Measurements Under Biomechanical Stress in Medical Robotics: Diagnosing Pulmonary Impairments by Sensing Breathe Sounds

Abstract

Robotic beds are an advanced version of automatic beds, often used for physical rehabilitation with minimal impact on neurophysiology. These devices play a crucial role in aiding bedridden individuals by helping them regain upright positions, particularly through verticalization, which improves vascularization by increasing oxygen levels in the blood. This enhanced oxygenation is the key to detecting pathologies associated with biomechanical stress. By adjusting the bed to various angular orientations, the sound of breathing can be analyzed to indirectly quantify pulmonary activity. This article presents new findings on feature extraction from breathing sounds by leveraging the verticalization angles of medical robotic beds. We compare traditional methods with artificial intelligence-based techniques, showing that both approaches yield improved results. For clarity, we focus on data collected at a 60° angle, which facilitates accurate diagnosis for individual patients. Notably, robotic beds enable the detection of breathing abnormalities, offering a new avenue for bypassing conventional rehabilitation methods.