Design of a Sensor Based on Plastic Optical Fibre (POF) to Measure Fluid Flow and Turbidity

Although many optical fibre applications are based on their capacity to transmit optical signals with low losses, it can also be desirable for the optical fibre to be strongly affected by a certain physical parameter in the environment. In this way, it can be used as a sensor for this parameter. There are many strong arguments for the use of POFs as sensors. In addition to being easy to handle and low cost, they demonstrate advantages common to all multimode optical fibres. These specifically include flexibility, small size, good electromagnetic compatibility behaviour, and in general, the possibility of measuring any phenomenon without physically interacting with it. In this paper, a sensor based on POF is designed and analysed with the aim of measuring the volume and turbidity of a low viscosity fluid, in this case water, as it passes through a pipe. A comparative study with a commercial sensor is provided to validate the proven flow measurement. Likewise, turbidity is measured using different colour dyes. Finally, this paper will present the most significant results and conclusions from all the tests which are carried out.

Aireztapenen maiztasunaren neurketa bihotz biriketako berpiztean kapnografia erabiliz.

[EN]Hyperventilation, which is common both in-hospital and out-of-hospital cardiac arrest, decreases coronary and cerebral perfusion contributing to poorer survival rates in both animals and humans. Current resucitation guidelines recommend continuous monitoring of exhaled carbon dioxide (CO2) during cardiopulmonary resucitation (CPR) and emphasize good quality of CPR, including ventilations at 8-10 min1. Most of commercial monitors/de- brilators incorporate methods to compute the respiratory rate based on capnography since it shows uctuations caused by ventilations. Chest compressions may induce artifacts in this signal making the calculation of the respiratory rate di cult. Nevertheless, the accuracy of these methods during CPR has not been documented yet. The aim of this project is to analyze whether the capnogram is reliable to compute ventilation rate during CPR. A total of 91 episodes, 63 out-of-hospital cardiac arrest episodes ( rst database) and 28 in-hospital cardiac arrest episodes (second database) were used to develop an algorithm to detect ventilations in the capnogram, and the nal aim is to provide an accurate ventilation rate for feedback purposes during CPR. Two graphic user interfaces were developed to make the analysis easier and another two were adapted to carry out this project. The use of this interfaces facilitates the managment of the databases and the calculation of the algorithm accuracy. In the rst database, as gold standard every ventilation was marked by visual inspection of both the impedance, which shows uctuations with every ventilation, and the capnography signal. In the second database, volume of the respiratory ow signal was used as gold standard to mark ventilation instants since it is not a ected by chest compressions. The capnogram was preprocessed to remove high frequency noise, and the rst di erence was computed to de ne the onset of inspiration and expiration. Then, morphological features were extracted and a decission algorithm built based on the extracted features to detect ventilation instants. Finally, ventilation rate was calculated using the detected instants of ventilation. According to the results obtained in this project, the capnogram can be reliably used to give feedback ventilation rate, and therefore, on hyperventilation in a resucitation scenario.