Portable oxygen breathing apparatus integrated with biosensors: Enabling intelligent monitoring and optimal oxygen provision for biomechanical homeostasis

A lightweight, compact, inconspicuous gadget that provides extra oxygen when traveling is called a portable oxygen breathing apparatus. Cells rely on oxygen to drive the oxidative phosphorylation process within mitochondria, where adenosine triphosphate (ATP) is synthesized. Adequate ATP is essential for maintaining the muscle contraction and cell motility. With these portable devices, patients can maintain their oxygen therapy while going about their daily lives, enhancing their quality of life (QoL) and encouraging more mobility. An incorrect assessment could result in a low oxygen supply during exercise. Hypoxia-induced changes can also trigger intracellular signaling pathways that may lead to cell damage and, in the long term, contribute to the progression of various pathologies. Promising resolution to the difficulties can be discovered by incorporating machine learning (ML) algorithms and sophisticated monitoring systems into portable oxygen delivery devices. In this study, we propose a novel intelligent portable oxygen breathing apparatus integrated with biosensors (IPOBAB) that has revolutionized the treatment of long-term respiratory disorders, particularly severe hypoxemia and chronic obstructive pulmonary disease (COPD). IPOBAB system deployed with the Dynamic Gradient Boosting Machine (DGBM) classifier to classify the physical activities into low, moderate, and high exertion levels to ensure oxygen delivery is repeatedly adjusted based on the patient’s current requirements. Inertial Measurement Unit (IMU) sensor data, blood oxygen saturation (SpO2), and cardiovascular rate are just a few of the vital physiological features that biological sensors continuously monitor. This data lets doctors perform real-time assessments of a patient’s health status. To eliminate noise, the information was processed using a median filter. The Fast Fourier Transform (FFT), which displays dominating frequency components, divides the electrical signal into individual frequencies to extract features. The results demonstrated that the IPOBAB model exhibits a high weighted accuracy of 98.4% in mechanically adjusting oxygen flow according to medical criteria compared to existing algorithms. This indicates that the system is effective in optimizing oxygen delivery, which is essential for maintaining the proper cell and molecular biomechanical functions in patients with long-term respiratory disorders. In conclusion, the IPOBAB represents a significant advancement in portable oxygen therapy as it combines adaptive oxygen delivery and comprehensive monitoring, thereby optimizing the care for patients with long-term respiratory conditions and safeguarding the integrity and functionality of cells and tissues at the molecular level.