Personalized Pain Management System Based on Real-time Brain Activity Analysis
Legal Citation
Summary of the Inventive Concept
A novel system that leverages machine learning, wearable EEG/MEG sensors, and real-time brain activity analysis to provide personalized pain management, enabling more effective and adaptive therapy settings.
Background and Problem Solved
The original patent disclosed a method for pain management based on brain activity monitoring. However, it had limitations in terms of personalization, adaptability, and real-time responsiveness. The new inventive concept addresses these limitations by integrating machine learning, wearable sensors, and real-time analysis to provide a more effective and adaptive pain management system.
Detailed Description of the Inventive Concept
The system comprises a wearable EEG/MEG sensor array, a microcontroller, and a wireless transmitter. The sensor array detects brain activity signals, which are processed by the microcontroller to generate a personalized pain susceptibility score. This score is transmitted to a neuromodulation system, which adjusts therapy settings in real-time based on the score. The system can be trained using a deep learning algorithm and a patient population's brain activity data, enabling it to learn patterns indicative of pain susceptibility and improve over time.
Novelty and Inventive Step
The new inventive concept's novelty lies in its integration of machine learning, wearable sensors, and real-time analysis to provide personalized pain management. The inventive step is the use of a predictive model of pain susceptibility based on brain activity signals to adjust therapy settings in real-time, which is not anticipated by the original patent.
Alternative Embodiments and Variations
Alternative embodiments include using different types of sensors, such as functional near-infrared spectroscopy (fNIRS) or magnetoencephalography (MEG), or incorporating additional data sources, such as cardiovascular or respiratory signals. Variations may include using different machine learning algorithms or adapting the system for use in different therapeutic applications.
Potential Commercial Applications and Market
The inventive concept has significant commercial potential in the pain management market, which is expected to grow to $10 billion by 2025. The system's adaptability and personalization capabilities make it an attractive solution for patients and healthcare providers seeking more effective pain management solutions.
Section 103 Obviousness Analysis (PHOSITA)
Field of Art
Biomedical engineering, neurostimulation, and pain management technologies involving neural signal processing and adaptive medical device systems
Person of Ordinary Skill (PHOSITA) Profile
A biomedical engineer or neurotechnology specialist with expertise in neural signal processing, machine learning, medical device design, and pain management technologies, holding advanced degrees and practical experience in developing adaptive medical systems
Obviousness Rationale
A person of ordinary skill would recognize that integrating machine learning techniques with existing neuromodulation systems represents a predictable technological evolution. The source patent's foundation of brain activity-based pain management provides a clear framework for extending the technology through advanced signal processing and adaptive algorithms. The PTD's proposed variations are logical extensions of known techniques in neural interface and personalized medical technology.
Obvious Combinations & Variations
Original Patent Information
| Patent Number | US 11,857,794 |
|---|---|
| Title | Pain management based on brain activity monitoring |
| Assignee(s) | Boston Scientific Neuromodulation Corporation |