I-Corps: Artificial Intelligence-based mobile application to mitigate health risks of firefighters

这个i-Corps项目的更广泛的影响/商业潜力是开发基于人工智能(AI)的移动应用程序，以减少消防员的死亡。消防员在接到警报后突发心脏事件的可能性是非紧急任务的14倍，消防后突发心脏事件的可能性是非紧急任务的136倍。这项拟议的技术旨在使用商用个人无线可穿戴健康跟踪器监测消防员的生理数据，评估心血管风险因素，并就迫在眉睫的风险向消防员发出警报。这项拟议技术的目标是减少消防员的死亡率和与心血管疾病相关的发病率。大约92%的院外心脏骤停导致死亡，这表明许多人没有意识到这些症状，也没有根据早期预警信号采取行动。及早识别心血管健康风险(如高血压、心律失常、睡眠呼吸暂停)，增加姐妹染色单体交换的可能性，持续监测疾病进展，并及时处理风险，可能会增加预防或存活姐妹姐妹交换的机会。健康跟踪器成本低，可以持续跟踪生理数据(心率、睡眠行为)和身体活动(步数、旅行距离、楼层爬高)，并可以通过移动设备将这些数据无线上传到云中。长期的好处可能包括减少心脏病的发生率，这可能会导致更低的医疗成本，并提高消防员的安全。此外，拟议的技术可能会被普通民众使用，这可能会对社会产生广泛的健康益处。这个i-Corps项目基于为消防部门开发的移动软件应用程序，以减少因突发心脏事件(SCE)而导致的消防员死亡。拟议的技术利用了商业上可用的健康跟踪器技术，与人工智能(AI)模型相结合，这些模型已经使用消防员的健康数据进行了培训和开发，并使用消防部门的相关临床研究进行了定制。建议的软件以原生反应跨平台(iOS/Android)构建，并与深度学习模型集成，以远程诊断心律失常、高血压、心房颤动和睡眠呼吸暂停，这些都是消防数据中普遍存在的心血管风险因素，导致突发心脏事件-消防员发病率和在职死亡的主要原因(50%-60%)。拟议的物联网系统从可穿戴健康跟踪器捕获生理数据，并将其馈送到基于云的AI模型，以进行实时远程诊断。基于自定义风险阈值，当AI模型检测到健康风险时，可以通知用户。此外，拟议的软件应用程序的广泛延长使用还可以提供消防员生理数据的数据库，然后可以用来进一步完善技术，导致对灭火的生理和潜在病理反应的新理解，并刺激新的数据驱动的临床研究。这一奖项反映了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。

The broader impact/commercial potential of this I-Corps project is the development of an Artificial Intelligence (AI)-based mobile application to reduce firefighter deaths. Firefighters are fourteen times more likely to suffer a sudden cardiac event (SCE) in response to an alarm, and 136 times more likely to suffer a fatal SCE after firefighting than nonemergency duties. The proposed technology is designed to monitor the physiological data of firefighters using commercially available personal wireless wearable health trackers, evaluate cardiovascular risk factors, and alert the firefighter about impending risks. The goal for this proposed technology is to reduce firefighter mortalities and morbidities associated with cardiovascular disease. Approximately 92% of out-of-hospital cardiac arrests result in death suggesting that many people do not recognize the symptoms, and don’t act on early warning signs. Early identification of cardiovascular health risks (e.g., hypertension, arrhythmia, sleep apnea) that increase the possibility of SCE, continuous monitoring of disease progression, and addressing risks in a timely manner may increase the chances of preventing or surviving a SCE. The health trackers are low-cost, and can continuously track physiological data (heart rate, sleep behavior) and physical activity (step count, travel distance, floors climbed), and may be used to upload this data wirelessly to the cloud via a mobile device. Long-term benefits may include a decrease in cardiac incidence that may lead to lower healthcare costs and improve the safety of firefighters. In addition, the proposed technology may be used by the general population, which may have a broad health benefit to society.This I-Corps project is based on the development of a mobile software application for the fire service to reduce firefighter deaths due to sudden cardiac events (SCE). The proposed technology utilizes commercially available health tracker technology integrated with Artificial Intelligence (AI) models that have been trained and developed using firefighters’ health data and customized using relevant clinical studies from the fire service. The proposed software is built with react-native cross-platform (iOS/Android) and is integrated with deep learning models to remotely diagnose arrhythmia, hypertension, atrial fibrillation, and sleep apnea, which are prevalent cardiovascular risk factors in fire service data leading to sudden cardiac events – a leading cause (50-60%) of firefighter morbidity and on-duty deaths. The proposed Internet of Things system captures the physiological data from wearable health trackers and feeds it to cloud-based AI models for real-time remote diagnosis. Based on custom risk thresholds, the user may then be notified when a health risk is detected by the AI models. In addition, wide-spread prolonged usage of the proposed software application also may provide a database of firefighters’ physiological data that may then be used to further refine the technology, lead to new understandings of physiological, and potentially pathological, responses to firefighting, and stimulate new data-driven clinical research.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.