Next-Generation Sleep Disorder Treatment System

Publication ID: 24-11857456_0010_PTD
Published: October 28, 2025
Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Next-Generation Sleep Disorder Treatment System,” Published Technical Disclosure No. 24-11857456_0010_PTD, Published October 28, 2025, available at https://archive.pr1or.art/24-11857456_0010_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. 11,857,456.

Summary of the Inventive Concept

A wearable dental appliance with integrated sensors and AI-powered software predicts and prevents sleep apnea episodes, while a cloud-based platform enables remote monitoring and personalized treatment adjustments.

Background and Problem Solved

The original patent, 'Method and system for homogeneous dental appliance', addressed the limitations of traditional dental appliances for sleep apnea treatment. However, these appliances lacked real-time monitoring and personalized adjustments, leading to suboptimal treatment outcomes. The new inventive concept addresses this limitation by integrating sensors, AI-powered software, and cloud-based remote monitoring to provide more effective and personalized sleep disorder treatment.

Detailed Description of the Inventive Concept

The next-generation sleep disorder treatment system comprises a wearable dental appliance with integrated sensors that track a patient's sleep patterns, oral characteristics, and medical history. The appliance communicates with a cloud-based platform, which utilizes machine learning algorithms to analyze the data and provide personalized treatment recommendations. The system also includes a mobile app for tracking sleep quality and apnea events, and a cloud-based analytics platform for identifying trends and providing recommendations for improving sleep health. The dental appliance can be customized using machine learning algorithms to optimize airflow and comfort features, and can be manufactured using 3D printing or other advanced techniques.

Novelty and Inventive Step

The new inventive concept introduces a paradigm shift in sleep disorder treatment by integrating real-time monitoring, AI-powered software, and cloud-based remote monitoring. This enables personalized treatment adjustments, improved treatment outcomes, and enhanced patient engagement. The use of machine learning algorithms to customize the dental appliance and predict sleep apnea episodes is a novel and non-obvious advancement over the original patent.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include the use of different sensor technologies, such as MEMS sensors or EEG sensors, or the integration of additional features, such as snore detection or sleep stage tracking. The system could also be adapted for use with other sleep disorders, such as insomnia or restless leg syndrome.

Potential Commercial Applications and Market

The next-generation sleep disorder treatment system has significant commercial potential in the sleep health industry, which is projected to reach $17.4 billion by 2025. The system could be marketed to sleep clinics, hospitals, and dental offices, as well as directly to consumers through online platforms or retail partnerships.

CPC Classifications

SectionClassGroup
A A61 A61F5/56
A A61 A61C7/08
A A61 A61C7/36
B B29 B29C45/00
B B29 B29C51/10
B B29 B29C64/00

Field of Art

Medical device engineering, specifically dental appliances for sleep disorder treatment, involving biomechanical design, sensor integration, additive manufacturing, and digital health technologies

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer or dental technology specialist with expertise in 3D printing, medical device design, sensor integration, and machine learning applications in healthcare, typically holding a master's or doctoral degree with 3-5 years of industry experience

Obviousness Rationale

A PHOSITA would recognize that integrating sensor technologies, machine learning algorithms, and cloud-based monitoring into existing dental appliance designs represents a predictable technological evolution. The source patent's foundational work on dental sleep apnea appliances provides a clear technical framework that naturally suggests enhancement through digital health technologies. The proposed variations represent incremental improvements using standard engineering techniques and readily available technological components.

Obvious Combinations & Variations

Source Patent Element
3D printed dental appliance using polymerizable resin compositions
PTD Variation
Adding integrated sensors and machine learning customization during 3D printing process
Obviousness Reasoning
Modifying manufacturing process to incorporate sensors is a known technique in medical device production, representing a predictable application of existing 3D printing capabilities
Source Patent Element
Dental appliance designed for mandibular advancement
PTD Variation
Adding real-time sleep pattern monitoring and AI-powered episode prediction
Obviousness Reasoning
Enhancing medical devices with sensor and predictive technologies is a standard approach in medical engineering, with clear potential for improved patient outcomes
Source Patent Element
Patient oral characteristic data processing method
PTD Variation
Cloud-based platform for remote monitoring and personalized treatment adjustments
Obviousness Reasoning
Extending data processing capabilities to cloud platforms is a routine digital transformation strategy in medical technology, representing an obvious technological progression
Source Patent Element
Dental appliance manufacturing using thermoplastic and polymerizable materials
PTD Variation
Incorporating MEMS sensors and detachable modular design for sleep tracking
Obviousness Reasoning
Integrating miniature sensors into existing device architectures is a well-established engineering practice with predictable implementation strategies
Source Patent Element
Method for determining patient dentition and mandibular positioning
PTD Variation
Machine learning algorithms for dynamic appliance customization and sleep event prediction
Obviousness Reasoning
Applying machine learning to existing medical diagnostic methodologies represents a standard technological enhancement with foreseeable implementation approaches
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857456 and the disclosed technical variations, a person of ordinary skill in the art would find the proposed sleep disorder treatment system and associated methods obvious and non-patentable. The incremental technological enhancements involving sensor integration, machine learning, and cloud-based monitoring represent predictable extensions of existing dental appliance design principles, thereby rendering subsequent claims obvious under 35 U.S.C. Section 103.

Original Patent Information

Patent NumberUS 11,857,456
TitleMethod and system for homogeneous dental appliance