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Introduction: The need for remote ventilator control has been highlighted by the COVID-19 Public Health Emergency. Remote ventilator control from outside a patient's room can improve response time to patient needs, protect health care workers, and reduce personal protective equipment (PPE) consumption. Extending remote control to distant locations can expand the capabilities of frontline health care workers by delivering specialized clinical expertise to the point of care, which is much needed in diverse health care settings, such as tele-critical care and military medicine. However, the safety and effectiveness of remote ventilator control can be affected by many risk factors, including communication failures and network disruptions. Consensus safety requirements and test methods are needed to assess the resilience and safety of remote ventilator control under communication failures and network disruptions.
Materials And Methods: We designed two test methods to assess the robustness, usability, and safety of a remote ventilator control prototype system jointly developed by Nihon Kohden OrangeMed, Inc. and DocBox, Inc. ("the NK-DocBox system") to control the operation of an NKV-550 critical care ventilator under communication failures and network disruptions. First, the robustness of the NKV-550 ventilator was tested using a remote-control application developed on OpenICE - an open-source medical device interoperability platform - to transmit customized high-frequency and erroneous remote-control commands that could be caused by communication failures in a real-world environment. The second method utilized a network emulator to create different types and severity of network quality of service (QoS) degradation, including bandwidth throttling, network delay and jitter, packet drop and reordering, and bit errors, in the NKV-DocBox system to quantitatively assess the impact on system usability and safety.
Results: The NKV-550 ventilator operated as expected when remote-control commands arrived as fast as once per second. It ignored erroneous commands attempting to adjust invalid ventilation parameters. When facing commands that set the ventilation mode and parameters to invalid values, it reset the ventilation mode or parameters to default values, the safety implication of which may merit further evaluation. When any network QoS attribute (except for packet reordering) started to degrade, the NK-DocBox System experienced interference to its remote-control function, such as delays in the transmission of ventilator data and remote-control commands within the system. When the network QoS was worse than 500 ms network delay, 100 ms network jitter, 1% data drop rate, 12 Mbps minimal bandwidth, or 1e-6 bit error rate, the system became unsafe to use. For example, ventilator waveforms visualized on the remote-control application demonstrated freezes, out-of-synchronization, and moving backwards; and the connection between the ventilator and the remote-control application became unstable.
Conclusion: The presented test methods confirmed the robustness of the NKV-550 ventilator against high-frequency and erroneous remote control, quantified the impact of network disruptions on the usability, reliability, and safety of the NK-DocBox system and identified the minimum network QoS requirements for it to function safely. These generalizable test methods can be customized to evaluate other remote ventilator control technologies and remote control of other types of medical devices against communication failures and network disruptions.
