Synergistic Respiratory Monitoring System

Publication ID: 24-11857308_0008_PTD
Published: November 07, 2025
Category:Synergistic Combinations

Legal Citation

pr1or.art Inc., “Synergistic Respiratory Monitoring System,” Published Technical Disclosure No. 24-11857308_0008_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857308_0008_PTD
This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,857,308.

Summary of the Inventive Concept

A novel system integrating bioimpedance measurement with AI, IoT, blockchain, and natural language processing for enhanced respiratory monitoring and personalized health reports.

Background and Problem Solved

The original patent for respiratory monitoring using bioimpedance signals has limitations in terms of data analysis and integration with other technologies. The new inventive concept addresses these limitations by combining bioimpedance measurement with machine learning, blockchain, IoT, and natural language processing to provide a more comprehensive and accurate picture of a subject's respiratory health.

Detailed Description of the Inventive Concept

The Synergistic Respiratory Monitoring System comprises a bioimpedance measurement sensor, a processing unit, and various modules for integrating and analyzing the acquired bioimpedance signal. The system applies machine learning algorithms to identify patterns indicative of respiratory distress, uses blockchain-based encryption to ensure data integrity, and integrates with IoT-based environmental sensors to provide a comprehensive picture of the subject's respiratory health. The system also features a user interface to display alerts and recommendations to the subject and can generate personalized respiratory health reports using natural language processing.

Novelty and Inventive Step

The new inventive concept's integration of bioimpedance measurement with AI, IoT, blockchain, and natural language processing provides a novel and non-obvious solution for respiratory monitoring. The use of machine learning algorithms to identify patterns indicative of respiratory distress, blockchain-based encryption for data integrity, and IoT-based environmental sensors for comprehensive data analysis are all new and inventive aspects of the system.

Alternative Embodiments and Variations

Alternative embodiments of the Synergistic Respiratory Monitoring System could include the use of different types of sensors, such as ECG or accelerometer sensors, or the integration of additional technologies, such as computer vision or robotics. Variations of the system could also be designed for specific applications, such as monitoring respiratory health in athletes or individuals with chronic respiratory conditions.

Potential Commercial Applications and Market

The Synergistic Respiratory Monitoring System has significant commercial potential in the healthcare industry, particularly in the fields of respiratory medicine, critical care, and telemedicine. The system's ability to provide accurate and personalized respiratory health reports makes it an attractive solution for healthcare providers, insurance companies, and patients seeking proactive respiratory care.

Field of Art

Biomedical signal processing and respiratory monitoring technologies, with expertise in bioimpedance measurement, signal analysis, and medical sensor systems

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer or medical device specialist with advanced knowledge of signal processing, machine learning, sensor integration, and healthcare monitoring technologies, typically holding a Master's or PhD in biomedical engineering or related field

Obviousness Rationale

A person of ordinary skill would recognize that the source patent's fundamental bioimpedance respiratory monitoring system provides a clear technical foundation for integrating advanced computational and communication technologies. The PTD's variations represent predictable extensions of the core respiratory monitoring concept using well-established techniques in machine learning, blockchain, and IoT. These technological integrations would be considered straightforward improvements by a skilled practitioner seeking to enhance the functionality and utility of the original respiratory monitoring system.

Obvious Combinations & Variations

Source Patent Element
Bioimpedance measurement sensor for acquiring respiratory signals
PTD Variation
Adding machine learning algorithms to identify respiratory distress patterns
Obviousness Reasoning
Applying machine learning to medical signal processing is a known technique for extracting advanced diagnostic insights, representing a predictable application of computational methods to existing sensor technologies
Source Patent Element
Processing unit for receiving and analyzing bioimpedance signals
PTD Variation
Integrating blockchain encryption for data integrity and IoT environmental sensors
Obviousness Reasoning
Enhancing data security and contextual analysis through blockchain and IoT represents a standard approach to improving medical monitoring systems, utilizing well-established technological integration strategies
Source Patent Element
Reference measurement sensor for respiratory effort tracking
PTD Variation
Implementing natural language processing for generating personalized health reports
Obviousness Reasoning
Converting complex medical data into user-friendly reports is a predictable evolution in medical technology, leveraging standard natural language processing techniques to improve patient communication
Source Patent Element
System for acquiring and processing respiratory signals
PTD Variation
Adding remote monitoring capabilities with alert transmission
Obviousness Reasoning
Creating remote monitoring and alert systems is a standard approach in medical device development, representing an obvious enhancement to existing respiratory monitoring technologies
Source Patent Element
Bioimpedance signal acquisition method
PTD Variation
Predicting respiratory failure using artificial intelligence techniques
Obviousness Reasoning
Applying predictive AI to medical signal analysis is a known and expected approach for extracting advanced diagnostic insights from sensor data
35 U.S.C. § 103 Summary: Pursuant to 35 U.S.C. ยง 103, the variations disclosed in the published technical disclosure would have been obvious to a person having ordinary skill in the art at the time of invention, as they represent predictable technological extensions of the respiratory monitoring system disclosed in US Patent 11857308, combining known techniques in machine learning, blockchain, and IoT with established bioimpedance monitoring methodologies to achieve foreseeable improvements in medical signal processing and patient monitoring technologies.

Original Patent Information

Patent NumberUS 11,857,308
TitleSystem and method for respiratory monitoring of a subject
Assignee(s)Stichting IMEC Nederland