Advanced Hemodynamic Parameter Monitoring System

Publication ID: 24-11857295_0001_PTD
Published: November 07, 2025
Category:Direct Improvements & Enhancements

Legal Citation

pr1or.art Inc., “Advanced Hemodynamic Parameter Monitoring System,” Published Technical Disclosure No. 24-11857295_0001_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857295_0001_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. 11,857,295.

Summary of the Inventive Concept

An innovative system for monitoring hemodynamic parameters, enhancing accuracy and efficiency through machine learning algorithms, neural networks, and advanced sensor integration.

Background and Problem Solved

The original patent, 'Connectors for medical equipment,' has limitations in terms of accuracy and efficiency in determining hemodynamic parameters. The new inventive concept addresses these limitations by incorporating advanced technologies to improve the measurement and analysis of hemodynamic parameters.

Detailed Description of the Inventive Concept

The advanced hemodynamic parameter monitoring system comprises a cuff adapted to at least partially occlude a blood vessel, a pressure sensor configured to measure pressure within the cuff, and a processing unit that determines a hemodynamic parameter based on the measured pressure. The system incorporates a machine learning algorithm to improve the accuracy of the determined hemodynamic parameter. Additionally, the system may include a neural network to filter out noise in the pressure waveform during deflation. The system can also include a medical equipment connector with an integrated sensor to detect the connection status of the connector and transmit a signal to the patient monitoring system. Furthermore, the system may comprise a warning module that alerts a user if the cuff is not properly connected to the patient. The system can also be calibrated using a statistical model to compensate for variations in the cuff's pressure measurement over time.

Novelty and Inventive Step

The new inventive concept introduces the use of machine learning algorithms, neural networks, and advanced sensor integration, which are not present in the original patent. These advancements provide a significant improvement in accuracy and efficiency, making the new inventive concept novel and non-obvious compared to the original patent.

Alternative Embodiments and Variations

Alternative embodiments of the advanced hemodynamic parameter monitoring system may include variations in the type of machine learning algorithm used, the integration of additional sensors, or the use of different materials for the cuff and connector. Other variations may include the development of a portable or wearable version of the system, or the integration of the system with other medical devices.

Potential Commercial Applications and Market

The advanced hemodynamic parameter monitoring system has significant commercial potential in the medical device industry, particularly in the areas of patient monitoring and cardiovascular health. The system's ability to provide accurate and efficient hemodynamic parameter measurements makes it an attractive solution for hospitals, clinics, and healthcare providers.

Field of Art

Medical device engineering, specifically non-invasive hemodynamic monitoring systems, with expertise in blood pressure measurement technologies, sensor integration, and medical equipment connectors

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer with advanced degree, 3-5 years experience in medical device design, familiar with blood pressure monitoring technologies, sensor systems, signal processing, and machine learning applications in medical diagnostics

Obviousness Rationale

A PHOSITA would recognize that the advanced hemodynamic monitoring system represents predictable variations and incremental improvements to existing blood pressure measurement technologies. The integration of machine learning and neural network techniques for signal processing and noise reduction are well-established approaches in medical sensor systems. The proposed modifications represent standard engineering design choices that would be obvious to a skilled practitioner seeking to enhance measurement accuracy and diagnostic capabilities.

Obvious Combinations & Variations

Source Patent Element
Blood pressure cuff adapter with specific connector geometry
PTD Variation
Adding integrated sensor to detect connection status and transmit connection signals
Obviousness Reasoning
Adding status detection sensors to medical connectors is a known technique for improving device reliability and patient safety, representing a predictable design enhancement
Source Patent Element
Pressure measurement system for hemodynamic parameters
PTD Variation
Incorporating machine learning algorithms to improve parameter determination accuracy
Obviousness Reasoning
Application of machine learning to sensor data processing is a standard engineering approach for improving measurement precision, representing an obvious optimization technique
Source Patent Element
Blood pressure measurement method using cuff inflation and deflation
PTD Variation
Using neural network to filter pressure waveform noise during deflation
Obviousness Reasoning
Signal noise reduction through neural network filtering is a well-known technique in signal processing, representing a predictable solution to improving measurement quality
Source Patent Element
Medical equipment connector for blood pressure monitoring
PTD Variation
Adding warning module to alert users about improper device connection
Obviousness Reasoning
Safety alert systems for medical devices are standard design considerations, representing an obvious user interface enhancement
Source Patent Element
Blood pressure measurement system
PTD Variation
Implementing statistical model for long-term calibration compensation
Obviousness Reasoning
Developing calibration models to address measurement drift is a standard engineering approach for maintaining sensor accuracy over time
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857295 and the published technical disclosure, a person of ordinary skill in the art would find the proposed hemodynamic monitoring system variations obvious and anticipated, as the modifications represent predictable engineering solutions using known techniques in medical sensor technology, signal processing, and diagnostic system design.

Original Patent Information

Patent NumberUS 11,857,295
TitleConnectors for medical equipment
Assignee(s)WELCH ALLYN, INC.