RESUMEN
BACKGROUND: In this work we describe a breath emulator system, used to simulate temporal characteristics of exhaled carbon dioxide (CO2) concentration waveform versus time simulating how much CO2 is present at each phase of the human lung respiratory process. The system provides a method for testing capnometers incorporating fast response non-dispersive infrared (NDIR) CO2 gas sensing devices - in a clinical setting, capnography devices assess ventilation which is the CO2 movement in and out of the lungs. A mathematical model describing the waveform of the expired CO2 characteristic and influence of CO2 gas sensor noise factors and speed of response is presented and compared with measured and emulated data. OBJECTIVE: A range of emulated capnogram temporal waveforms indicative of normal and restricted respiratory function demonstrated. The system can provide controlled introduction of water vapour and/ or other gases, simulating the influence of water vapour in exhaled breath and presence of other gases in a clinical setting such as anaesthetic agents (eg N2O). This enables influence of water vapour and/ or other gases to be assessed and modelled in the performance of CO2 gas sensors incorporated into capnography systems. As such the breath emulator provides a means of controlled testing of capnometer CO2 gas sensors in a non-clinical setting, allowing device optimisation before use in a medical environment. METHODS: The breath emulator uses a unique combination of mass flow controllers, needle valves and a fast acting switchable pneumatic solenoid valve (FASV), used to controllably emulate exhaled CO2 temporal waveforms for normal and restricted respiratory function. Output data from the described emulator is compared with a mathematical model using a range of input parameters such as time constants associated with inhalation/ exhalation for different parts of the respiratory cycle and CO2 concentration levels. Sensor noise performance is modelled, taking into account input parameters such as sampling period, sensor temperature, sensing light throughput and pathlength. RESULTS: The system described here produces realistic human capnographic waveforms and has the capability to emulate various waveforms associated with chronic respiratory diseases and early stage detection of exacerbations. The system has the capability of diagnosing medical conditions through analysis of CO2 waveforms. Demonstrated in this work the emulator has been used to test NDIR gas sensor technology deployed in capnometer devices prior to formal clinical trialling.
Asunto(s)
Capnografía , Dióxido de Carbono , Pruebas Respiratorias , Simulación por Computador , Humanos , Pulmón , RespiraciónRESUMEN
Hyperspectral imaging for agricultural applications provides a solution for non-destructive, large-area crop monitoring. However, current products are bulky and expensive due to complicated optics and electronics. A linear variable filter was developed for implementation into a prototype hyperspectral imaging camera that demonstrates good spectral performance between 450 and 900 nm. Equipped with a feature extraction and classification algorithm, the proposed system can be used to determine potato plant health with â¼88% accuracy. This algorithm was also capable of species identification and is demonstrated as being capable of differentiating between rocket, lettuce, and spinach. Results are promising for an entry-level, low-cost hyperspectral imaging solution for agriculture applications.