Enhanced System for Respiratory Monitoring of a Subject

The present inventive concept relates to an improved system and method for respiratory monitoring of a subject, enhancing the accuracy and efficiency of respiratory effort and airflow estimation through the integration of machine learning algorithms, signal processing techniques, and pattern recognition.

The original patent, 'System and method for respiratory monitoring of a subject', has limitations in accurately estimating respiratory effort and airflow. The new inventive concept addresses these limitations by introducing advanced algorithms and techniques to improve the estimation process.

The enhanced system comprises a bioimpedance measurement sensor and a processing unit. The bioimpedance measurement sensor acquires a bioimpedance signal, which is then processed by the processing unit using a machine learning algorithm to determine an estimation of the effort signal component. Alternatively, the processing unit can use a signal processing technique to determine an estimation of the flow signal component. Additionally, a neural network can be employed to estimate the respiratory effort of the subject. The system can also utilize a filter to remove noise from the measured bioimpedance signal, enabling a more accurate estimation of the respiratory airflow. Furthermore, a pattern recognition algorithm can be used to determine the respiratory rate of the subject.

The new claims introduce novel machine learning algorithms, signal processing techniques, and pattern recognition methods that significantly improve the accuracy and efficiency of respiratory effort and airflow estimation, distinguishing the inventive concept from the original patent.

Alternative embodiments of the inventive concept could include the use of different machine learning algorithms, signal processing techniques, or pattern recognition methods. Additionally, the system could be integrated with other sensors or devices to provide a more comprehensive respiratory monitoring system.

The enhanced system and method for respiratory monitoring have significant commercial potential in the healthcare industry, particularly in applications such as remote patient monitoring, critical care, and respiratory therapy.