Next-Generation Neural Activity Detection System

Publication ID: 24-11857348_0005_PTD
Published: October 28, 2025
Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Next-Generation Neural Activity Detection System,” Published Technical Disclosure No. 24-11857348_0005_PTD, Published October 28, 2025, available at https://archive.pr1or.art/24-11857348_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. 11,857,348.

Summary of the Inventive Concept

A wearable, optically-transparent neural interface that detects neural activity in the brain and uses machine learning to predict neural activity patterns, enabling real-time cognitive enhancement and personalized recommendations.

Background and Problem Solved

The original patent's techniques for determining timing uncertainty in optical measurement systems are limited to detecting neural activity in a controlled laboratory setting. However, the next-generation system addresses the need for a wearable, non-invasive, and real-time neural activity detection system that can be used in daily life, overcoming the limitations of traditional systems.

Detailed Description of the Inventive Concept

The system consists of a wearable, optically-transparent neural interface that captures individual photons with high time-of-arrival resolution using a photodetector array. The detected neural activity is then analyzed using machine learning algorithms to identify patterns indicative of neural activity. The system can be configured to provide real-time neural activity feedback, enabling users to adjust their cognitive states in real-time. The system can also be integrated with a cloud-based analytics platform to provide personalized recommendations for cognitive enhancement.

Novelty and Inventive Step

The new claims introduce a wearable, optically-transparent neural interface and machine learning-based pattern recognition, which are novel and non-obvious compared to the original patent's laboratory-based systems. The inventive step lies in the integration of these components to enable real-time, non-invasive neural activity detection and personalized recommendations.

Alternative Embodiments and Variations

Alternative embodiments may include using a swarm of micro-scale, biocompatible photodetectors or a non-invasive, optically-based neural interface. Variations may include using different machine learning algorithms or integrating the system with other wearable devices or virtual reality platforms.

Potential Commercial Applications and Market

The next-generation neural activity detection system has significant commercial potential in the healthcare, education, and gaming industries, enabling real-time cognitive enhancement, personalized recommendations, and immersive gaming experiences.

CPC Classifications

SectionClassGroup
A A61 A61B5/7214
A A61 A61B5/0082
A A61 A61B5/6803
A A61 A61B2562/0238
A A61 A61B2562/046
A A61 A61B2576/026

Field of Art

Biomedical imaging and neural activity detection systems, specifically optical measurement technologies for neurological monitoring with expertise in photon detection, time-resolved measurement, and signal processing techniques

Person of Ordinary Skill (PHOSITA) Profile

A skilled practitioner with advanced degrees in biomedical engineering, optics, or neuroscience, possessing knowledge of time-to-digital conversion, photodetector arrays, signal processing algorithms, and neural interface technologies

Obviousness Rationale

A person of ordinary skill would recognize that extending the source patent's optical measurement system to a wearable neural interface represents a predictable application of existing technologies. The fundamental signal detection and time-resolved measurement principles remain consistent, with the primary innovation being miniaturization and integration of machine learning techniques. The combination of known optical detection methods with emerging machine learning approaches would be a natural progression for a skilled practitioner seeking to enhance neural activity monitoring.

Obvious Combinations & Variations

Source Patent Element
Time-to-digital converter (TDC) for measuring light pulse occurrences
PTD Variation
Photodetector array capturing individual photons with high time-of-arrival resolution
Obviousness Reasoning
A PHOSITA would recognize this as a straightforward scaling and optimization of existing time-resolved detection techniques, representing a predictable extension of known signal measurement principles
Source Patent Element
Optical measurement system for detecting component responses
PTD Variation
Wearable, optically-transparent neural interface for brain activity detection
Obviousness Reasoning
Miniaturization and adaptation of laboratory-based optical measurement systems to wearable form factors is a known design approach in biomedical engineering, representing an obvious technological progression
Source Patent Element
Signal processing for compensating measurement irregularities
PTD Variation
Machine learning algorithms for identifying neural activity patterns
Obviousness Reasoning
Applying advanced signal processing techniques like machine learning to improve measurement interpretation is a predictable evolution in signal analysis, particularly in complex biological measurement systems
Source Patent Element
Precision timing circuit for generating output pulses
PTD Variation
Cloud-based analytics platform for providing personalized cognitive recommendations
Obviousness Reasoning
Extending measurement systems to include data analysis and recommendation platforms is a natural technological progression, representing an obvious combination of signal detection and data processing technologies
Source Patent Element
Optical measurement system with configurable components
PTD Variation
Genetic algorithm for optimizing photodetector and TDC configurations
Obviousness Reasoning
Using optimization algorithms to improve sensor system performance is a well-established technique in engineering, representing a predictable application of known computational methods to sensor design
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857348 and the disclosed variations, a person of ordinary skill in the art would find the claimed neural activity detection system and methods to be obvious variations of existing optical measurement technologies. The combination of known time-resolved detection techniques, miniaturized optical interfaces, and machine learning signal processing represents a predictable technological progression that lacks inventive step under 35 U.S.C. Section 103.

Original Patent Information

Patent NumberUS 11,857,348
TitleTechniques for determining a timing uncertainty of a component of an optical measurement system
Assignee(s)HI LLC