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首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >An Advanced First Aid System Based on an Unmanned Aerial Vehicles and a Wireless Body Area Sensor Network for Elderly Persons in Outdoor Environments
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An Advanced First Aid System Based on an Unmanned Aerial Vehicles and a Wireless Body Area Sensor Network for Elderly Persons in Outdoor Environments

机译：基于无人飞行器和无线人体区域传感器网络的高级急救系统用于室外环境中的老年人

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For elderly persons, a fall can cause serious injuries such as a hip fracture or head injury. Here, an advanced first aid system is proposed for monitoring elderly patients with heart conditions that puts them at risk of falling and for providing first aid supplies using an unmanned aerial vehicle. A hybridized fall detection algorithm (FDB-HRT) is proposed based on a combination of acceleration and a heart rate threshold. Five volunteers were invited to evaluate the performance of the heartbeat sensor relative to a benchmark device, and the extracted data was validated using statistical analysis. In addition, the accuracy of fall detections and the recorded locations of fall incidents were validated. The proposed FDB-HRT algorithm was 99.16% and 99.2% accurate with regard to heart rate measurement and fall detection, respectively. In addition, the geolocation error of patient fall incidents based on a GPS module was evaluated by mean absolute error analysis for 17 different locations in three cities in Iraq. Mean absolute error was 1.08 × 10−5° and 2.01 × 10−5° for latitude and longitude data relative to data from the GPS Benchmark system. In addition, the results revealed that in urban areas, the UAV succeeded in all missions and arrived at the patient’s locations before the ambulance, with an average time savings of 105 s. Moreover, a time saving of 31.81% was achieved when using the UAV to transport a first aid kit to the patient compared to an ambulance. As a result, we can conclude that when compared to delivering first aid via ambulance, our design greatly reduces delivery time. The proposed advanced first aid system outperformed previous systems presented in the literature in terms of accuracy of heart rate measurement, fall detection, and information messages and UAV arrival time.
机译：对于老人来说，跌倒会导致严重的伤害，例如髋部骨折或头部受伤。在这里，提出了一种先进的急救系统，用于监测患有心脏病的老年患者，使他们处于跌倒的危险中，并使用无人飞行器提供急救用品。提出了一种结合加速度和心率阈值的混合跌倒检测算法（FDB-HRT）。邀请五名志愿者评估心跳传感器相对于基准设备的性能，并使用统计分析对提取的数据进行验证。此外，还验证了跌倒检测的准确性以及跌倒事件的记录位置。提出的FDB-HRT算法在心率测量和跌倒检测方面的准确度分别为99.16％和99.2％。此外，通过对伊拉克三个城市中17个不同地点的平均绝对误差分析，评估了基于GPS模块的患者跌倒事件的地理位置误差。相对于GPS Benchmark系统的数据，经纬度数据的平均绝对误差为1.08×10 −5 °和2.01×10 −5 °。此外，结果表明，在市区，无人机成功完成了所有任务，并在救护车之前到达患者的位置，平均节省了105秒的时间。此外，与救护车相比，使用无人机将急救箱运送到患者时，节省了31.81％的时间。结果，我们可以得出结论，与通过救护车运送急救相比，我们的设计大大减少了运送时间。在心率测量，跌倒检测，信息消息和无人机到达时间的准确性方面，所提出的先进的急救系统优于文献中介绍的先前系统。

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