BIOFEEDBACK IMPLANTS FOR CHRONIC PAIN MANAGEMENT

Abstract

ABSTRACT The present invention discloses a biofeedback implant for chronic pain management, designed to address the limitations of current pain therapies. The implantable device comprises biosensors to continuously monitor pain-related neural signals, a signal processing unit for real-time analysis, and a biofeedback mechanism to deliver personalized feedback, such as electrical stimulation or thermal modulation. The closed-loop system adapts its therapy based on the individual's unique pain patterns and physiological responses, enabling targeted and optimized pain relief. The invention empowers patients to actively participate in their pain management through a user-friendly interface, potentially reducing reliance on medications and invasive procedures.

Specification

Description:BIOFEEDBACK IMPLANTS FOR CHRONIC PAIN MANAGEMENT

Field of Invention
The present invention relates to the biofeedback implants designed to help manage chronic pain. More particularly, a biofeedback implants for chronic pain management.

Background of the Invention
Biofeedback is a type of mind-body technique you use to control some of your body's functions, such as your heart rate, breathing patterns and muscle responses. During biofeedback, you're connected to electrical pads that help you get information about your body. There are several types of biofeedback therapy. It can help manage conditions like chronic pain, anxiety and incontinence. There are certain prior arts such as
Traditional Biofeedback Techniques: • Reference: deCharms RC, Maeda F, Glover GH, Ludlow D, Pauly JM, Soneji D, Gabrieli JD, Mackey SC. Control over brain activation and pain learned by using real-time functional MRI. Proc Natl Acad Sci U S A. 2005 Aug 2;102(31):10926-30. • Problem: Traditional biofeedback often relies on external sensors and feedback mechanisms, which can be cumbersome and limit the patient's mobility and ability to integrate the therapy into daily life. • Technical Drawback: There is a lack of continuous, real-time monitoring and feedback, especially during activities outside of a clinical setting.
Neurostimulation Devices: • Reference: Deer TR, Mekhail N, Provenzano D, Pope JE, Krames E, Slavin KV. The appropriate use of neurostimulation of the spinal cord and peripheral nervous system for the treatment of chronic pain and ischemic diseases: the Neuromodulation Appropriateness Consensus Committee (NACC) recommendations. Pain Med. 2014 Sep;15(9):1580-97. • Problem: Current neurostimulation devices often rely on pre-programmed stimulation patterns and are unable to adapt to the individual's changing pain experience. • Technical Drawback: Limited personalization and lack of closed-loop feedback based on real-time physiological data.
Implantable Drug Delivery Systems: • Reference: Deer TR, Pope JE, Hayek SM, Abejón D, Campos D, Hassenbusch SJ, Leknes S, Milligan K, Nickel FT, Panchal SJ, Patel VB, Schultz DM, Vallejo R, Webster LR. The Neurostimulation Appropriateness Consensus Committee (NACC) recommends using intrathecal drug delivery in the treatment of chronic pain. Pain Med. 2020 Jan 1;21(1):16- 34. • Problem: While effective in delivering medication, these systems do not directly address the underlying neural mechanisms of pain or give the patient a sense of control. • Technical Drawback: Lack of a biofeedback component and potential for side effects associated with long-term medication use.
Problems
• Limited real-time monitoring and adaptive feedback.
• Lack of personalization based on individual pain patterns.
• Limited patient engagement and control over their pain management.
• Reliance on external devices or medication with potential side effects.
The present biofeedback implants aim to overcome these limitations by providing a closed-loop system that continuously monitors pain signals, adapts to the individual's needs, and empowers the patient to participate in their pain management actively.

Objectives of the Invention
The prime objective of the present invention is to provide a biofeedback implants for chronic pain management.
Another object of this invention is to provide the biofeedback implants for chronic pain management that is implantable, minimizing the need for external components and enabling continuous monitoring and feedback.
Another objective of the present invention is to provide the biofeedback implants for chronic pain management that is personalized and adaptive, tailoring the therapy to the individual's specific pain patterns and needs in real time.
Another objective of the present invention is to provide the biofeedback implants for chronic pain management that is a closed-loop, allowing for real-time adjustments based on the patient's physiological response.
Another objective of the present invention is to provide the biofeedback implants for chronic pain management where empowering gives the patient more control and engagement in pain management.
Another objective of the present invention is to provide the biofeedback implants for chronic pain management that is potentially safer by reducing the reliance on medications with potential side effects and minimizing the invasiveness of some current procedures.
Yet another object of this invention is to provide the biofeedback implants for chronic pain management that offers a more effective, personalized, and patient-centric approach to chronic pain management, addressing key limitations in existing solutions.
These and other objects of the present invention will be apparent from the drawings and descriptions herein. Every object of the invention is attained by at least one embodiment of the present invention.

Summary of the Invention
In one aspect of the present invention provides a biofeedback implants for chronic pain management, the biofeedback implants are an implantable medical device that continuously monitors pain-related signals from the nervous system, by analyzing these signals in real time, the implant provides personalized biofeedback to the user, potentially through electrical stimulation or other mechanisms.

In one of the aspects, in the present invention, the closed-loop system enables the device to adapt its therapy based on the individual's unique pain patterns and physiological responses, optimizing pain management and improving overall effectiveness.

In one of the aspects, the present invention eliminates the need for external devices or frequent clinical visits, enabling continuous monitoring and feedback even during daily activities, it empowers patients to actively participate in their pain management, fostering a sense of control and improving their quality of life.

Brief Description of Drawings
The drawings described herein are for illustrative purposes only of selected embodiments and not all possible implementations, and are not intended to limit the scope of the present disclosure. Further objectives and advantages of this invention will be more apparent from the ensuing description when read in conjunction with the accompanying drawing and wherein:
Figure 1 illustrates the Closed-Loop Pain Management System flow diagram according to an embodiment of the present invention.
Figure 2 illustrates the Adaptive Closed-Loop Neuromodulation for Pain Management flow diagram according to an embodiment of the present invention.
Figure 3 illustrates the Biofeedback-Based Adaptive Pain Management System flow diagram according to an embodiment of the present invention.


DETAIL DESCRIPTION OF INVENTION
Unless the context requires otherwise, throughout the specification which follow, the word "comprise" and variations thereof, such as, "comprises" and "comprising" are to be construed in an open, inclusive sense that is as "including, but not limited to".
In the following description, numerous specific details are set forth in order to provide a thorough understanding of embodiments of the present invention. It will be apparent to one skilled in the art that embodiments of the present invention may be practiced without some of these specific details.
Reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
As used in this specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the content clearly dictates otherwise. It should also be noted that the term "or" is generally employed in its sense including "and/or" unless the content clearly dictates otherwise.
The embodiments are in such detail as to clearly communicate the disclosure. However, the amount of detail offered is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the present disclosure as defined by the appended claims.
The headings and abstract of the invention provided herein are for convenience only and do not interpret the scope or meaning of the embodiments. Reference will now be made in detail to the exemplary embodiments of the present invention.
The present invention discloses a biofeedback implant for chronic pain management that operates on a closed loop principle, continuously monitoring pain-related neural signals through implanted biosensors.
In describing the preferred embodiment of the present invention, reference will be made herein to like numerals refer to like features of the invention.
According to an embodiment of the invention, Figure 1 depicts a process flow for a closed-loop system, likely designed for pain management. It starts with initialization, involves acquiring neural signals, and detecting and recognizing pain patterns. Based on this, feedback is generated and adjusted in real-time. The system also includes machine learning for long-term adaptation, data logging and communication for remote monitoring and adjustments, and periodic recalibration to ensure optimal performance.
According to an embodiment of the invention, Figure 2 depicts a flowchart illustrating a closed-loop system for pain management. The process begins with initialization, where sensors are loaded, and pre-trained models and parameters are set. Neural signals are then acquired, filtered, and converted for pain detection and recognition. If pain is detected, feedback is generated, involving appropriate stimulation or thermal therapy selection. This feedback is applied, and the system monitors real-time feedback for adjustments. Data is logged and stored for machine learning and adaptive learning purposes. Remote monitoring and alerts ensure safety and allow for further interventions.
According to an embodiment of the invention, Figure 3 depicts a biofeedback-based system for adaptive pain management. It starts by acquiring neural signals and checking for pain. If detected, the system classifies pain intensity and location, then generates and applies biofeedback to the patient. The system continuously monitors the patient's physiological response and adjusts the feedback if pain isn't reduced. Session data is stored and used for adaptive learning with machine learning. Data is also transmitted for remote monitoring and adjustments; periodic recalibration ensures the system's effectiveness.
According to an embodiment of the invention, the biofeedback implant for chronic pain management comprises of sub parts/module such as: Neural Signal Acquisition Module, Signal Pre-Processing Module, Neural Pattern Recognition and Decoding Module, Real-Time Analysis and Feedback Generation Module, Therapeutic Stimulation or Feedback Module.
According to another embodiment of the invention, the Neural Signal Acquisition Module further comprises of:
• Sensors (Neural Electrodes)- Collect electrical signals from neurons associated with pain perception;
• Signal Amplifiers: Boost weak neural signals for unambiguous interpretation;
• Neural Interface: Connects sensors to the implant system and facilitates communication between the nervous system and the device.
According to another embodiment of the invention, the Signal Pre-Processing Module further comprises of:
• Signal Filters: Remove noise and irrelevant data from neural signals to ensure accurate readings;
• Analog-to-Digital Converter (ADC): Converts the analog neural signals into digital form for processing by the implant's algorithms;
• Data Compression Unit: Reduces the size of the collected data for efficient storage and transmission.
According to another embodiment of the invention, the Neural Pattern Recognition and Decoding Module further comprises of:
• Signal Pattern Recognition Algorithms: Analyze the neural data to detect pain-related patterns and determine the intensity or location of pain;
• Neural Decoder: Translate the recognized patterns into actionable data to guide biofeedback therapy;
According to another embodiment of the invention, the Real-Time Analysis and Feedback Generation Module further comprises of:
• Control Algorithms: Implement real-time decision-making processes to adjust the biofeedback response based on the decoded neural patterns;
• Biofeedback Generator: This generator produces the appropriate biofeedback response, such as electrical stimulation or other feedback mechanisms, tailored to the patient's pain signals;
• Stimulator Control Unit: Governs the intensity, frequency, and type of biofeedback stimulation delivered.
According to another embodiment of the invention, the Therapeutic Stimulation or Feedback Module further comprises of:
• Electrical Stimulators: Deliver targeted electrical pulses to specific nerves to alleviate pain based on the analyzed neural data. - May include vibration, thermal feedback, or other stimuli to aid in pain relief;
According to another embodiment of the invention, the biofeedback implant for chronic pain management uses sensors that are critical for real-time monitoring of neural signals and physiological responses. Below are some of the common types of sensors that would typically be used in such a system:' such as Neural Signal Sensors (Electrodes):
• Electroencephalography (EEG) Electrodes: These detect electrical activity in the brain. In this case, they would be adapted to monitor neural signals related to pain.
• Electrocorticography (ECoG) Electrodes: These are implanted on the brain's surface to record neural signals with higher resolution than EEG.
• Intracortical Microelectrodes: These sensors are implanted directly into neural tissue to record specific neuronal activity.
• Pressure Sensors: These can detect physical pressure on tissues or joints, providing additional context to neural signals for detecting chronic pain associated with mechanical stress.
• Electromyography (EMG) Sensors: EMG sensors detect electrical activity produced by muscles. They can be used to monitor muscle tension, which is often related to chronic pain, especially in conditions like fibromyalgia or back pain.
• Heart Rate Variability (HRV) Sensors: These sensors measure heart rate variability, which is linked to the autonomic nervous system and pain levels. They help assess stress-or pain-induced changes in heart function.
• Skin Conductance Sensors (Galvanic Skin Response - GSR): These sensors measure the skin's electrical conductance, which varies with sweat production. Changes in skin conductance can indicate emotional or physical stress, including pain.
According to another embodiment of the invention, the biofeedback implant for chronic pain management works in the following manner:
the biofeedback implant operates on a closed loop principle, continuously monitoring pain-related neural signals through implanted biosensors. An onboard signal processing unit analyzes this data in real-time, identifying individual pain patterns and thresholds. Based on this analysis, the implant delivers personalized biofeedback, potentially via electrical stimulation to disrupt pain pathways or thermal modulation to soothe affected areas. The system dynamically adapts its therapy, adjusting stimulation parameters or temperature based on the user's physiological responses, ensuring optimal pain relief and comfort.
It may utilize different sensor types (e.g., electrical, thermal, or chemical) and biofeedback mechanisms, with a multi-modal approach potentially offering the most comprehensive solution by combining multiple modalities. A user interface allows patients to visualize their pain data and adjust settings within safe limits, fostering active participation in their pain management.
The best method likely involves this multi-modal, closed-loop system, empowered by advanced signal processing and machine learning, to deliver adaptable, personalized, and effective chronic pain relief while minimizing side effects and risks associated with traditional treatments.
According to another embodiment of the invention, the biofeedback implant for chronic pain management has a highly promising industrial application lies in the realm of professional sports. Athletes frequently experience chronic pain due to intense training, repetitive movements, and injuries. This can significantly impact their performance, lead to prolonged recovery periods, and even shorten their careers. The implant could offer a revolutionary solution by continuously monitoring athletes' physiological signals, identifying early signs of stress or injury, and providing personalized biofeedback to manage pain and optimize training regimens. By proactively addressing pain and promoting faster recovery, the implant could help athletes maintain peak performance, extend their careers, and reduce the reliance on potentially harmful pain medications. Furthermore, aggregated data from multiple athletes could provide valuable insights into injury patterns and training practices, enabling teams and coaches to develop more effective injury prevention strategies and training programs, ultimately benefiting the entire sports industry.
According to another embodiment of the invention, the biofeedback implant for chronic pain management has following features that sets it prat from prior arts:
1. Closed-Loop Biofeedback System: The biofeedback implant integrates real-time biosensing, signal processing, and personalized biofeedback delivery into a closed-loop system. This enables the implant to adapt its therapy dynamically based on the individual's unique pain patterns and physiological responses, going beyond pre-programmed or open-loop stimulation approaches found in prior art.
2. Implantable Design for Continuous Monitoring: By being fully implantable, the device allows for continuous, long-term monitoring of pain-related signals, even during daily activities. This overcomes the limitations of external sensors or infrequent clinical visits seen in existing biofeedback and pain management technologies.
3. Personalized and Adaptive Biofeedback: The biofeedback implant employs advanced signal processing algorithms to analyze individual pain patterns and thresholds. This enables the delivery of highly personalized biofeedback, tailored to the specific needs of each user, addressing the lack of personalization in many current pain management solutions.
4. Patient Empowerment and Control: Through a user-friendly interface, the invention allows patients to visualize their pain data, understand their pain patterns, and adjust biofeedback parameters within safe limits. This fosters active participation in pain management, contrasting with the passive nature of many existing treatments.
5. Minimized Side Effects and Risks: By potentially reducing the reliance on medications and invasive procedures, the biofeedback implant aims to minimize the side effects and risks associated with current chronic pain management options.
6. Potential for Long-Term Efficacy: The combination of continuous monitoring, personalized biofeedback, and patient empowerment may lead to improved long-term pain management outcomes compared to existing solutions that often provide temporary or limited relief.

Although a preferred embodiment of the invention has been illustrated and described, it will at once be apparent to those skilled in the art that the invention includes advantages and features over and beyond the specific illustrated construction. Accordingly it is intended that the scope of the invention be limited solely by the scope of the hereinafter appended claims, and not by the foregoing specification, when interpreted in light of the relevant prior art.
, Claims:We Claim;
1. A biofeedback implant for chronic pain management comprising:
• Neural Signal Acquisition Module;
• Signal Pre-Processing Module;
• Neural Pattern Recognition and Decoding Module;
• Real-Time Analysis and Feedback Generation Module, and
• Therapeutic Stimulation or Feedback Module.

2. The biofeedback implant for chronic pain management as claimed in claim 1, wherein the Neural Signal Acquisition Module further comprises of:
• Sensors (Neural Electrodes) to collect electrical signals from neurons associated with pain perception;
• Signal Amplifiers are used to boost weak neural signals for unambiguous interpretation;
• Neural Interface, connects sensors to the implant system and facilitates communication between the nervous system and the device.

3. The biofeedback implant for chronic pain management as claimed in claim 1, wherein the Signal Pre-Processing Module further comprises of:
• Signal Filters to remove noise and irrelevant data from neural signals to ensure accurate readings;
• Analog-to-Digital Converter (ADC) to convert the analog neural signals into digital form for processing by the implant's algorithms;
• Data Compression Unit reduces the size of the collected data for efficient storage and transmission.

4. The biofeedback implant for chronic pain management as claimed in claim 1, wherein the Neural Pattern Recognition and Decoding Module further comprises of:
• Signal Pattern Recognition Algorithms to analyse the neural data to detect pain-related patterns and determine the intensity or location of pain;
• Neural Decoder translate the recognized patterns into actionable data to guide biofeedback therapy.

5. The biofeedback implant for chronic pain management as claimed in claim 1, wherein, the Real-Time Analysis and Feedback Generation Module further comprises of:
• Control Algorithms to implement real-time decision-making processes to adjust the biofeedback response based on the decoded neural patterns;
• Biofeedback Generator produces the appropriate biofeedback response, such as electrical stimulation or other feedback mechanisms, tailored to the patient's pain signals;
• Stimulator Control Unit governs the intensity, frequency, and type of biofeedback stimulation delivered.

6. The biofeedback implant for chronic pain management as claimed in claim 1, wherein, the Therapeutic Stimulation or Feedback Module further comprises of: Electrical Stimulators to deliver targeted electrical pulses to specific nerves to alleviate pain based on the analysed neural data.

7. The biofeedback implant for chronic pain management as claimed in claim 1, wherein, the biofeedback implant comprises of sensors selected from the group of: Electroencephalography (EEG) Electrodes, Electrocorticography (ECoG) Electrodes, Intracortical Microelectrodes, Pressure Sensors, Electromyography (EMG) Sensors, Heart Rate Variability (HRV) Sensors, Skin Conductance Sensors (Galvanic Skin Response - GSR).

8. The biofeedback implant for chronic pain management as claimed in claim 1, wherein, the process flow for a closed-loop system for pain management is as follows:
• starts with initialization, involves acquiring neural signals, and detecting and recognizing pain patterns;
• Based on this, feedback is generated and adjusted in real-time;
• The system also includes machine learning for long-term adaptation, data logging and communication for remote monitoring and adjustments, and periodic recalibration to ensure optimal performance.

9. The biofeedback implant for chronic pain management as claimed in claim 1, wherein, the closed-loop system for pain management is as follows:
• The process begins with initialization, where sensors are loaded, and pre-trained models and parameters are set;
• Neural signals are then acquired, filtered, and converted for pain detection and recognition;
• If pain is detected, feedback is generated, involving appropriate stimulation or thermal therapy selection;
• This feedback is applied, and the system monitors real-time feedback for adjustments;
• Data is logged and stored for machine learning and adaptive learning purposes;
• Remote monitoring and alerts ensure safety and allow for further interventions.

10. The biofeedback implant for chronic pain management as claimed in claim 1, wherein, the biofeedback-based system for adaptive pain management is as follows:
• It starts by acquiring neural signals and checking for pain;
• If detected, the system classifies pain intensity and location, then generates and applies biofeedback to the patient;
• The system continuously monitors the patient's physiological response and adjusts the feedback if pain isn't reduced;
• Session data is stored and used for adaptive learning with machine learning
• Then data is also transmitted for remote monitoring and adjustments and periodic recalibration ensures the system's effectiveness.

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