Enhanced Respiration Monitoring Device with Improved Accuracy and Real-time Feedback

Publication ID: 24-11857309_0006_PTD
Published: November 07, 2025
Category:Direct Improvements & Enhancements

Legal Citation

pr1or.art Inc., “Enhanced Respiration Monitoring Device with Improved Accuracy and Real-time Feedback,” Published Technical Disclosure No. 24-11857309_0006_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857309_0006_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. 11,857,309.

Summary of the Inventive Concept

The present inventive concept enhances the original respiration monitoring device by introducing a gyroscopic sensor for improved motion detection, machine learning-based acoustic sensor calibration, real-time feedback for irregular breathing patterns, and advanced anomaly detection. These improvements enable more accurate respiration rate calculation and timely interventions.

Background and Problem Solved

The original patent, 'Respiration monitoring device and methods for use,' provided a foundational concept for monitoring and recording health and wellness. However, it had inherent limitations, such as potential inaccuracies in motion detection and noise interference in acoustic sensing. The present inventive concept addresses these limitations by introducing direct improvements and enhancements to the original device.

Detailed Description of the Inventive Concept

The enhanced respiration monitoring device replaces the first accelerometer with a gyroscopic sensor, providing more accurate detection of motion in the x, y, and z-axis. The acoustic sensor is calibrated using a machine learning algorithm to reduce noise interference, ensuring more reliable sound detection related to the patient's breath. A real-time feedback mechanism is integrated to alert the patient of irregular breathing patterns, enabling timely interventions. Furthermore, the device analyzes filtered sound values and motion values to detect anomalies indicative of respiratory distress. The respiration rate calculation is improved by incorporating heart rate variability data from an external device.

Novelty and Inventive Step

The present inventive concept introduces a novel combination of a gyroscopic sensor, machine learning-based acoustic sensor calibration, real-time feedback, and advanced anomaly detection. These enhancements provide a non-obvious improvement over the original patent, enabling more accurate and timely respiration monitoring.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include using different types of sensors, such as optical or electromagnetic sensors, to detect motion and sound. The real-time feedback mechanism could be implemented through various interfaces, such as a mobile application or a wearable device. Additionally, the device could be integrated with other health monitoring systems to provide a more comprehensive picture of the patient's health.

Potential Commercial Applications and Market

The enhanced respiration monitoring device has significant commercial potential in the healthcare industry, particularly in applications such as telemedicine, remote patient monitoring, and respiratory disease diagnosis. The device could be marketed to hospitals, clinics, and healthcare providers, as well as to patients and caregivers seeking to monitor respiratory health at home.

Field of Art

Medical device technology, specifically respiratory monitoring systems, encompassing biomedical engineering, sensor integration, and physiological signal processing

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer or medical device designer with expertise in motion sensing, signal processing, machine learning, and health monitoring technologies, holding at least a master's degree with 3-5 years of experience in wearable medical device development

Obviousness Rationale

A PHOSITA would recognize that the PTD's variations represent predictable improvements to the source patent's respiration monitoring device by leveraging known sensor technologies and machine learning techniques. The proposed enhancements follow standard engineering design approaches for increasing sensor accuracy and adding diagnostic capabilities. The modifications represent incremental technical advances that would be apparent to a skilled practitioner seeking to optimize respiratory monitoring technologies.

Obvious Combinations & Variations

Source Patent Element
First accelerometer detecting motion in x, y, z axes
PTD Variation
Replacing accelerometer with gyroscopic sensor for improved motion detection
Obviousness Reasoning
Substituting sensor types with equivalent motion-sensing capabilities is a known design optimization technique, with predictable results of enhanced motion tracking precision
Source Patent Element
Acoustic sensor for detecting patient breath sounds
PTD Variation
Machine learning-based acoustic sensor calibration to reduce noise interference
Obviousness Reasoning
Applying machine learning techniques to sensor signal processing is a standard approach in medical device engineering for improving signal-to-noise ratio and measurement accuracy
Source Patent Element
Processor calculating respiration rate
PTD Variation
Incorporating heart rate variability data to improve respiration rate calculation
Obviousness Reasoning
Integrating multiple physiological data streams is a common method for enhancing diagnostic accuracy, representing an obvious extension of existing monitoring techniques
Source Patent Element
Basic breath detection and counting mechanism
PTD Variation
Real-time feedback system for alerting patients about irregular breathing patterns
Obviousness Reasoning
Adding user notification features to medical monitoring devices is a predictable design evolution that addresses user safety and engagement needs
Source Patent Element
Motion and sound value filtering
PTD Variation
Advanced anomaly detection algorithm to identify potential respiratory distress
Obviousness Reasoning
Extending signal processing techniques to include diagnostic pattern recognition represents a logical progression in medical monitoring technology design
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857309, a Person Having Ordinary Skill In The Art would find the technical variations disclosed in the Published Technical Disclosure to be obvious modifications that do not represent a non-obvious invention. The proposed enhancements represent predictable technical improvements using known sensor integration, signal processing, and machine learning techniques that would be apparent to a skilled practitioner in medical device engineering.

Original Patent Information

Patent NumberUS 11,857,309
TitleRespiration monitoring device and methods for use