Hastings Samuel, Mildenhall Jacob, Sinclair Kayla, Guy Ella F S, Clifton Jaimey A, Hill Jordan F, Su Yunpeng, Chase J Geoffrey
Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand.
HardwareX. 2025 Jun 28;23:e00671. doi: 10.1016/j.ohx.2025.e00671. eCollection 2025 Sep.
This article details a pressure and flow sensor system device which enables a framework for the research and development of personalized mechanical ventilator support in a closed-loop or semi-closed-loop control system, where the measurements from this device could be hooked to digital twin models and any ventilator allowing open control. In current practice, patient response to mechanical ventilation is highly variable. Furthermore, current weaning best-practice relies on clinical experience which can lead to variability and inequality in both care and health outcomes. Personalized care can improve these inequalities in care due to patient variability when combined with digital twin models, which simulate physiology based on patient specific data, by improving the level of care possible in the ICU (Intensive Care Unit), regardless of clinician experience and/or patient variability. The device consists of two 3D printed custom Venturis and a Y-piece, with differential pressure sensors measuring gauge, inhalation, and exhalation pressure at the patient. The sensor system has an operating range of ±50.8 cmHO and a mean error in flow data of 3.2%. The system uses BLE (Bluetooth Low Energy) communication between ESP32-S3 development boards to facilitate the closed loop framework. Within this loop, pressure data is sent to a digital beside sheet, which runs digital twin protocols and sends commands to a BLE controlled ventilator. Overall, this device allows the future development and validation of personalized mechanical ventilation treatment through integration with digital twin models.
本文详细介绍了一种压力和流量传感器系统设备，该设备为在闭环或半闭环控制系统中研发个性化机械通气支持提供了一个框架，此设备的测量数据可接入数字孪生模型以及任何支持开放控制的呼吸机。在当前实践中，患者对机械通气的反应差异很大。此外，当前的撤机最佳实践依赖于临床经验，这可能导致护理和健康结果的差异和不平等。个性化护理与数字孪生模型相结合时，可通过提高重症监护病房（ICU）的护理水平来改善因患者个体差异导致的护理不平等，而无需考虑临床医生的经验和/或患者个体差异。该设备由两个3D打印的定制文丘里管和一个Y形管组成，差压传感器测量患者处的表压、吸气压力和呼气压力。该传感器系统的工作范围为±50.8厘米水柱，流量数据的平均误差为3.2%。该系统使用ESP32-S3开发板之间的低功耗蓝牙（BLE）通信来促进闭环框架。在这个环路中，压力数据被发送到一个数字床边表，该表运行数字孪生协议并向BLE控制的呼吸机发送命令。总体而言，该设备通过与数字孪生模型集成，为个性化机械通气治疗的未来发展和验证提供了可能。
