1. A portable neurofeedback device, comprising: a cerebro-signal interface module (CSIM) configured to capture and relay brainwave activity; a neuron-data computation unit (NDCU) for processing and interpreting signals from the CSIM; a bio-memory matrix (BMM) for chronologically storing neurofeedback sessions; a neura-comm interface (NCI) enabling wireless communication with external devices or platforms; and a user interaction portal (UIP) designed for configuring sessions, viewing feedback, and customizing alert preferences.

2. The device of claim 1, wherein the CSIM incorporates multi-node electrode connectivity to increase the granularity of brainwave capture.

3. The device of claim 1, further comprising: a harmonization audio-visual module (HAVM) that delivers synchronized stimuli designed to guide or influence the user's brainwave patterns.

4. The device of claim 1, wherein the NDCU employs an adaptive neuro-algorithm (ANA) that evolves based on longitudinal data from the BMM to enhance feedback precision.

5. The device of claim 1, further comprising: a self-sustaining power management core (PMCore) designed for extended operational durations and minimalistic energy consumption.

6. A method for providing neurofeedback using a portable device, comprising: obtaining neural signals via the cerebro-signal interface module (CSIM); decoding and analyzing these signals within the neuron-data computation unit (NDCU); storing session information within the bio-memory matrix (BMM); enabling user interaction and customization via the user interaction portal (UIP); and transmitting summarized feedback or raw neural data via the neura-comm interface (NCI).

7. The method of claim 6, further comprising: delivering harmonized audio-visual stimuli to the user through the harmonization audio-visual module (HAVM) to modulate specific brainwave patterns.

8. The method of claim 6, wherein the decoding step incorporates the adaptive neuro-algorithm (ANA) to iteratively refine signal interpretation based on historical user data from the BMM.

9. The method of claim 6, further comprising: alerting the user to deviations or anomalies in their neural patterns through a series of custom alerts from the user interaction portal (UIP).

10. The method of claim 6, further comprising: harvesting energy from ambient sources or through user interaction to recharge the self-sustaining power management core (PMCore), thus extending device usability. PORTABLE NEUROFEEDBACK DEVICE Abstract A groundbreaking portable neurofeedback device designed to capture, interpret, and provide real-time feedback on neural activity. This compact device seamlessly integrates advanced sensors to monitor brainwave patterns, with sophisticated algorithms processing these patterns to identify specific neural states or anomalies. Its portability ensures user flexibility, facilitating on-the-go neurofeedback sessions whether at home, work, or in therapeutic environments. Through immediate feedback, users can engage in self-regulation exercises or therapeutic interventions, offering a dynamic approach to brain health and cognitive enhancement. , Claims:Claims :

1. A portable neurofeedback device, comprising: a cerebro-signal interface module (CSIM) configured to capture and relay brainwave activity; a neuron-data computation unit (NDCU) for processing and interpreting signals from the CSIM; a bio-memory matrix (BMM) for chronologically storing neurofeedback sessions; a neura-comm interface (NCI) enabling wireless communication with external devices or platforms; and a user interaction portal (UIP) designed for configuring sessions, viewing feedback, and customizing alert preferences.

2. The device of claim 1, wherein the CSIM incorporates multi-node electrode connectivity to increase the granularity of brainwave capture.

3. The device of claim 1, further comprising: a harmonization audio-visual module (HAVM) that delivers synchronized stimuli designed to guide or influence the user's brainwave patterns.

4. The device of claim 1, wherein the NDCU employs an adaptive neuro-algorithm (ANA) that evolves based on longitudinal data from the BMM to enhance feedback precision.

5. The device of claim 1, further comprising: a self-sustaining power management core (PMCore) designed for extended operational durations and minimalistic energy consumption.

6. A method for providing neurofeedback using a portable device, comprising: obtaining neural signals via the cerebro-signal interface module (CSIM); decoding and analyzing these signals within the neuron-data computation unit (NDCU); storing session information within the bio-memory matrix (BMM); enabling user interaction and customization via the user interaction portal (UIP); and transmitting summarized feedback or raw neural data via the neura-comm interface (NCI).

7. The method of claim 6, further comprising: delivering harmonized audio-visual stimuli to the user through the harmonization audio-visual module (HAVM) to modulate specific brainwave patterns.

8. The method of claim 6, wherein the decoding step incorporates the adaptive neuro-algorithm (ANA) to iteratively refine signal interpretation based on historical user data from the BMM.

9. The method of claim 6, further comprising: alerting the user to deviations or anomalies in their neural patterns through a series of custom alerts from the user interaction portal (UIP).

10. The method of claim 6, further comprising: harvesting energy from ambient sources or through user interaction to recharge the self-sustaining power management core (PMCore), thus extending device usability.

Description:PORTABLE NEUROFEEDBACK DEVICE
Field of the Invention
[0001] The present invention broadly encompasses the domains of neurotechnology and portable diagnostic equipment. More specifically, it pertains to a portable neurofeedback device engineered to capture, interpret, and provide real-time feedback on neural activity and patterns. The device integrates state-of-the-art brainwave sensors, advanced computational algorithms, and user-friendly interfaces, making it possible to conduct on-the-go neurofeedback sessions. With its compact design and versatile functionality, the invention revolutionizes traditional neurofeedback practices by offering individuals a means to monitor and modulate their neural responses outside of clinical settings, promoting self-awareness, cognitive enhancement, and mental well-being.
[0001]
Background
[0002] The background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[0003] Neurofeedback, a subset of biofeedback, is a rapidly evolving field that focuses on providing individuals with real-time information about their brain activity. This information is then used to help them learn to regulate their brain functions, leading to potential cognitive improvements. Traditional neurofeedback systems were typically confined to clinical settings, involving complex and expensive equipment. However, recent advancements have led to the development of portable neurofeedback devices, enabling users to engage in brain training and cognitive enhancement activities in various environments.
[0004] Early neurofeedback systems utilized electroencephalography (EEG) technology to monitor and provide feedback on brainwave activity. These systems required users to be connected to a stationary machine via an array of electrodes on their scalp. While effective, the lack of portability limited their practicality for applications outside clinical settings.
[0005] Brain-Computer Interfaces (BCIs) have played a significant role in the development of portable neurofeedback devices. BCIs allow direct communication between the brain and external devices. Devices like Emotiv and NeuroSky headsets have utilized EEG technology to provide real-time feedback on brainwave patterns. These portable BCIs enable users to engage in neurofeedback training and cognitive exercises in a variety of contexts, from home to educational settings.
[0006] Wearable neurofeedback devices have gained traction as more compact and consumer-friendly options. These devices, like Muse and Melon headbands, incorporate dry electrodes that do not require gel for conductivity. This innovation makes the devices easier to use and reduces setup time. Wearable neurofeedback devices are often designed to enhance mindfulness, stress reduction, and cognitive training, thus making cognitive enhancement more accessible to a broader user base.
[0007] Another significant advancement is the integration of neurofeedback with smartphones and mobile apps. Developers have created apps that work with portable EEG devices, allowing users to track their brain activity and engage in brain-training exercises on their smartphones. This merging of technology makes neurofeedback more user-friendly and adaptable to daily routines.
[0008] Portable neurofeedback devices are increasingly adopting closed-loop systems. These systems continuously monitor brain activity, detect deviations from desired patterns, and provide immediate feedback to guide the user toward the target state. The real-time nature of closed-loop neurofeedback enhances the effectiveness of cognitive training, enabling users to learn more efficiently.
[0009] Portable neurofeedback devices mark a paradigm shift in the field by offering several unique features. The portability of these devices allows users to engage in brain training exercises in a wide range of settings, making cognitive enhancement a part of their daily routine. The user interfaces of these devices have been designed to be intuitive and user-friendly, reducing the learning curve and enabling a broader demographic to benefit from neurofeedback.
[00010] Many portable neurofeedback devices use machine learning algorithms to adapt the training to individual users, optimizing cognitive enhancement efforts for each person's unique brain activity. The integration of neurofeedback with smartphones and mobile apps enhances the user experience by enabling data tracking, progress monitoring, and gamified training exercises.
[00011] In conclusion, the development of portable neurofeedback devices represents a significant breakthrough in the field of cognitive enhancement. By overcoming the limitations of traditional neurofeedback systems, these devices offer convenience, accessibility, and personalized training to users seeking to improve their cognitive functions. The integration of advanced EEG technology, wearability, and smartphone compatibility makes portable neurofeedback devices a promising tool for enhancing cognitive abilities in various contexts.
[00012]
[00013] All references, including publications, patent applications, and patents, cited herein are hereby incorporated by reference to the same extent as if each reference were individually and specifically indicated to be incorporated by reference and were set forth in its entirety herein.
[00014] It also shall be noted that as used herein and in the appended claims, the singular forms “a”, “an”, and “the” include plural referents unless the context clearly dictates otherwise. This invention can be achieved by means of hardware including several different elements or by means of a suitably programmed computer. In the unit claims that list several means, several ones among these means can be specifically embodied in the same hardware item. The use of such words as first, second, third does not represent any order, which can be simply explained as names.
Summary
[00015] Various objects, features, and advantages of the disclosed subject matter can be more fully appreciated with reference to the following detailed description of the disclosed subject matter when considered in connection with the following drawings, in which like reference numerals identify like elements.
[00016] The present invention broadly encompasses the domains of neurotechnology and portable diagnostic equipment. More specifically, it pertains to a portable neurofeedback device engineered to capture, interpret, and provide real-time feedback on neural activity and patterns. The device integrates state-of-the-art brainwave sensors, advanced computational algorithms, and user-friendly interfaces, making it possible to conduct on-the-go neurofeedback sessions. With its compact design and versatile functionality, the invention revolutionizes traditional neurofeedback practices by offering individuals a means to monitor and modulate their neural responses outside of clinical settings, promoting self-awareness, cognitive enhancement, and mental well-being.
[00017]
[00018] Summarized herein a portable neurofeedback device that presents a revolutionary advancement in brainwave activity monitoring and cognitive enhancement. This device consists of five key components, merging neuroscience and technology to create a compact and effective tool for improving brain function.
[00019] At its core, the cerebro-signal interface module (CSIM) captures and transmits brainwave activity, providing a direct link to the user's cognitive processes. With multi-node electrode connectivity, the CSIM achieves a higher level of detail in capturing brainwave patterns, enabling precise analysis and feedback.
[00020] The neuron-data computation unit (NDCU) processes and interprets the signals received from the CSIM. This unit translates the complex brainwave data into actionable insights, enabling real-time analysis of cognitive patterns and functions.
[00021] To ensure continuity and progress tracking, the bio-memory matrix (BMM) chronologically stores neurofeedback sessions. This feature allows users to review and analyze their brainwave activity over time, facilitating an understanding of their cognitive evolution and the impact of interventions.
[00022] The neura-comm interface (NCI) adds a layer of connectivity, enabling wireless communication with external devices or platforms. This capability expands the device's functionality and potential for integrating with various applications and ecosystems.
[00023] The user interaction portal (UIP) acts as the user's gateway to the device's features. Through the UIP, users can configure neurofeedback sessions, visualize feedback, and customize alert preferences. This user-centric interface empowers individuals to tailor their cognitive enhancement experiences.
[00024] Enhancing the experience further, the harmonization audio-visual module (HAVM) synchronizes stimuli to guide or influence the user's brainwave patterns. This module introduces auditory and visual cues that aid in achieving desired cognitive states, promoting relaxation, focus, or other cognitive enhancements.
[00025] The neuron-data computation unit (NDCU) employs an adaptive neuro-algorithm (ANA) that evolves over time. By leveraging longitudinal data from the bio-memory matrix (BMM), the ANA continuously refines its analysis, enhancing the precision of the feedback provided.
[00026] To ensure seamless operation, the self-sustaining power management core (PMCore) is incorporated. This core extends the device's operational duration while minimizing energy consumption, making it ideal for prolonged sessions and on-the-go use.
[00027] In summary, the portable neurofeedback device revolutionizes cognitive enhancement through the integration of brainwave capture, signal processing, and user-friendly interfaces. With features such as multi-node electrode connectivity, harmonization audio-visual cues, adaptive neuro-algorithms, and energy-efficient operation, this device empowers users to enhance their cognitive function and gain insights into their cognitive progress. This innovation has the potential to impact diverse areas, from cognitive therapy and personal development to brain health research and neurofeedback training.
[00028] The method for providing neurofeedback through a portable device introduces an innovative approach to cognitive enhancement and self-improvement. Comprising five essential steps, this method seamlessly integrates technology and neuroscientific principles to offer users a personalized and convenient means of optimizing brain function.
[00029] The method begins with the cerebro-signal interface module (CSIM), which obtains neural signals directly from the user's brain. These signals provide a direct window into the user's cognitive activity, forming the foundation for the subsequent neurofeedback process.
[00030] The neuron-data computation unit (NDCU) decodes and analyzes the obtained neural signals within the portable device. This unit employs advanced algorithms to interpret the complex neural data, deriving meaningful insights that facilitate real-time analysis of cognitive patterns and states.
[00031] For continuity and progress tracking, the bio-memory matrix (BMM) records session information. This bio-memory matrix enables users to review their historical neural activity, aiding in understanding their cognitive journey, identifying patterns, and tracking changes over time.
[00032] Empowering user engagement and customization, the user interaction portal (UIP) serves as an interface for users to interact with the device. Through this portal, users can customize their neurofeedback sessions, visualize their cognitive feedback, and configure personalized alerts, enhancing the user experience.
[00033] The neura-comm interface (NCI) enables the device to communicate with external devices or platforms, facilitating the transmission of summarized feedback or raw neural data. This capability opens the door for integration with various applications, research studies, and cognitive training programs.
[00034] Furthermore, the method introduces the harmonization audio-visual module (HAVM), which delivers harmonized stimuli to the user. These stimuli, in the form of auditory and visual cues, modulate specific brainwave patterns to guide users toward desired cognitive states.
[00035] The decoding process within the neuron-data computation unit (NDCU) incorporates the adaptive neuro-algorithm (ANA). This algorithm iteratively refines its interpretation of neural signals based on historical user data from the bio-memory matrix (BMM), enhancing the precision of feedback and promoting personalized cognitive enhancement.
[00036] To alert users to deviations or anomalies in their neural patterns, the method employs custom alerts from the user interaction portal (UIP). These alerts offer timely insights and encourage users to take actions to optimize their cognitive function.
[00037] Energy sustainability is achieved through the self-sustaining power management core (PMCore). The method harnesses energy from ambient sources or user interactions to recharge the device, ensuring prolonged usability and minimizing the need for frequent recharging.
[00038] In summary, the method redefines cognitive enhancement through the integration of neural signal capture, decoding, customization, and energy efficiency. With features like personalized alerts, adaptive algorithms,

harmonized stimuli, and energy harvesting, this approach empowers users to optimize their cognitive function and embark on a journey of self-improvement. This innovation has the potential to impact various fields, from cognitive therapy and brain health research to neurofeedback training and personal development.
[00039]
Brief Description of the Drawings
[00040] The features and advantages of the present disclosure would be more clearly understood from the following description taken in conjunction with the accompanying drawings in which:
[00041] FIG. 1 represents an architectural overview of a portable neurofeedback device, according to some embodiments of the present disclosure.
[00042] FIG. 2 shows an exemplary detailed schematic flow diagram of a method for providing neurofeedback using a portable device, according to some embodiments of the present disclosure.
[00043]
Detailed Description
[00044] The following is a detailed description of exemplary embodiments to illustrate the principles of the invention. The embodiments are provided to illustrate aspects of the invention, but the invention is not limited to any embodiment. The scope of the invention encompasses numerous alternatives, modifications and equivalent; it is limited only by the claims.
[00045] In view of the many possible embodiments to which the principles of the present discussion may be applied, it should be recognized that the embodiments described herein with respect to the drawing figures are meant to be illustrative only and should not be taken as limiting the scope of the claims. Therefore, the techniques as described herein contemplate all such embodiments as may come within the scope of the following claims and equivalents thereof.
[00046] Throughout the present disclosure, the term “network” relates to an arrangement of interconnected programmable and/or non-programmable components that are configured to facilitate data communication between one or more electronic devices and/or databases, whether available or known at the time of filing or as later developed. Furthermore, the network may include, but is not limited to, one or more peer-to-peer network, a hybrid peer-to-peer network, local area networks (LANs), radio access networks (RANs), metropolitan area networks (MANS), wide area networks (WANs), all or a portion of a public network such as the global computer network known as the Internet, a private network, a cellular network and any other communication system or systems at one or more locations.
[00047] Throughout the present disclosure, the term “process”* relates to any collection or set of instructions executable by a computer or other digital system so as to configure the computer or the digital system to perform a task that is the intent of the process.
[00048] Throughout the present disclosure, the term ‘Artificial intelligence (AI)’ as used herein relates to any mechanism or computationally intelligent system that combines knowledge, techniques, and methodologies for controlling a bot or other element within a computing environment. Furthermore, the artificial intelligence (AI) is configured to apply knowledge and that can adapt it-self and learn to do better in changing environments. Additionally, employing any computationally intelligent technique, the artificial intelligence (AI) is operable to adapt to unknown or changing environment for better performance. The artificial intelligence (AI) includes fuzzy logic engines, decision-making engines, preset targeting accuracy levels, and/or programmatically intelligent software.
[00049] The detailed description is described with reference to the accompanying figures. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The use of the same reference numbers in different instances in the description and the figures may indicate similar or identical items.
[00050] Pursuant to the "Detailed Description" section herein, whenever an element is explicitly associated with a specific numeral for the first time, such association shall be deemed consistent and applicable throughout the entirety of the "Detailed Description" section, unless otherwise expressly stated or contradicted by the context.
[00051] The present invention broadly encompasses the domains of neurotechnology and portable diagnostic equipment. More specifically, it pertains to a portable neurofeedback device engineered to capture, interpret, and provide real-time feedback on neural activity and patterns. The device integrates state-of-the-art brainwave sensors, advanced computational algorithms, and user-friendly interfaces, making it possible to conduct on-the-go neurofeedback sessions. With its compact design and versatile functionality, the invention revolutionizes traditional neurofeedback practices by offering individuals a means to monitor and modulate their neural responses outside of clinical settings, promoting self-awareness, cognitive enhancement, and mental well-being.
[00052]
[00053] Pursuant to the "Detailed Description" section herein, whenever an element is explicitly associated with a specific numeral for the first time, such association shall be deemed consistent and applicable throughout the entirety of the "Detailed Description" section, unless otherwise expressly stated or contradicted by the context.
[00054] In recent years, the field of neurofeedback has witnessed remarkable advancements, with portable neurofeedback devices emerging as a significant innovation. These devices harness brainwave activity to provide users with real-time information and enable them to modulate their brain patterns for cognitive enhancement, stress reduction, and even therapeutic purposes. This disclosure delves into the key components and features of such a portable neurofeedback device 100, unravelling its potential to revolutionize brain-related interventions. Combining cutting-edge neuroscience, signal processing, and user interaction design, this device holds immense potential for enhancing brainwave activity monitoring and manipulation. The disclosure explores its various components, functionalities, and potential applications in both medical and non-medical domains.
[00055] According to a pictorial portrayal in FIG. 1, illustrating an architectural setup of the system 100 comprising a cerebro-signal interface module (CSIM) 102 configured to capture and relay brainwave activity, a neuron-data computation unit (NDCU) 104 for processing and interpreting signals from the CSIM, a bio-memory matrix (BMM) 106 for chronologically storing neurofeedback sessions, a neura-comm interface (NCI) 108 enabling wireless communication with external devices or platforms, and a user interaction portal (UIP) 110 designed for configuring sessions, viewing feedback, and customizing alert preferences.
[00056] At the core of the portable neurofeedback device is the Cerebro-Signal Interface Module (CSIM), a vital component responsible for capturing and relaying brainwave activity. This module utilizes multi-node electrode connectivity, facilitating the precise capture of brainwave data. Multi-node electrode connectivity enhances spatial resolution, enabling the device to capture brain activity from multiple regions simultaneously. This, in turn, enables more accurate and comprehensive neurofeedback. Imagine a user wearing the portable neurofeedback device, with its CSIM incorporating multi-node electrode connectivity. As the user engages in a cognitive task, the CSIM captures brainwave activity from distinct regions, allowing the device to provide detailed insights into the user's cognitive state.
[00057] In an embodiment, the Neuron-Data Computation Unit (NDCU) plays a critical role in processing and interpreting signals from the CSIM. Equipped with advanced signal processing algorithms, the NDCU transforms raw brainwave data into meaningful information. This unit employs adaptive neuro-algorithms (ANA) that evolve over time using longitudinal data to enhance the precision of the feedback provided. When a user wears the portable neurofeedback device, the NDCU processes the brainwave data captured by the CSIM. By employing the adaptive neuro-algorithm, the NDCU learns from previous sessions stored in the bio-memory matrix (BMM), optimizing the feedback given to the user during subsequent sessions.
[00058] In an embodiment, the Bio-Memory Matrix (BMM) serves as the device's memory bank, storing neurofeedback sessions chronologically. This storage system enables users and professionals to track progress, compare sessions, and gain insights into the effectiveness of interventions. The BMM contributes to the adaptive neuro-algorithm's evolution by providing longitudinal data for analysis and refinement. For instance, as a user engages in multiple neurofeedback sessions using the portable device, the BMM chronicles each session. Over time, the BMM accumulates a wealth of data that aids in refining the device's algorithms, leading to more personalized and effective neurofeedback.
[00059] In an embodiment, the Neura-Comm Interface (NCI) is a vital feature that facilitates wireless communication between the portable neurofeedback device and external devices or platforms. This interface enables data transfer, remote monitoring, and integration with other technologies, opening avenues for collaborative research, remote therapy, and data-driven interventions. The NCI empowers healthcare professionals to remotely monitor their patients' neurofeedback sessions, enabling them to adjust protocols and provide personalized guidance without the need for physical presence. Moreover, researchers can collect anonymized data from multiple users to gain insights into broader trends and patterns.
[00060] In an embodiment, the User Interaction Portal (UIP) is the interface through which users interact with the portable neurofeedback device. Designed for user-friendliness, the UIP allows users to configure sessions, view feedback, and customize alert preferences. The portal's intuitive design ensures that users can easily navigate and make the most of their neurofeedback experience. For instance, through the UIP, users can set preferences such as session duration, types of feedback (visual, auditory, or both), and notification thresholds. This customization empowers users to tailor their neurofeedback sessions according to their goals and preferences, enhancing their overall experience.
[00061] An innovative addition to the portable neurofeedback device is the Harmonization Audio-Visual Module (HAVM). This module delivers synchronized stimuli, such as audio cues and visual patterns, designed to guide or influence the user's brainwave patterns. By leveraging principles of entrainment and neuroplasticity, the HAVM enhances the device's effectiveness in facilitating desired cognitive states. A user seeking to improve their focus uses the HAVM during a neurofeedback session. The module delivers rhythmic auditory tones and synchronized visual cues, aligning with the brain's natural frequency range associated with concentration. Over time, the user's brainwave patterns may adapt to match these stimuli, resulting in improved focus and attention.
[00062] In an embodiment, the portable neurofeedback device employs an Adaptive Neuro-Algorithm (ANA) that evolves over time. This evolution is fueled by longitudinal data from the Bio-Memory Matrix (BMM). As the ANA analyzes data from multiple sessions, it fine-tunes its algorithms to provide increasingly accurate and personalized feedback. Consider a user with a history of anxiety who uses the portable device for neurofeedback. As the ANA processes data from multiple sessions and tracks improvements, it adjusts the feedback protocol to target the user's specific anxiety-related brainwave patterns, resulting in more effective anxiety reduction.
[00063] A crucial aspect of the portable neurofeedback device is its Self-Sustaining Power Management Core (PMCore). Engineered for extended operational durations and minimal energy consumption, the PMCore ensures that users can engage in prolonged neurofeedback sessions without constant battery replacements. A user using the portable neurofeedback device during a long flight can do so without worrying about battery life. The efficient PMCore design maximizes energy utilization, allowing the device to operate for extended periods without the need for frequent charging.
[00064] Portable neurofeedback devices hold immense potential in medical applications. They can be utilized for cognitive rehabilitation after brain injuries, as well as for managing conditions such as attention deficit hyperactivity disorder (ADHD), anxiety disorders, and post-traumatic stress disorder (PTSD). The device's ability to adapt its neuro-algorithms based on longitudinal data ensures tailored interventions for patients. For instance, a patient recovering from a traumatic brain injury uses the portable neurofeedback device to improve cognitive functions.
[00065] The device's ANA evolves over time, precisely targeting the areas of the brain affected by the injury and facilitating cognitive recovery.Beyond medical applications, portable neurofeedback devices have profound implications for cognitive enhancement in healthy individuals. By leveraging the device's capabilities to modulate brainwave patterns associated with specific cognitive states, these devices offer a unique opportunity for individuals to unlock and optimize their cognitive potential. This section explores the potential of portable neurofeedback devices in enhancing cognitive abilities such as focus, relaxation, and creativity.
[00066] One of the most sought-after cognitive enhancements is improved focus and concentration. In today's fast-paced world, maintaining sustained attention is crucial for productivity and success. Portable neurofeedback devices can assist users in achieving and sustaining states of heightened focus through targeted training. For example, a professional seeking enhanced productivity uses the portable neurofeedback device during work sessions. By configuring the device to provide auditory feedback when their brainwave patterns indicate a focused state, the user receives real-time reinforcement that encourages sustained attention. Over time, the user's brain becomes more adept at entering and maintaining focused states even during demanding tasks.
[00067] Stress and anxiety can hamper cognitive performance and overall well-being. Portable neurofeedback devices offer a potential solution by helping users achieve states of relaxation and stress reduction. By guiding users to modulate their brainwave patterns associated with calmness, these devices can contribute to improved emotional regulation and mental clarity. For example, a busy executive uses the portable neurofeedback device to unwind and alleviate stress after a long day. Through the device's bio-feedback mechanism, the user learns to recognize their brainwave patterns associated with relaxation. As they practice, the device delivers auditory cues or visual feedback when these patterns are detected, reinforcing the desired state. This regular practice gradually trains the brain to more easily access relaxed states, leading to improved stress management and cognitive resilience.
[00068] Creativity is a cornerstone of innovation and problem-solving. Portable neurofeedback devices hold exciting potential in enhancing creative thinking by facilitating the brain's transition to creative states. By guiding users to access neural patterns conducive to divergent thinking, these devices can inspire novel ideas and solutions. For example, an artist looking to overcome creative blocks uses the portable neurofeedback device. During creative sessions, the device's harmonization audio-visual module (HAVM) delivers stimuli that encourage brainwave patterns associated with enhanced creativity. As the artist engages in their creative process, the device provides real-time feedback whenever their brainwave patterns align with a heightened creative state. Over time, this practice not only aids in overcoming creative blocks but also cultivates a more consistent flow of creative ideas.
[00069] One of the strengths of portable neurofeedback devices lies in their adaptability to individual needs and goals. These devices can be customized to target specific cognitive domains based on user preferences. This personalization ensures that users can tailor their neurofeedback experiences to match their unique cognitive enhancement aspirations. For example, a student preparing for exams utilizes the portable neurofeedback device to optimize their study sessions. By configuring the device to emphasize brainwave patterns associated with deep concentration and information retention, the student enhances their ability to absorb and recall information effectively. The device's adaptive neuro-algorithm (ANA) continually refines the feedback protocol based on the student's progress, leading to increasingly effective cognitive enhancement.
[00070] Portable neurofeedback devices have the potential to revolutionize cognitive enhancement strategies for healthy individuals. By harnessing neuroscientific insights and cutting-edge technology, these devices enable users to fine-tune their brainwave patterns for improved focus, relaxation, and creativity. Whether for professionals aiming to boost productivity, individuals seeking stress relief, or creatives looking to inspire innovation, these devices offer a novel and personalized approach to cognitive enhancement. As research in this field advances, we can anticipate even more sophisticated and tailored interventions to further unleash human cognitive potential.
[00071] This embodiment outlines a groundbreaking method 200 for providing neurofeedback using a portable device. Figuratively depicted in FIG. 2, representing a flow diagram of the method 200 that capitalizes on advanced neurofeedback technologies, including a cerebro-signal interface module (CSIM), neuron-data computation unit (NDCU), bio-memory matrix (BMM), user interaction portal (UIP), and neura-comm interface (NCI). This invention also introduces novel features like harmonization audio-visual module (HAVM), adaptive neuro-algorithm (ANA), and self-sustaining power management core (PMCore). The method embraces decoding neural signals, enabling user interaction, enhancing user engagement, and supporting energy sustainability.
[00072] The following embodiment illustrates a comprehensive method 200 for delivering neurofeedback using a portable device. The method 200 leverages cutting-edge neurofeedback technologies to provide users with personalized, effective, and adaptable neurofeedback experiences. The method 200 comprising steps of (at step 202) obtaining neural signals via the cerebro-signal interface module (CSIM), (at step 204) decoding and analyzing these signals within the neuron-data computation unit (NDCU), (at step 206) storing session information within the bio-memory matrix (BMM), (at step 208) enabling user interaction and customization via the user interaction portal (UIP) and (at step 210) transmitting summarized feedback or raw neural data via the neura-comm interface (NCI).
[00073] In an embodiment, the method 200 begins with obtaining neural signals through the cerebro-signal interface module (CSIM) of the portable device. The CSIM utilizes multi-node electrode connectivity to capture brainwave activity with enhanced granularity and accuracy. For instance, a user wears the portable device, and the CSIM captures neural signals from various brain regions as the user engages in a cognitive task. The CSIM's multi-node electrode connectivity ensures precise and comprehensive data collection, facilitating effective neurofeedback.
[00074] Once the neural signals are obtained, they are decoded and analyzed within the neuron-data computation unit (NDCU). Advanced signal processing algorithms within the NDCU transform raw neural data into meaningful insights about the user's cognitive state. The NDCU processes the captured neural signals, extracting information about the user's cognitive patterns. It identifies specific brainwave frequencies associated with attention or relaxation, enabling the device to offer targeted neurofeedback.
[00075] In an embodiment, the method 200 involves storing session information chronologically within the bio-memory matrix (BMM). This stored data supports the evolution of the adaptive neuro-algorithm (ANA) and allows users to track their progress over time. Each neurofeedback session's data is stored in the BMM, enabling users to monitor their cognitive improvements. As the user engages in more sessions, the BMM accumulates valuable longitudinal data for refining the ANA's accuracy.
[00076] In an embodiment, the user interaction portal (UIP) serves as a critical interface for user engagement and customization. The method includes enabling users to configure neurofeedback sessions, view feedback, and set preferences through the UIP. Users access the UIP to tailor their neurofeedback experience. They can adjust session duration, select visual or auditory feedback, and set notification thresholds. This customization enhances user satisfaction and outcomes.
[00077] Summarized feedback or raw neural data is transmitted via the neura-comm interface (NCI). This communication capability enables remote monitoring, collaborative research, and data-driven interventions. Neurofeedback professionals can remotely access users' feedback data through the NCI. Researchers can analyze aggregated data from multiple users, contributing to a deeper understanding of cognitive patterns.
[00078] An innovative aspect of this method involves delivering harmonized audio-visual stimuli through the harmonization audio-visual module (HAVM). These stimuli are designed to modulate specific brainwave patterns, enhancing the effectiveness of neurofeedback sessions. The HAVM delivers synchronized audio tones and visual cues that align with desired cognitive states. For instance, a user seeking relaxation experiences calming sounds and visuals, promoting a coherent neural response.
[00079] In an embodiment, the method integrates an adaptive neuro-algorithm (ANA) into the decoding process. This algorithm iteratively refines signal interpretation based on historical user data from the BMM, optimizing feedback precision. As the ANA processes data from multiple sessions stored in the BMM, it evolves to provide personalized and accurate feedback. Users observe increasingly effective neurofeedback outcomes over time.
[00080] In an embodiment, the method introduces a feature where users are alerted to deviations or anomalies in their neural patterns through customized alerts from the UIP. This proactive approach enhances user engagement and compliance. If a user's brainwave patterns deviate significantly from their target state, the UIP sends alerts, prompting the user to take action. This feature helps users maintain focus during neurofeedback sessions.
[00081] In an embodiment, the method incorporates a self-sustaining power management core (PMCore) that harvests energy from ambient sources or user interactions. This ensures extended device usability and minimizes the need for frequent recharging. The portable device harnesses solar energy during outdoor use or converts kinetic energy from the user's movements into power. This sustainable energy approach enhances the device's portability and user convenience.
[00082] Referring to one or more preceding embodiments, the method 200 described in this patent embodiment presents a groundbreaking approach to providing neurofeedback using a portable device. By seamlessly integrating advanced technologies such as CSIM, NDCU, BMM, UIP, and NCI, along with innovative features like HAVM, ANA, and PMCore, this method revolutionizes neurofeedback interventions. Its potential applications span medical treatment, cognitive enhancement, and beyond, ushering in a new era of personalized cognitive well-being.
[00083] The above description is intended to be illustrative, and not restrictive. Although the present disclosure has been described with references to specific illustrative examples and implementations, it will be recognized that the present disclosure is not limited to the examples and implementations described. The scope of the disclosure should be determined with reference to the following claims, along with the full scope of equivalents to which the claims are entitled.
[00084] Modifications, additions, or omissions may be made to the systems and apparatuses described herein without departing from the scope of the disclosure. The components of the systems and apparatuses may be integrated or separated. Moreover, the operations of the systems and apparatuses may be performed by more, fewer, or other components. Additionally, operations of the systems and apparatuses may be performed using any suitable logic comprising software, hardware, and/or other logic. As used in this document, “each” refers to each member of a set or each member of a subset of a set.
[00085] The term “memory,” as used herein relates to a volatile or persistent medium, such as a magnetic disk, or optical disk, in which a computer can store data or software for any duration. Optionally, the memory is non-volatile mass storage such as physical storage media. Furthermore, a single memory may encompass and in a scenario wherein computing system is distributed, the processing, memory and/or storage capability may be distributed as well.
[00086] Throughout the present disclosure, the term ‘server’ relates to a structure and/or module that include programmable and/or non-programmable components configured to store, process and/or share information. Optionally, the server includes any arrangement of physical or virtual computational entities capable of enhancing information to perform various computational tasks.
[00087]

Claims
I/We Claim:
1. A portable neurofeedback device, comprising:
a cerebro-signal interface module (CSIM) configured to capture and relay brainwave activity;
a neuron-data computation unit (NDCU) for processing and interpreting signals from the CSIM;
a bio-memory matrix (BMM) for chronologically storing neurofeedback sessions;
a neura-comm interface (NCI) enabling wireless communication with external devices or platforms; and
a user interaction portal (UIP) designed for configuring sessions, viewing feedback, and customizing alert preferences.
2. The device of claim 1, wherein the CSIM incorporates multi-node electrode connectivity to increase the granularity of brainwave capture.
3. The device of claim 1, further comprising: a harmonization audio-visual module (HAVM) that delivers synchronized stimuli designed to guide or influence the user's brainwave patterns.
4. The device of claim 1, wherein the NDCU employs an adaptive neuro-algorithm (ANA) that evolves based on longitudinal data from the BMM to enhance feedback precision.
5. The device of claim 1, further comprising: a self-sustaining power management core (PMCore) designed for extended operational durations and minimalistic energy consumption.
6. A method for providing neurofeedback using a portable device, comprising: obtaining neural signals via the cerebro-signal interface module (CSIM); decoding and analyzing these signals within the neuron-data computation unit (NDCU); storing session information within the bio-memory matrix (BMM); enabling user interaction and customization via the user interaction portal (UIP); and transmitting summarized feedback or raw neural data via the neura-comm interface (NCI).
7. The method of claim 6, further comprising: delivering harmonized audio-visual stimuli to the user through the harmonization audio-visual module (HAVM) to modulate specific brainwave patterns.
8. The method of claim 6, wherein the decoding step incorporates the adaptive neuro-algorithm (ANA) to iteratively refine signal interpretation based on historical user data from the BMM.
9. The method of claim 6, further comprising: alerting the user to deviations or anomalies in their neural patterns through a series of custom alerts from the user interaction portal (UIP).
10. The method of claim 6, further comprising: harvesting energy from ambient sources or through user interaction to recharge the self-sustaining power management core (PMCore), thus extending device usability.

PORTABLE NEUROFEEDBACK DEVICE
Abstract
A groundbreaking portable neurofeedback device designed to capture, interpret, and provide real-time feedback on neural activity. This compact device seamlessly integrates advanced sensors to monitor brainwave patterns, with sophisticated algorithms processing these patterns to identify specific neural states or anomalies. Its portability ensures user flexibility, facilitating on-the-go neurofeedback sessions whether at home, work, or in therapeutic environments. Through immediate feedback, users can engage in self-regulation exercises or therapeutic interventions, offering a dynamic approach to brain health and cognitive enhancement. , Claims:Claims
I/We Claim:
1. A portable neurofeedback device, comprising:
a cerebro-signal interface module (CSIM) configured to capture and relay brainwave activity;
a neuron-data computation unit (NDCU) for processing and interpreting signals from the CSIM;
a bio-memory matrix (BMM) for chronologically storing neurofeedback sessions;
a neura-comm interface (NCI) enabling wireless communication with external devices or platforms; and
a user interaction portal (UIP) designed for configuring sessions, viewing feedback, and customizing alert preferences.
2. The device of claim 1, wherein the CSIM incorporates multi-node electrode connectivity to increase the granularity of brainwave capture.
3. The device of claim 1, further comprising: a harmonization audio-visual module (HAVM) that delivers synchronized stimuli designed to guide or influence the user's brainwave patterns.
4. The device of claim 1, wherein the NDCU employs an adaptive neuro-algorithm (ANA) that evolves based on longitudinal data from the BMM to enhance feedback precision.
5. The device of claim 1, further comprising: a self-sustaining power management core (PMCore) designed for extended operational durations and minimalistic energy consumption.
6. A method for providing neurofeedback using a portable device, comprising: obtaining neural signals via the cerebro-signal interface module (CSIM); decoding and analyzing these signals within the neuron-data computation unit (NDCU); storing session information within the bio-memory matrix (BMM); enabling user interaction and customization via the user interaction portal (UIP); and transmitting summarized feedback or raw neural data via the neura-comm interface (NCI).
7. The method of claim 6, further comprising: delivering harmonized audio-visual stimuli to the user through the harmonization audio-visual module (HAVM) to modulate specific brainwave patterns.
8. The method of claim 6, wherein the decoding step incorporates the adaptive neuro-algorithm (ANA) to iteratively refine signal interpretation based on historical user data from the BMM.
9. The method of claim 6, further comprising: alerting the user to deviations or anomalies in their neural patterns through a series of custom alerts from the user interaction portal (UIP).
10. The method of claim 6, further comprising: harvesting energy from ambient sources or through user interaction to recharge the self-sustaining power management core (PMCore), thus extending device usability.