Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu City 30010, Taiwan.
College of Artificial Intelligence, National Yang Ming Chiao Tung University, Hsinchu City 30010, Taiwan.
Sensors (Basel). 2021 Apr 15;21(8):2781. doi: 10.3390/s21082781.
Acute Coronary Syndrome (ACS) and other heart emergency events require immediate chest pain identification in the ambulance. Specifically, early identification and triage is required so that patients with chest pain can be quickly sent to a hospital with appropriate care facilities for treatment. In the traditional approach, ambulance personnel often use symptom checklists to examine the patient and make a quick decision for the target hospital. However, not every hospital has specialist facilities to handle such emergency cases. If the result of the subsequent cardiac enzyme test performed at the target hospital strongly suggests the occurrence of myocardial infarction, the patient may need to be sent to another hospital with specialist facilities, such as Percutaneous Coronary Intervention. The standard procedure is time consuming, which may result in delayed treatment and reduce patent survival rate. To resolve this issue, we propose AMBtalk (Ambulance Talk) for accurate, early ACS identification in an ambulance. AMBtalk provides real-time connection to hospital resources, which reduces the elapsed time for treatment, and therefore, improves the patient survival rate. The key to success for AMBtalk is the development of the AllCheck Internet of Things (IoT) device, which can accurately and quickly provide cardiovascular parameter values for early ACS identification. The interactions between the AllCheck IoT device, the emergency medical service center, the ambulance personnel and the hospital are achieved through the AMBtalk IoT server in the cloud network. AllCheck outperforms the existing cardiovascular IoT device solutions for ambulance applications. The testing results of the AllCheck device show 99% correlation with the results of the hospital reports. Due to its excellent performance in quick ACS identification, the AllCheck device was awarded the 17th Taiwan Innovators Award in 2020.
急性冠状动脉综合征 (ACS) 和其他心脏急症需要在救护车上立即识别胸痛。具体来说，需要进行早期识别和分诊，以便将胸痛患者迅速送往具有适当治疗设施的医院。在传统方法中，救护人员通常使用症状清单检查患者，并快速决定目标医院。然而，并非每家医院都有处理此类紧急情况的专科设施。如果在目标医院进行的后续心肌酶检测结果强烈提示心肌梗死的发生，患者可能需要被送往另一家具有专科设施的医院，例如经皮冠状动脉介入治疗。标准程序耗时较长，可能导致治疗延误和降低患者生存率。为了解决这个问题，我们提出了 AMBtalk（救护车谈话），用于在救护车上进行准确、早期的 ACS 识别。AMBtalk 提供与医院资源的实时连接，减少了治疗的时间，从而提高了患者的生存率。AMBtalk 成功的关键是开发了 AllCheck 物联网 (IoT) 设备，该设备可以准确、快速地提供心血管参数值，用于早期 ACS 识别。AllCheck IoT 设备、紧急医疗服务中心、救护车人员和医院之间的互动是通过云网络中的 AMBtalk IoT 服务器实现的。AllCheck 在救护车应用中的心血管 IoT 设备解决方案中表现出色。AllCheck 设备的测试结果与医院报告的结果有 99%的相关性。由于其在快速 ACS 识别方面的出色性能，AllCheck 设备在 2020 年获得了第 17 届台湾创新奖。
