McGill University, Faculty of Medicine and Health Sciences, Montreal, Canada.
Côte Saint-Luc EMS, Montreal, Canada.
Prehosp Disaster Med. 2023 Oct;38(5):617-621. doi: 10.1017/S1049023X23006362. Epub 2023 Oct 3.
In recent years, unmanned aerial vehicles (UAVs) have been increasingly used for medical surveillance purposes in mass-gathering events. No studies have investigated the reliability of live video transmission from UAVs for accurate identification of distressed race participants in need of medical attention. The aim of this study was to determine the proportion of time during which live medical surveillance UAV video feed was successfully transmitted and considered of sufficient quality to identify acute illness in runners participating in the 2022 Montreal Marathon (Canada).
Four UAVs equipped with high-resolution cameras were deployed at two pre-defined high-risk areas for medical incidents located within the last 500 meters of the race. The video footage was transmitted in real-time during four consecutive hours to a remote viewing station where four research assistants monitored it on large screens. Interruptions in live feed transmission and moments with inadequate field of view (FOV) on runners were documented.
On September 25, 2022, a total of 6,916 athletes ran during the Montreal Marathon and Half Marathon. Out of the eight hours of video footage analyzed (four hours per high-risk area), 91.7% represented uninterrupted live video feed with an adequate view of the runners passing through the high-risk areas. There was a total of 18 live feed interruptions leading to a total interruption time of 22 minutes and 19 seconds (median interruption time of 32 seconds) and eight distinct moments with inadequate FOV on runners which accounted for 17 minutes and 33 seconds (median of 1 minute 47 seconds per moments with inadequate FOV). Active surveillance of drone-captured footage allowed early identification of two race participants in need of medical attention. Appropriate resources were dispatched, and UAV repositioning allowed for real-time viewing of the medical response.
Live video transmission from UAVs for medical surveillance of runners passing through higher risk segments of a marathon for four consecutive hours is feasible. Live feed interruptions and moments with inadequate FOV could be minimized through practice and additional equipment redundancy.
近年来，无人机（UAV）越来越多地用于群体活动的医疗监测。目前尚无研究调查无人机实时视频传输用于准确识别需要医疗关注的有困难的参赛选手的可靠性。本研究的目的是确定在 2022 年蒙特利尔马拉松（加拿大）期间，用于监测通过高风险赛段的跑步者的医疗监测用无人机实时视频传输成功且质量足够高以识别急性疾病的时间比例。
四架配备高分辨率摄像机的无人机部署在比赛最后 500 米内两个预先确定的医疗事件高风险区域。视频实时传输四小时，传至远程观察站，四名研究助理在大屏幕上对其进行监控。记录实时视频传输中断和跑步者视场（FOV）不足的时刻。
2022 年 9 月 25 日，共有 6916 名运动员参加了蒙特利尔马拉松和半程马拉松比赛。在所分析的八小时视频片段（每个高风险区域两小时）中，91.7%为不间断的实时视频，可清晰看到跑步者通过高风险区域。共有 18 次实时视频中断，总中断时间为 22 分 19 秒（中位数中断时间为 32 秒），有 8 个跑步者 FOV 不足的不同时刻，共计 17 分 33 秒（每个 FOV 不足时刻的中位数为 1 分 47 秒）。对无人机拍摄的视频进行主动监测可及早识别需要医疗关注的两名参赛选手。及时派遣了适当的资源，并且通过重新定位无人机实现了对医疗响应的实时观察。
对通过马拉松高风险赛段的跑步者进行四小时连续医疗监测的无人机实时视频传输是可行的。通过实践和增加设备冗余，可以将实时视频中断和 FOV 不足的时刻最小化。
