Respiratory pressure and split flow data collection device with rapid expiratory shuttering
The venturi-based flow meter utilises split inspiratory and expiratory flow pathways, for greater configurability with additional respiratory monitoring or simulation devices, as well for ease of data processing. The venturi is designed to be integrated in series with respiratory circuitry, using standard 22mm male and female connections. In its current application the inspiratory input port (22mm male connection) is connected to a CPAP device using its accompanying circuitry (or is unconnected when CPAP is not required), the expiratory output port vents to atmosphere (22mm female connection), and the subject port (22mm male connection) is connected to a mouthpiece, filter, or mask. Differential Pressure Sensors were also upgraded (SSCDRRN001PD2A5) to capture larger flow ranges (seen in maximal breaths and panting). Additionally, a modular expiratory shutter attachment is outlined for identification of passive respiratory mechanics. Specifically, the rapid expiratory shuttering allows for breath-wise identification of elastance and resistance during shutter instances. Thus, eliminating the issue of trade-off associated with the simultaneous fitting of elastance and resistance to expiratory profiles. Ultimately, the device provides researchers with: - Rapid expiratory occlusion for identification of passive lung mechanics - A low-cost alternative to commercial sensor systems - Individual inspiratory and expiratory flow pathways - Non-invasive data collection - A modular design with high customisability
Steps to reproduce
- The Venturi tubes, PCB bracket, and expiratory shutter housing components were 3D printed using a Prusa Mini. Supporting Material was removed and stringing on the interior of the venturi tubes were removed using a pipe cleaner. - The pressure sensor port guide holes were drilled out using a 1.6mm drill bit. The Pressure sensor port tube was cut into 8mm lengths using a Stanley knife. These were inserted into the venturi port holes and glued in place. It was ensured that the tubes terminated flush with the interior surface of the venturi tubes. - The venturi components were then connected using one-way valves to construct a y-split tube device with an inhalation, exhalation, and patient interface pathways. - The control and pressure sensor breakout PCBs were ordered from JLCPCB. These were populated, with resistors, capacitors, bus splitter, and connector headers, in the SMT Laboratory at the University of Canterbury using a pick and place machine and reflow soldered in a reflow oven. Pressure sensors and pin headers were then hand-soldered on. - The microcontroller was then connected, and the microcontroller sampling and shuttering control code was written and uploaded using Arduino IDE. - Next, the control and pressure sensor PCBs were attached to pressure sensor bracket using M2 x 12mm Cap Screws and M2 Nylon Nuts. The pressure sensor bracket can be zip tied, or otherwise attached to the venturi device for testing. Flexible silicone tubing was then used to connect the pressure sensor ports to the port tubes. - A camera shutter was dismantled, and the IR filter was removed. Leads were subsequently soldered onto the shutter solenoid. - An O-Ring was inserted into the groove on the shutter housing and the camera shutter was secured in the housing using M2 x 8mm Cap Screws and M2 Nyloc Nuts. - A connector was then cut in half and used in combination with jumper cables to construct and adapter from the control board to the driver board. - The shutter attachment was connected to expiratory pathway and the driver board secured to the venturi tube for testing. The board was then connected to the shutter leads. Connections from the control board to pressure sensor breakout boards were make using connector cables, and to the shutter driver board using the adapted driver board connector. - The data collection code, and processing code was written in MATLAB. The included code samples gauge pressure, inspiratory and expiratory different pressures (to calculate flow and volume), and dynamic circumference values (https://doi.org/10.17632/wfw7nyctcy.2). The code can be easily adapted to exclude dynamic circumference measures or include additional sensor data.
University of Canterbury
Horizon 2020 Framework Programme
MSCA-RISE-2019 #872488 — DCPM