Philip Asare1, Adit Acharya1, Yuxuan Huang1, Dikendra Karki1, Win Kyaw1, Caitlin Mahoney1, S. Mark Poler2, Jean R. Lavalley2, Rick Tevis2
Research Abstracts (Poster)
08:30 - 19:30 | Wed 26 Oct | Auditorium Foyer | WePOS
11:45 - 12:15 | Thu 27 Oct | Main Auditorium | IS-2
BACKGROUND Automation of pump control by closed-loop systems has long-recognized advantages. The attention of the clinician may be directed to other matters, while desired conditions are automatically maintained. Such systems been explored for over 20 years [1, 2]. In some cases they have demonstrated performance superior to expert clinicians . Potential hazards are also recognized and must be addressed in model systems. A critical enabling technology for such closed-loop systems is open nonproprietary standard interfaces for acquisition and transmission of data in a device network facilitating monitoring and control, allowing monitors, sensors, pumps, and controllers to be integrated. Efforts at standard device interfaces over the past 30 years [4, 5], have, however, borne little fruit. Only a few proprietary or customized systems have been developed. Enabling nonproprietary device interactions has been a pipedream. Yet, this is essential to enable research, development, and adoption of systems of interconnected devices. PURPOSE The main goal of this work is to develop minimalist open standard interfaces to facilitate research and development. Clinically-appropriate standardization would require much more sophistication. Standardization enables interaction of components with otherwise incompatible proprietary communications. Open software in the device interfaces and protocols permits logging of communication at every interface level to fully understand all interactions of closed-loop systems. Applications include capture of clinical events and interventions, and implementation of clinical controller systems. Work in progress includes development of closed-loop physiological animal testing and computer-in-the-middle model systems. METHODS We have adopted hardware and an architecture similar to the integrated clinical environment work by MDPnP . Each medical device is connected to a dongle that translates the specific proprietary device protocol into a standardized one. The dongles then connect to a local network allowing them to interact with applications on a computer that handle device and data management and processing algorithms. Unlike the MDPnP work, Python is used for software development to allow rapid-prototyping and ease of adoption and modification. In addition, the Robot Operating System (ROS)  is our middleware because of its proven effectiveness for developing production-grade distributed systems and Python integration. IV. RESULTS We will demonstrate a system that: (a) interacts with a patient monitor (Philips IntelliVue MP50) and sends commands to an unmodified commercial pump (CME America BodyGuard 121 Dual-Channel Infusion Pump); (b) detects whether a device is connected to the system; (c) logs system performance, device data, and monitored data (simulated patient data and infusion actions); (d) configures and controls the system through a graphical user interface; (e) runs a simple illustrative closed-loop control scenario. CONCLUSION Our progress suggests that an easier-to-use experimentation platform for closed-loop control is feasible.
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