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

这个I-Corps项目更广泛的影响/商业潜力是开发基于人工智能（AI）的移动的应用程序，以减少消防员的死亡。消防员在接到警报后发生突发心脏事件（SCE）的可能性是非紧急任务的14倍，在消防后发生致命SCE的可能性是非紧急任务的136倍。 该技术旨在使用商用个人无线可穿戴健康追踪器监测消防员的生理数据，评估心血管风险因素，并提醒消防员即将发生的风险。这项技术的目标是减少消防员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，这表明许多人没有认识到症状，也没有对早期预警信号采取行动。早期识别心血管健康风险（例如，高血压、心律失常、睡眠呼吸暂停），持续监测疾病进展，及时处理风险，可能会增加预防SCE或生存的机会。健康追踪器是低成本的，并且可以连续地追踪生理数据（心率、睡眠行为）和身体活动（步数、行进距离、爬过的楼层），并且可以用于经由移动终端将该数据无线地上传到云。 长期的好处可能包括心脏病发病率的降低，这可能导致医疗保健成本的降低，并提高消防员的安全性。 此外，所提出的技术可用于一般人群，这可能有一个广泛的健康效益society.This I-Corps项目是基于消防服务的移动的软件应用程序的开发，以减少消防员死亡，由于突发心脏事件（SCE）。 该技术利用了商业上可用的健康跟踪器技术，该技术与人工智能（AI）模型集成，这些模型已经使用消防员的健康数据进行了训练和开发，并使用消防服务的相关临床研究进行了定制。 拟议的软件采用react-native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，房颤和睡眠呼吸暂停，这些是消防数据中常见的心血管风险因素，导致突发心脏事件-消防员发病和值班死亡的主要原因（50 - 60%）。 拟议的物联网系统从可穿戴健康追踪器捕获生理数据，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，用户可以被通知。 此外，所提出的软件应用程序的广泛长期使用还可以提供消防员生理数据的数据库，该数据库然后可以用于进一步改进技术，导致对消防的生理和潜在病理反应的新理解，并激发新的数据-该奖项反映了NSF的法定使命，并被认为是值得通过使用基金会的智力价值和更广泛的评估支持影响审查标准。

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.