Advanced Ultrasonic Detection System for Next-Generation Device Distraction

Publication ID: 24-11857226_0005_PTD
Published: November 07, 2025
Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Advanced Ultrasonic Detection System for Next-Generation Device Distraction,” Published Technical Disclosure No. 24-11857226_0005_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857226_0005_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. 11,857,226.

Summary of the Inventive Concept

A novel system utilizing machine learning and neural networks to detect device distraction in real-time, enabling personalized and precise treatment of skeletal system disorders.

Background and Problem Solved

The original patent disclosed systems and methods for ultrasonic detection of device distraction, but it relied on manual detection and lacked real-time analysis. This new inventive concept addresses these limitations by introducing advanced machine learning algorithms and neural networks to detect anomalies indicative of device distraction, providing a more accurate and efficient solution.

Detailed Description of the Inventive Concept

The advanced ultrasonic detection system consists of a handheld ultrasonic probe, a processing unit, and a database of subject-specific ultrasonic signal patterns. The probe transmits ultrasonic signals and receives echoes, which are then analyzed by the processing unit using machine learning algorithms to detect anomalies indicative of device distraction. The system can generate 3D point clouds of a subject's skeletal system, enabling real-time analysis and personalized treatment. The neural network is trained on a dataset of ultrasonic signals to detect anomalies, ensuring high accuracy and efficiency.

Novelty and Inventive Step

The use of machine learning algorithms and neural networks to detect device distraction in real-time, combined with the ability to generate 3D point clouds and perform personalized analysis, represents a significant departure from the original patent and provides a novel solution to the problem of device distraction detection.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include the use of different machine learning algorithms, such as deep learning or reinforcement learning, or the integration of additional sensors, such as accelerometers or gyroscopes, to enhance the accuracy of the system. Variations could also include the development of specialized probes for specific skeletal system disorders or the creation of a cloud-based platform for remote analysis and treatment.

Potential Commercial Applications and Market

The advanced ultrasonic detection system has significant commercial potential in the medical device industry, particularly in the treatment of skeletal system disorders such as limb lengthening and osteogenesis. The system's ability to provide real-time analysis and personalized treatment could revolutionize the field, offering a more accurate and efficient solution for patients and healthcare professionals alike.

CPC Classifications

SectionClassGroup
A A61 A61B17/7216
A A61 A61B17/68
A A61 A61B17/7016
A A61 A61B90/06
A A61 A61B17/702
A A61 A61B17/7008
A A61 A61B17/7068
A A61 A61B2017/681
A A61 A61B2090/061
A A61 A61B2090/3925
A A61 A61B2090/3929
Y Y10 Y10T29/49963
Y Y10 Y10T29/49966

Field of Art

Medical device engineering, specifically orthopedic surgical technologies focused on skeletal system interventions and diagnostic imaging techniques

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer or medical device designer with expertise in ultrasonic imaging, machine learning applications in medical diagnostics, and orthopedic surgical technologies, holding advanced degrees in bioengineering or medical engineering with 3-5 years of specialized experience

Obviousness Rationale

A PHOSITA would recognize that applying machine learning techniques to ultrasonic detection of device distraction represents a predictable extension of existing medical imaging technologies. The combination of neural network analysis with ultrasonic imaging provides a natural progression in diagnostic precision, leveraging well-established machine learning approaches to enhance existing medical device monitoring techniques. The technical variations disclosed demonstrate incremental improvements that would be obvious to a skilled practitioner seeking more advanced diagnostic capabilities.

Obvious Combinations & Variations

Source Patent Element
Distraction device with capability for monitoring skeletal system interventions
PTD Variation
Machine learning-enhanced ultrasonic detection system for real-time device distraction monitoring
Obviousness Reasoning
Applying machine learning to existing medical device monitoring represents a known technique for improving diagnostic precision, with predictable results of enhanced detection capabilities
Source Patent Element
Monolithic member configured for attachment to skeletal system
PTD Variation
3D point cloud generation of skeletal system using ultrasonic signals
Obviousness Reasoning
Extending device monitoring techniques to create comprehensive spatial representations is a logical design choice for improving diagnostic accuracy
Source Patent Element
Dynamic seal to inhibit bodily fluid interference
PTD Variation
Subject-specific ultrasonic signal pattern database for personalized analysis
Obviousness Reasoning
Creating specialized diagnostic databases represents a predictable approach to improving medical device monitoring, building upon existing techniques for patient-specific medical interventions
Source Patent Element
Rotational locking mechanism for distraction device
PTD Variation
Neural network trained to detect anomalies in ultrasonic signal patterns
Obviousness Reasoning
Implementing machine learning algorithms for anomaly detection is a standard engineering approach to improving diagnostic precision in medical technologies
Source Patent Element
Device for manipulating skeletal system portions
PTD Variation
Handheld ultrasonic probe with integrated machine learning processing
Obviousness Reasoning
Miniaturization and integration of diagnostic technologies is a predictable evolution in medical device design, representing an obvious combination of known techniques
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857226 and the disclosed technical variations, a person of ordinary skill in the art would find the claimed innovations obvious, as the combination of ultrasonic imaging techniques with machine learning represents a predictable and incremental advancement in medical device monitoring technologies. The disclosed variations demonstrate no more than the application of known machine learning approaches to existing medical diagnostic methodologies, rendering any claims to such techniques obvious and unpatentable under 35 U.S.C. Section 103.

Original Patent Information

Patent NumberUS 11,857,226
TitleSystems and methods for ultrasonic detection of device distraction
Assignee(s)NuVasive Specialized Orthopedics, Inc.