video-EEG monitoring as standard-of-care. This seizure was verified independently by three epileptologists. In Phase I, automated, machine learning-based seizure detection algorithms will be designed to first work in the Aura cloud to detect seizures in Epilog EEG, including seizures a person may not consciously know they are having (>50% of all seizures), such as while sleeping. Aura will run these algorithms developed exclusively for Epilog’s single-channel of EEG to provide a daily digital seizure diary. In Phase II, the Aura system will enter clinical validation trials for FDA clearance as an EEG-based automated home seizure detection and alerting system. Early in Phase II Aura will be commercialized as a medical device-enabled-service business model. Out-of-pocket costs for a person living with epilepsy is an average of $380/year. Armed with long-term, reproducible EEG, epileptologists will now have a more precise, quantitative record of seizure counts, enabling them to adapt patient treatment more rapidly and successfully to improve quality of life. Aura will give people living with epilepsy their lives back. Aura provides certainty where you are and when you need it. Throughout Phase II, physiological, psychological, behavioral, and environmental factors will be combined in the Aura app to collect 27,000 days of multi-modal data from 300 patients to create an unprecedented dataset of features known to precipitate seizures. These data will be used in Phase III to create a robust, wearable seizure forecasting system using artificial intelligence that combines multi-modal seizure precipitating factors, creating an hourly seizure probability. Aura will profoundly disrupt how epilepsy is managed and improve the quality of life of people living with epilepsy.