Simulation and Feasibility Study of Drone-Delivered AED for Out-of-Hospital Cardiac Arrest

Condition(s) studied

Investigational drug(s) / intervention(s)

Drone-Based AED Delivery System: The drone platform is a DJI M400 operating along pre-specified flight routes and carrying a lightweight AED training device. The AED device used in this study is a Mindray BeneHeart series AED trainer, which is a simulation device rather than a live AED. Depending on the sub-study, one of three delivery modes will be used: winch lowering, low-altitude compartment retrieval, or direct landing. The mission will primarily be executed automatically based on preset flight routes, while the drone operator will monitor the mission and take over when necessary for safety or contingency management.

Standard Ground Ambulance Response Pathway Simulation: The control pathway will be simulated using a standard ambulance, a fixed ambulance crew, and a predefined operational workflow modeled on the local standard prehospital emergency response process.

Study summary

Background: Survival after out-of-hospital cardiac arrest (OHCA) depends heavily on early defibrillation. Reducing the time from cardiac arrest to defibrillation is a key factor in improving survival. In recent years, many countries have promoted early defibrillation through public automated external defibrillator (AED) networks. However, in practice, public access to and use of AEDs remain limited because of insufficient accessibility, uneven distribution, difficulties in locating devices, and delays in retrieval. With the development of drone technology, rapid drone-based AED delivery has been considered a potentially promising solution. Drones may bypass ground traffic congestion and reach the scene more quickly via aerial routes, allowing bystanders to use an AED under remote guidance. Although simulation studies, system optimization studies, and preliminary real-world applications of drone-delivered AEDs have been reported in other countries, this field remains exploratory in China. At present, most Chinese cities still rely mainly on conventional ambulance dispatch systems and fixed AED networks, both of which may be limited by urban traffic congestion, high population density, and uneven spatial distribution of AEDs.

Objective: This prospective quasi-real-world simulation study in Wuhu, Anhui Province, China, aims to compare the time efficiency of a drone-based AED delivery pathway with that of a standard ground ambulance response pathway in simulated OHCA scenarios. The study will also evaluate the effects of geographic setting, traffic period, and different aerial delivery modes on delivery performance, in order to provide preliminary evidence for the deployment of drone-assisted emergency response networks in Chinese cities.

Methods: This is an open-label, non-randomized, exploratory pilot feasibility study. The drone launch site will be located at a designated takeoff and landing area near the Emergency Department building of the Second Affiliated Hospital of Wannan Medical College. Simulated task endpoints will be selected within a 30-km one-way mission radius from the launch site. The study includes three sub-studies: (1) comparison of response efficiency between the drone pathway and the ground ambulance pathway in urban versus suburban locations; (2) comparison of response efficiency between the drone pathway and the ground ambulance pathway during peak versus off-peak traffic periods; and (3) comparison of operational time and success rate among three drone AED delivery modes, including winch lowering, low-altitude compartment retrieval, and direct landing. A total of 24 healthy volunteers will participate in the simulation tasks, and 1 to 3 professional drone operators will conduct flight operations. For each simulated task, a unified start command will be issued by the study coordinator, and the volunteer will receive the AED and complete electrode pad placement on the manikin.

Primary Outcome: The primary outcome is the time from the unified simulated task start to completion of AED pad placement on the manikin chest.

Eligibility

Primary outcome measure(s)

• Time From Unified Simulated Task Start to AED Pad Placement on the Manikin Chest — Up to 30 minutes
  Defined as the elapsed time from issuance of the unified simulated task start command by the study coordinator to completion of standard placement of both AED pads on the manikin chest. Time points will be recorded by the lead timekeeper using a standardized timing tool.

Trial sites (1)