Collaborative use of RGB and thermal imaging for remote breathing rate measurement under realistic conditions

Las enfermedades cronicas obstructivas son parte de los adolecimientos mas comunes en la poblacion humana, en la actualidad, existen equipos que permiten diagnosticar y llevar un tratamiento a este tipo de enfermedades, a pesar de ello, no existen equipos que permitan llevar un tratamiento preventivo sin necesidad de un medico especialista. Este trabajo de grado muestra una alternativa para la medicion de la capacidad pulmonar que permita ser replicado con facilidad, para garantizar su precision, se hizo uso de la norma ISO 5167, asimismo, se utilizo un sensor de presion diferencial realizando un filtrado digital que fue disenado con base en una caracterizacion de la senal a estudiar, proponiendo un algoritmo para calibrar el sensor presion, y los datos son visualizados en un aplicativo de android, se realizaron 10 pruebas a pacientes sanos para mostrar el funcionamiento del espirometro.

Medidor inalámbrico de capacidad pulmonar a partir del aire espirado para alarma temprana en pacientes cronico-respiratorios

Breathing exercise training with a flow-oriented incentive spirometer (or Triflo) is important in lung expansion rehabilitation for patients with lung surgery or pulmonary injury. In this article, we propose a novel technique to estimate the volume of air inhaled and the sustained inhalation time based on video processing. The proposed technique combines a randomized circle detection algorithm to detect the three balls in Triflo tubes and a normalized cross-correlation algorithm to track these three balls that rise due to inhalation. The values of inhalation and the sustained inhalation time intervals are automatically recorded as screenshots on a personal computer for later analysis by a doctor. Three major experiments were conducted to verify the advantages of this proposed system. The first experiment evaluated the performances of both the ball detection and the tracking algorithms showing 3.68% error. The second experiment applied the proposed method implemented, so that it displays in plots the changes in the inhalation rate, as the training of a postoperative volunteer progressed. In the last experiment, a healthy subject employs Triflo to test the inhalation training format for lung volume regeneration with three levels of difficulty, to record the number of successful breathing maneuvers. When the data are displayed in rate versus time plots, a graph can help a doctor to appropriately plan the training program for the benefit of patients, because a more adaptable therapy can be realized and varying degrees of difficulty can be implemented. In addition, the patients can comfortably practice in home-based rehabilitation, seeing the improvements in the inspiratory muscle performance in computer screenshots.

Monitoring of Volume of Air in Inhalation From Triflo Using Video Processing

Lung function parameters are important reference for evaluating lung health. Compared with the flow vital capacity measurement method, the bioimpedance method has been widely concerned as a detection method with non-respiratory contact, strong comfort, and continuous monitoring. However, the current bioimpedance method still has the problems of large measurement error. To achieve accurate calculation of lung function parameters, this article first established a six-port circuit network model of the thoracic cross-section with the four-electrode fitting position as the node, calculated the transfer impedances in different measurement modes, and the mutual correction mathematical relationship of them is deduced. Furthermore, the calculated expression for the integrated transfer impedance is obtained. Second, the refined simulation model of the thoracic cross-section is constructed. The simulation results prove that the conclusions of the theoretical analysis are applicable for any respiratory moment. Then, 300 samples were measured, the experimental data were analyzed, and the parameters that correlate most strongly with lung function parameters were selected as independent variables for the binary functions used to calculate forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1). The coefficients of the function analytic formula are corrected by means of a higher-order parameter matrix, the elements of which are fitted from the experimental data. Finally, 20 samples were measured, and the calculated lung function parameters were compared with the standard values. The results showed that the difference between the two data was within the confidence range of 95%, and the maximum relative errors of FVC and FEV1 were 1.44% and 1.97%, respectively.

Method of Calculating FVC and FEV1 Based on Integrated Transfer Impedance With Higher-Order Modified Parameter Matrix

Lung rehabilitation can be done by using different measuring and monitoring tools to recover patient from lung collapse. However, the patients can feel uncomfortable or get infected from using these tools. This paper present lung volume monitoring using flow-oriented incentive spirometer with video processing. According to the result, the proposed method can be used for lung rehabilitation monitoring and measuring with more comfortable, low cost and easy to use.

Athtayu Yuthong

Papers

Monitoring of Volume of Air in Inhalation From Triflo Using Video Processing

Lung volume monitoring using flow-oriented incentive spirometer with video processing