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

• Published in: IEEE transactions on instrumentation and measurement 2020-07, Vol.69 (7), p.4334-4347
• Main Authors: Yuthong, Athtayu, Duangsoithong, Rakkrit, Booranawong, Apidet, Chetpattananondh, Kanadit
• Format: Article
• Language: English
• Subjects: Air monitoring; Algorithms; Breathing; Cameras; circle detection; Electron tubes; Experiments; Image processing; inhalation; Lung; lung therapy; lung volume; Lungs; Maneuvers; Medical treatment; Monitoring; Muscles; object tracking; Personal computers; Physical training; Regeneration; Rehabilitation; Respiration; respiratory; spirometer; Training; Tubes; Video
• ISSN: 0018-9456; 1557-9662
• DOI: 10.1109/TIM.2019.2947931

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.