Non-Invasive System for Measuring Intra-Abdominal Pressure

Abstract

Extended Abstract Purpose: Monitoring surgical and intensive care patients is an usual procedure in hospital units Methods: The selection of the features was realized according with the literature review of the parameters that can be influenced by IAP Results The IAP showed average results of 4.05 ± 3.60 mmHg and the parameters with the highest statistical correlation with the IAP were: weight (cc0.48), ACSA (cc0.46), perimeter (cc0.34), diastolic (cc0.25) and mean blood pressure (cc0.17), duration of the QRS (cc0.20) and the amplitude of the R wave (cc0.12). Systems based on the 18 inputs were constructed and a simplified system was created only with the inputs with the highest correlation with the output. The best ANN created was built with 7 inputs, with the activation function Tansig and the training function Bayseian regularization. This network showed results of linear regression coefficient of 0.97. The ANFIS that demonstrated the best results was also constructed with the simplified model, with only 7 entries. The best results were obtained with Sugeno inference system and 20 rules demonstrating an error of 2.10 (training), 1.73 (test) and 3.79 (validation). Conclusion: This type of non-invasive methodology allows the determination of IAP continuously. The ANN and the ANFIS created allowed predicting IAP with low error compared to real values. This type of methodology can be used in human medicine