1. A non-invasive glucose monitoring system, comprising: a sensor unit designed to detect glucose level changes through the skin without piercing it; a signal processing module configured to receive and process data from said sensor unit; a display module to showcase real-time glucose levels to the user; a calibration module allowing users to input known glucose levels for system accuracy adjustment; and a communication interface for transferring glucose data to external devices.

2. The system of claim 1, wherein the sensor unit utilizes near-infrared spectroscopy to detect glucose concentrations.

3. The system of claim 1, wherein the signal processing module further comprises machine learning algorithms trained to correlate detected signals with actual blood glucose levels.

4. The system of claim 1, further comprising an alert mechanism configured to warn the user when detected glucose levels are outside a predetermined range.

5. The system of claim 1, wherein the communication interface is wireless and compatible with multiple device platforms for data access and sharing.

6. A method for non-invasive glucose monitoring, comprising the steps of: placing a sensor unit against a user's skin; detecting glucose level changes through the skin using said sensor; processing the detected signals to determine glucose concentration; displaying the real-time glucose concentration to the user; and calibrating the system based on inputted known glucose levels.

7. The method of claim 6, further comprising the step of transmitting glucose data to an external device through a wireless communication interface.

8. The method of claim 6, wherein the step of detecting involves employing near-infrared spectroscopy.

9. The method of claim 6, further comprising the step of: setting a predetermined glucose range; and activating an alert mechanism when detected glucose levels fall outside the said range.

10. The method of claim 6, wherein the step of processing involves utilizing machine learning algorithms to correlate detected signals with actual blood glucose levels. Non-invasive glucose monitoring system Abstract The present invention introduces a non-invasive glucose monitoring system designed to enhance user comfort and accuracy in diabetes management. This system comprises a sensor unit that detects glucose level variations through the skin without necessitating penetration. An integrated signal processing module receives and processes the acquired data from the sensor, ensuring precision in readings. Users benefit from a display module that provides real-time visualization of their glucose concentrations. A unique calibration module is incorporated, allowing users to input known glucose levels, thus fine-tuning the system's accuracy. Furthermore, the system boasts a communication interface, facilitating seamless transfer of glucose data to external devices, enhancing interoperability and data sharing capabilities. , Claims:Claims :

1. A non-invasive glucose monitoring system, comprising: a sensor unit designed to detect glucose level changes through the skin without piercing it; a signal processing module configured to receive and process data from said sensor unit; a display module to showcase real-time glucose levels to the user; a calibration module allowing users to input known glucose levels for system accuracy adjustment; and a communication interface for transferring glucose data to external devices.

2. The system of claim 1, wherein the sensor unit utilizes near-infrared spectroscopy to detect glucose concentrations.

3. The system of claim 1, wherein the signal processing module further comprises machine learning algorithms trained to correlate detected signals with actual blood glucose levels.

4. The system of claim 1, further comprising an alert mechanism configured to warn the user when detected glucose levels are outside a predetermined range.

5. The system of claim 1, wherein the communication interface is wireless and compatible with multiple device platforms for data access and sharing.

6. A method for non-invasive glucose monitoring, comprising the steps of: placing a sensor unit against a user's skin; detecting glucose level changes through the skin using said sensor; processing the detected signals to determine glucose concentration; displaying the real-time glucose concentration to the user; and calibrating the system based on inputted known glucose levels.

7. The method of claim 6, further comprising the step of transmitting glucose data to an external device through a wireless communication interface.

8. The method of claim 6, wherein the step of detecting involves employing near-infrared spectroscopy.

9. The method of claim 6, further comprising the step of: setting a predetermined glucose range; and activating an alert mechanism when detected glucose levels fall outside the said range.

10. The method of claim 6, wherein the step of processing involves utilizing machine learning algorithms to correlate detected signals with actual blood glucose levels.

Description:Non-invasive glucose monitoring system
Field of the Invention
[0001] The present invention relates generally to medical monitoring devices, and more specifically, to a system and method for non-invasive glucose monitoring. The invention provides an innovative approach to measure glucose levels in individuals without the need for skin penetration, offering enhanced comfort, reduced risk of infection, and continuous or frequent monitoring capabilities. Utilizing advanced sensing techniques and data interpretation algorithms, the system allows for accurate and reliable glucose readings, thereby supporting effective diabetes management and monitoring.
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] The continuous and accurate monitoring of glucose levels is paramount for individuals with diabetes, a condition that impacts millions worldwide. Traditionally, glucose monitoring involved pricking the finger to draw a small blood sample, which was then tested for glucose concentration. While effective, these invasive methods are painful, can lead to skin complications over time, and often deter consistent monitoring due to the discomfort associated.
[0004] The importance of regular glucose monitoring has driven significant research and development in the realm of non-invasive glucose monitoring systems. The overarching goal of these systems is to offer reliable glucose readings without penetrating the skin, thus eliminating the pain and potential complications of conventional methods.
[0005] One pioneering example in the prior art is the use of infrared (IR) spectroscopy. In these systems, IR light is directed at the skin, typically at the forearm or wrist. The light penetrates the skin and is reflected back to a sensor. Since glucose molecules absorb specific wavelengths of IR light, the amount of light absorbed versus the amount reflected provides an estimate of the glucose concentration in the blood. However, while promising, IR methods have sometimes been criticized for their sensitivity to external factors like skin moisture, temperature, and tissue composition.
[0006] Another notable approach in the prior art involves the use of dielectric spectroscopy. This method measures the dielectric properties of human tissues, which change with varying glucose levels. By applying a non-invasive probe to the skin that emits a radiofrequency signal, these systems measure the reflected signal's amplitude and phase. Changes in these parameters can then be correlated with glucose levels. Yet, as with IR-based methods, the accuracy of dielectric spectroscopy can be impacted by tissue hydration and other interferences.
[0007] Optical coherence tomography (OCT) has also been explored as a potential non-invasive glucose monitoring technique. OCT systems emit light into the skin and measure the echo time delay and magnitude of the backscattered light. Glucose concentrations influence the refractive index of the interstitial fluid, leading to detectable changes in the OCT signal. Still, this method's reliability can be influenced by skin heterogeneity and requires further validation for mainstream application.
[0008] A significant advancement in the field came with the introduction of biosensors that can be worn on the skin's surface. These sensors, often in the form of patches or wearables, interact with the skin's top layers and extract interstitial fluid through microscopic channels. While technically minimally invasive, these sensors are virtually painless and provide continuous glucose monitoring.
[0009] More recently, the integration of advanced computational methods, like machine learning, has provided avenues to enhance the accuracy of non-invasive techniques. By analyzing vast datasets of glucose readings correlated with sensor outputs, algorithms can be trained to compensate for some of the confounding factors that have historically impacted non-invasive readings.
[00010] In summary, the evolution of non-invasive glucose monitoring systems in the prior art underscores a consistent drive towards improving the comfort, accuracy, and reliability of glucose readings. While significant advancements have been made, there remains a considerable demand for further innovation in this domain, especially systems that can adapt to the individual variances seen in the global population.
[00011] 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.
[00012] 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
[00013] The following presents a simplified summary of various aspects of this disclosure in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements nor delineate the scope of such aspects. Its purpose is to present some concepts of this disclosure in a simplified form as a prelude to the more detailed description that is presented later.
[00014] The following paragraphs provide additional support for the claims of the subject application.
[00015] The present invention relates generally to medical monitoring devices, and more specifically, to a system and method for non-invasive glucose monitoring. The invention provides an innovative approach to measure glucose levels in individuals without the need for skin penetration, offering enhanced comfort, reduced risk of infection, and continuous or frequent monitoring capabilities. Utilizing advanced sensing techniques and data interpretation algorithms, the system allows for accurate and reliable glucose readings, thereby supporting effective diabetes management and monitoring.
[00016] Diabetes management has historically been a challenge due to the invasive nature of monitoring blood glucose levels. The presented system seeks to transform this paradigm by introducing a non-invasive approach to glucose monitoring, emphasizing user comfort and precision.
[00017] At the core of this system is a state-of-the-art sensor unit. This unit is meticulously designed to detect shifts in glucose levels directly through the skin, eliminating the need for painful and repetitive skin pricks. Specifically, this sensor unit employs near-infrared spectroscopy, a sophisticated technique known for its potential in discerning glucose concentrations without skin penetration. This method uses light absorption properties to infer glucose concentrations, promising both accuracy and minimal discomfort.
[00018] Once the sensor unit captures the necessary data, it interfaces with a dedicated signal processing module. This module is not just a simple data interpreter, it integrates machine learning algorithms. These algorithms have undergone training to expertly correlate detected signals with actual blood glucose concentrations. By employing machine learning, the system ensures that its readings remain precise, accounting for individual variances and external interferences.
[00019] Users are provided with immediate feedback through the display module, which showcases real-time glucose readings. This instantaneous insight is invaluable, allowing for prompt responses to fluctuating glucose levels. Enhancing the system's precision, a calibration module is incorporated. This module permits users to input known glucose concentrations, facilitating system adjustments for enhanced accuracy in future readings.
[00020] In the context of user safety, the system is not just a passive monitor. As highlighted, an integrated alert mechanism actively monitors the detected glucose levels. If these readings venture outside a pre-defined range, indicative of potential health concerns, the system immediately warns the user, enabling swift remedial action.
[00021] Connectivity and data sharing are critical in modern healthcare, and this system is no exception. A communication interface is integrated. This interface is not only wireless, reducing user encumbrance, but it's also designed for multi-platform compatibility. Whether it's transferring data to a personal device, sharing with healthcare providers, or integrating with other health applications, the system ensures seamless and flexible data access.
[00022] In conclusion, the proposed glucose monitoring system epitomizes the future of diabetes management. By combining non-invasive techniques with machine learning, real-time feedback, and extensive connectivity, it promises a new era of user-friendly and precise glucose monitoring.
[00023] The management of diabetes and the accurate monitoring of blood glucose levels have always posed a significant challenge due to the traditionally invasive nature of such monitoring processes. The method described herein revolutionizes this process by introducing a non-invasive approach, which is designed for optimum accuracy while maximizing user comfort.
[00024] Central to this method is the use of a sensor unit that is gently placed against the skin. This placement is the first step in a sequence of operations that eliminate the discomfort of skin pricks. The sensor, doesn’t merely detect glucose levels superficially. It employs a technique known as near-infrared spectroscopy; a method that gauges glucose concentrations based on how specific light wavelengths are absorbed. This method ensures accurate readings without breaking the skin.
[00025] Once the glucose-related signals are detected by the sensor, they are then funneled to a processing step. Intriguingly, and as highlighted, this isn't just a linear progression of data interpretation. The process harnesses the power of machine learning algorithms, sophisticated computational tools trained to correlate the detected signals with real-world blood glucose concentrations. The inclusion of machine learning ensures that the system can learn, adapt, and refine its accuracy over time, making it increasingly reliable.
[00026] After processing, users aren't left in the dark. The method immediately provides feedback through a real-time display of the glucose concentration. Such instant readings empower users to make immediate decisions about their health, be it adjusting their insulin intake, modifying their diet, or taking other necessary actions.
[00027] Understanding that all systems require periodic calibration for optimum functionality, this method incorporates a calibration step. Here, users can input known glucose levels, allowing the system to adjust its readings and ensuring its results remain accurate over time.
[00028] However, this method doesn't restrict its utility to mere monitoring. Introduction of a proactive component, a predetermined glucose range can be set, functioning as a safety threshold. Should detected glucose levels deviate from this range, an alert mechanism is activated. This step ensures that users are promptly notified of potential health risks, encouraging swift corrective actions.
[00029] The modern world values connectivity, and this method acknowledges that. After the monitoring and processing of glucose data, there's an option to transmit this crucial information wirelessly to external devices. Whether it's for personal record-keeping, sharing with healthcare professionals, or integrating with other digital health tools, this transmission ensures users and medical professionals remain informed.
[00030] In essence, this method amalgamates advanced techniques, proactive health management, and user-friendly procedures to redefine the paradigm of glucose monitoring. Offering a seamless blend of accuracy, safety, and connectivity, it represents a leap forward in diabetes management.
Brief Description of the Drawings
[00031] 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:
[00032] FIG. 1 represents an architectural overview of a non-invasive glucose monitoring system, according to some embodiments of the present disclosure.
[00033] FIG. 2 shows an exemplary detailed schematic flow diagram of a method for non-invasive glucose monitoring, according to some embodiments of the present disclosure.
Detailed Description
[00034] In the following detailed description of the invention, reference is made to the accompanying drawings that form a part hereof, and in which is shown, by way of illustration, specific embodiments in which the invention may be practiced. In the drawings, like numerals describe substantially similar components throughout the several views. These embodiments are described in sufficient detail to claim those skilled in the art to practice the invention. Other embodiments may be utilized and structural, logical, and electrical changes may be made without departing from the scope of the present invention. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is defined only by the appended claims and equivalents thereof.
[00035] The use of the terms “a” and “an” and “the” and “at least one” and similar referents in the context of describing the invention (especially in the context of the following claims) are to be construed to cover both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context. The use of the term “at least one” followed by a list of one or more items (for example, “at least one of A and B”) is to be construed to mean one item selected from the listed items (A or B) or any combination of two or more of the listed items (A and B), unless otherwise indicated herein or clearly contradicted by context. The terms “comprising,” “having,” “including,” and “containing” are to be construed as open-ended terms (i.e., meaning “including, but not limited to,”) unless otherwise noted. Recitation of ranges of values herein are merely intended to serve as a shorthand method of referring individually to each separate value falling within the range, unless otherwise indicated herein, and each separate value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g., “such as”) provided herein, is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention unless otherwise claimed. No language

in the specification should be construed as indicating any non-claimed element as essential to the practice of the invention.
[00036] 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.
[00037] The present invention relates generally to medical monitoring devices, and more specifically, to a system and method for non-invasive glucose monitoring. The invention provides an innovative approach to measure glucose levels in individuals without the need for skin penetration, offering enhanced comfort, reduced risk of infection, and continuous or frequent monitoring capabilities. Utilizing advanced sensing techniques and data interpretation algorithms, the system allows for accurate and reliable glucose readings, thereby supporting effective diabetes management and monitoring.
[00038] 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.
[00039] Diabetes, a condition that impacts millions globally, demands constant monitoring of blood glucose levels to ensure that they are maintained within a healthy range. Traditional methods of glucose monitoring involve piercing the skin to draw blood, a procedure that can be both painful and inconvenient. Enter the new-age non-invasive glucose monitoring system 100, designed to alleviate these pains and provide an efficient, painless, and accurate means of keeping tabs on blood glucose levels.
[00040] According to a pictorial portrayal in FIG. 1, illustrating an architectural setup of the system 100, comprising a sensor unit 102 designed to detect glucose level changes through the skin without piercing it, a signal processing module 104 configured to receive and process data from said sensor unit, a display module 106 to showcase real-time glucose levels to the user, a calibration module 108 allowing users to input known glucose levels for system accuracy adjustment, and a communication interface 110 for transferring glucose data to external devices.
[00041] In an embodiment, the cornerstone of this innovative system 100 is its sensor unit. Unlike traditional lancets that prick the skin to draw blood, this sensor unit is specifically crafted to detect glucose level changes through the skin, sans any piercing. Imagine the convenience of just placing a device against the skin and receiving real-time glucose readings without the associated pain of a needle prick. For instance, consider the sensor as a sophisticated scanner, akin to how a barcode scanner decodes information without making physical contact with the product label. This sensor deciphers the glucose information just below the skin's surface.
[00042] Delving deeper into the workings of the sensor, its foundation lies in near-infrared (NIR) spectroscopy. NIR spectroscopy is a technique that uses light waves in the near-infrared range to ascertain the concentration of certain molecules, in this case, glucose. For instance, a good analogy is how different substances have distinct "signatures" when exposed to specific light wavelengths. For glucose, near-infrared light provides the means to identify its unique signature, allowing the sensor to detect its concentration.
[00043] Once the sensor detects glucose concentrations, the data is forwarded to the signal processing module. This module isn't just a passive receiver; it's an active data processor. The system 100 introduces an even more intriguing aspect: the incorporation of machine learning algorithms. These algorithms have been trained to correlate the detected signals with actual blood glucose levels, ensuring the results are not only real-time but also accurate. For instance, consider the signal processing module as the brain behind the system. If the sensor provides the eyes that "see" the glucose levels, the signal processor interprets what's seen, akin to how our brains interpret visual stimuli.
[00044] Accuracy is meaningless if the results are not presented in a comprehensible manner. The display module is precisely for that. It showcases real-time glucose levels, rendered in an intuitive, user-friendly manner, ensuring that users, even without medical expertise, can understand their current glucose status. The display can be equated to a car dashboard that shows speed, fuel levels, and the like, in a manner that drivers can quickly understand and act upon.
[00045] Every machine requires occasional calibration to maintain its accuracy, and this system is no exception. It comprises a calibration module, allowing users to input known glucose levels. This ensures the system's readings remain in sync with actual blood glucose levels, bolstering the trust users place in the device. For instance, similar to how a weighing scale might need recalibration using known weights, the glucose monitor can be recalibrated using known glucose concentrations to ensure accuracy.
[00046] Beyond just displaying results, the system goes a step further. It incorporates an alert mechanism. Should the detected glucose levels stray outside a predetermined healthy range, the system immediately warns the user, ensuring timely interventions and corrective actions. For instance, it's akin to a car's warning system, which alerts the driver if, say, the engine temperature rises beyond a safe level or if the fuel level drops critically low.
[00047] In an age dominated by digital devices and interconnectedness, the system doesn't lag. The communication interface, one that's wireless and compatible across multiple device platforms. This ensures glucose data can be seamlessly transferred to external devices, be it smartphones, tablets, or even dedicated medical equipment. For instance, as modern smartphones connect to various other devices via Bluetooth, sharing data, music, or pictures.
[00048] Referring to one or more preceding embodiments, the non-invasive glucose monitoring system 100 embodies the next frontier in diabetic care. By amalgamating advanced sensing techniques, machine learning, and user-centric features, it promises to redefine the diabetes management landscape, making it more convenient, efficient, and user-friendly. As the world grapples with rising diabetic cases, such innovations are not just conveniences; they are necessities.
[00049] In the modern age, where convenience and technology go hand in hand, non-invasive methods of medical testing have become a focal point for research and development. The ability to monitor blood glucose levels without the need for invasive procedures is a revolutionary advancement. This narrative dives deep into the steps of a method 200 that has transformed the way we monitor glucose, elucidating each step with detailed explanations and illustrative examples.
[00050] Figuratively depicted in FIG. 2, representing a flow diagram of the method 200 comprising the steps of (at step 202) placing a sensor unit against a user's skin, (at step 204) detecting glucose level changes through the skin using said sensor, (at step 206) processing the detected signals to determine glucose concentration, (at step 208) displaying the real-time glucose concentration to the user, and (at step 210) calibrating the system based on inputted known glucose levels.
[00051] The initial step in this procedure is seemingly simple, placing a sensor unit against the skin. For example, the skin acts as a barrier, shielding our inner body from external harm. However, it also contains a wealth of information that can be harnessed with the right tools. The sensor unit, designed specifically for this purpose, makes contact with the skin to begin its monitoring. Further, using a thermometer to check for fever. You place it under the tongue or the armpit, and it does its job. Similarly, the sensor, when placed against the skin, begins its work.
[00052] Through the sensor, once placed, detects glucose level changes occurring just below the skin. Beneath the surface, the body undergoes countless chemical reactions. The sensor taps into these reactions to detect the presence and concentration of glucose molecules, all without piercing the skin. For instance, similarly how metal detectors at airports detect metal objects without touching you. They sense what's beneath without direct contact.
[00053] In yet another embodiment, the method 200 doesn't just rely on any technology; it employs near-infrared spectroscopy. This technique harnesses light in the near-infrared range to detect glucose concentrations. For instance, visualize shining a specialized flashlight onto an object and determining its composition based on how the light is absorbed or reflected. That's essentially what the sensor does with near-infrared light and glucose.
[00054] In yet another embodiment, the detected signals are then processed to ascertain glucose concentrations. Raw data, without proper interpretation, can be like an undeciphered code. The system takes these signals and processes them to derive meaningful results. For instance, it's analogous to how radios catch raw signals and convert them into clear music or speech.
[00055] In yet another embodiment, the innovation doesn't stop at mere processing. Machine learning algorithms are incorporated, which have been trained to associate detected signals with genuine blood glucose levels. For example, consider these algorithms as a seasoned detective who, over time, has learned to pick out subtle clues from a scene to solve a mystery. Similarly, the machine learning algorithms, with their training data, can interpret subtle changes in the signals to deduce glucose levels.
[00056] Once processed, the glucose concentration is displayed in real-time for the user. The system is designed with user-friendliness in mind. By providing immediate readings, users are kept informed about their glucose status without delays. For instance, like the modern cars display real-time fuel efficiency, the system gives users an immediate understanding of their glucose levels.
[00057] Periodically, or when needed, the system can be calibrated using known glucose levels. To maintain the system's precision, calibration acts as a tuning tool, ensuring that the readings align with actual glucose levels. For instance, musicians tune their instruments before performances to ensure they produce the correct notes. Similarly, calibration ensures the system's "notes" (readings) are accurate.
[00058] In an embodiment, the system can transmit glucose data wirelessly to external devices. In our interconnected age, data sharing is crucial. By sending data to other devices, users or healthcare professionals can track, analyze, or even store these readings for future reference. It's akin to syncing your fitness tracker with your smartphone to get a detailed view of your physical activities.
[00059] In an embodiment, the system is not just passive. If glucose levels stray outside a set range, an alert mechanism springs into action. This feature ensures users are not just informed, but also warned. Should glucose levels become critically high or low, the system sends out an alert, allowing users to take timely action. Modern home security systems send alerts when a breach is detected. Similarly, the alert mechanism acts as a guardian, monitoring glucose levels and signaling any anomalies.
[00060] Referring to one or more preceding embodiments, the non-invasive glucose monitoring method 200, with its intricate steps and state-of-the-art technologies, exemplifies how modern healthcare is gravitating towards comfort without compromising on accuracy. With the integration of advanced sensing, machine learning, and user-centric features, the future of glucose monitoring seems not just promising, but revolutionary. As diabetes continues to be a global concern, such groundbreaking methodologies will undoubtedly play a pivotal role in enhancing patient care and wellbeing.
[00061] For individuals with diabetes, regularly tracking blood glucose levels is critical for extending their lifespan. There are two primary monitoring approaches: invasive and non-invasive. The invasive technique requires finger pricking to collect a blood sample, whereas the non-invasive technique avoids breaking the skin or any bodily intrusion, making it a safer alternative. The absence of pricking in non-invasive measurements allows for more frequent monitoring without causing discomfort to the patient.
[00062] Non-invasive glucose monitoring could serve as a proactive measure against diabetes, although it's not yet commercially available. Currently, the most effective method to manage the severe challenges posed by diabetes involves monitoring its indicators. Keeping track of blood glucose levels has shown to increase life expectancy for diabetics. It aids in regulating episodes of low or high blood sugar, granting individuals better control over their health and minimizing severe complications. Moreover, glucose monitoring assists in refining treatment plans and offers insights into the impacts of medication, physical activity, and diet on patients. Despite its importance, the current gold standard for glucose measurement is based on the invasive approach. For non-diabetic individuals, blood glucose concentrations hover between 4.9–6.9 mm/ml, but can soar up to 40 mm/ml in diabetics post meals.
[00063] To address this, various commercial self-monitoring glucose devices and test strips are now available. These include enzymatic strips, electrochemical sensors, and other invasive tools. Efforts have been made to develop non-invasive methods using optical techniques, such as photodetectors, Raman spectroscopy, polarimetry, near-infrared absorption, and scattering. However, these attempts have found only limited physiological success. Presently, there are no commercial products based on non-invasive techniques, even though they are being actively researched. Previous studies indicate that many self-monitoring systems only deliver about 63% of dependable results and often struggle to accurately measure high glucose concentrations.
[00064] Example embodiments herein have been described above with reference to block diagrams and flowchart illustrations of methods and apparatuses. It will be understood that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, respectively, can be implemented by various means including hardware, software, firmware, and a combination thereof. For example, in one embodiment, each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations can be implemented by computer program instructions. These computer program instructions may be loaded onto a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions which execute on the computer or other programmable data processing apparatus create means for implementing the functions specified in the flowchart block or blocks.
[00065] 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.
[00066] Throughout the present disclosure, the term ‘processing means’ or ‘microprocessor’ or ‘processor’ or ‘processors’ includes, but is not limited to, a general purpose processor (such as, for example, a complex instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a microprocessor implementing other types of instruction sets, or a microprocessor implementing a combination of types of instruction sets) or a specialized processor (such as, for example, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), or a network processor).
[00067] The term “non-transitory storage device” or “storage” or “memory,” as used herein relates to a random access memory, read only memory and variants thereof, in which a computer can store data or software for any duration.
[00068] Operations in accordance with a variety of aspects of the disclosure is described above would not have to be performed in the precise order described. Rather, various steps can be handled in reverse order or simultaneously or not at all.
[00069] While several implementations have been described and illustrated herein, a variety of other means and/or structures for performing the function and/or obtaining the results and/or one or more of the advantages described herein may be utilized, and each of such variations and/or modifications is deemed to be within the scope of the implementations described herein. More generally, all parameters, dimensions, materials, and configurations described herein are meant to be exemplary and that the actual parameters, dimensions, materials, and/or configurations will depend upon the specific application or applications for which the teachings is/are used. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific implementations described herein. It is, therefore, to be understood that the foregoing implementations are presented by way of example only and that, within the scope of the appended claims and equivalents thereto, implementations may be practiced otherwise than as specifically described and claimed. Implementations of the present disclosure are directed to each individual feature, system, article, material, kit, and/or method described herein. In addition, any combination of two or more such features, systems, articles, materials, kits, and/or methods, if such features, systems, articles, materials, kits, and/or methods are not mutually inconsistent, is included within the scope of the present disclosure.

Non-invasive glucose monitoring system
Field of the Invention
[0001] The present invention relates generally to medical monitoring devices, and more specifically, to a system and method for non-invasive glucose monitoring. The invention provides an innovative approach to measure glucose levels in individuals without the need for skin penetration, offering enhanced comfort, reduced risk of infection, and continuous or frequent monitoring capabilities. Utilizing advanced sensing techniques and data interpretation algorithms, the system allows for accurate and reliable glucose readings, thereby supporting effective diabetes management and monitoring.
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] The continuous and accurate monitoring of glucose levels is paramount for individuals with diabetes, a condition that impacts millions worldwide. Traditionally, glucose monitoring involved pricking the finger to draw a small blood sample, which was then tested for glucose concentration. While effective, these invasive methods are painful, can lead to skin complications over time, and often deter consistent monitoring due to the discomfort associated.
[0004] The importance of regular glucose monitoring has driven significant research and development in the realm of non-invasive glucose monitoring systems. The overarching goal of these systems is to offer reliable glucose readings without penetrating the skin, thus eliminating the pain and potential complications of conventional methods.
[0005] One pioneering example in the prior art is the use of infrared (IR) spectroscopy. In these systems, IR light is directed at the skin, typically at the forearm or wrist. The light penetrates the skin and is reflected back to a sensor. Since glucose molecules absorb specific wavelengths of IR light, the amount of light absorbed versus the amount reflected provides an estimate of the glucose concentration in the blood. However, while promising, IR methods have sometimes been criticized for their sensitivity to external factors like skin moisture, temperature, and tissue composition.
[0006] Another notable approach in the prior art involves the use of dielectric spectroscopy. This method measures the dielectric properties of human tissues, which change with varying glucose levels. By applying a non-invasive probe to the skin that emits a radiofrequency signal, these systems measure the reflected signal's amplitude and phase. Changes in these parameters can then be correlated with glucose levels. Yet, as with IR-based methods, the accuracy of dielectric spectroscopy can be impacted by tissue hydration and other interferences.
[0007] Optical coherence tomography (OCT) has also been explored as a potential non-invasive glucose monitoring technique. OCT systems emit light into the skin and measure the echo time delay and magnitude of the backscattered light. Glucose concentrations influence the refractive index of the interstitial fluid, leading to detectable changes in the OCT signal. Still, this method's reliability can be influenced by skin heterogeneity and requires further validation for mainstream application.
[0008] A significant advancement in the field came with the introduction of biosensors that can be worn on the skin's surface. These sensors, often in the form of patches or wearables, interact with the skin's top layers and extract interstitial fluid through microscopic channels. While technically minimally invasive, these sensors are virtually painless and provide continuous glucose monitoring.
[0009] More recently, the integration of advanced computational methods, like machine learning, has provided avenues to enhance the accuracy of non-invasive techniques. By analyzing vast datasets of glucose readings correlated with sensor outputs, algorithms can be trained to compensate for some of the confounding factors that have historically impacted non-invasive readings.
[00010] In summary, the evolution of non-invasive glucose monitoring systems in the prior art underscores a consistent drive towards improving the comfort, accuracy, and reliability of glucose readings. While significant advancements have been made, there remains a considerable demand for further innovation in this domain, especially systems that can adapt to the individual variances seen in the global population.
[00011] 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.
[00012] 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
[00013] The following presents a simplified summary of various aspects of this disclosure in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements nor delineate the scope of such aspects. Its purpose is to present some concepts of this disclosure in a simplified form as a prelude to the more detailed description that is presented later.
[00014] The following paragraphs provide additional support for the claims of the subject application.
[00015] The present invention relates generally to medical monitoring devices, and more specifically, to a system and method for non-invasive glucose monitoring. The invention provides an innovative approach to measure glucose levels in individuals without the need for skin penetration, offering enhanced comfort, reduced risk of infection, and continuous or frequent monitoring capabilities. Utilizing advanced sensing techniques and data interpretation algorithms, the system allows for accurate and reliable glucose readings, thereby supporting effective diabetes management and monitoring.
[00016] Diabetes management has historically been a challenge due to the invasive nature of monitoring blood glucose levels. The presented system seeks to transform this paradigm by introducing a non-invasive approach to glucose monitoring, emphasizing user comfort and precision.
[00017] At the core of this system is a state-of-the-art sensor unit. This unit is meticulously designed to detect shifts in glucose levels directly through the skin, eliminating the need for painful and repetitive skin pricks. Specifically, this sensor unit employs near-infrared spectroscopy, a sophisticated technique known for its potential in discerning glucose concentrations without skin penetration. This method uses light absorption properties to infer glucose concentrations, promising both accuracy and minimal discomfort.
[00018] Once the sensor unit captures the necessary data, it interfaces with a dedicated signal processing module. This module is not just a simple data interpreter, it integrates machine learning algorithms. These algorithms have undergone training to expertly correlate detected signals with actual blood glucose concentrations. By employing machine learning, the system ensures that its readings remain precise, accounting for individual variances and external interferences.
[00019] Users are provided with immediate feedback through the display module, which showcases real-time glucose readings. This instantaneous insight is invaluable, allowing for prompt responses to fluctuating glucose levels. Enhancing the system's precision, a calibration module is incorporated. This module permits users to input known glucose concentrations, facilitating system adjustments for enhanced accuracy in future readings.
[00020] In the context of user safety, the system is not just a passive monitor. As highlighted, an integrated alert mechanism actively monitors the detected glucose levels. If these readings venture outside a pre-defined range, indicative of potential health concerns, the system immediately warns the user, enabling swift remedial action.
[00021] Connectivity and data sharing are critical in modern healthcare, and this system is no exception. A communication interface is integrated. This interface is not only wireless, reducing user encumbrance, but it's also designed for multi-platform compatibility. Whether it's transferring data to a personal device, sharing with healthcare providers, or integrating with other health applications, the system ensures seamless and flexible data access.
[00022] In conclusion, the proposed glucose monitoring system epitomizes the future of diabetes management. By combining non-invasive techniques with machine learning, real-time feedback, and extensive connectivity, it promises a new era of user-friendly and precise glucose monitoring.
[00023] The management of diabetes and the accurate monitoring of blood glucose levels have always posed a significant challenge due to the traditionally invasive nature of such monitoring processes. The method described herein revolutionizes this process by introducing a non-invasive approach, which is designed for optimum accuracy while maximizing user comfort.
[00024] Central to this method is the use of a sensor unit that is gently placed against the skin. This placement is the first step in a sequence of operations that eliminate the discomfort of skin pricks. The sensor, doesn’t merely detect glucose levels superficially. It employs a technique known as near-infrared spectroscopy; a method that gauges glucose concentrations based on how specific light wavelengths are absorbed. This method ensures accurate readings without breaking the skin.
[00025] Once the glucose-related signals are detected by the sensor, they are then funneled to a processing step. Intriguingly, and as highlighted, this isn't just a linear progression of data interpretation. The process harnesses the power of machine learning algorithms, sophisticated computational tools trained to correlate the detected signals with real-world blood glucose concentrations. The inclusion of machine learning ensures that the system can learn, adapt, and refine its accuracy over time, making it increasingly reliable.
[00026] After processing, users aren't left in the dark. The method immediately provides feedback through a real-time display of the glucose concentration. Such instant readings empower users to make immediate decisions about their health, be it adjusting their insulin intake, modifying their diet, or taking other necessary actions.
[00027] Understanding that all systems require periodic calibration for optimum functionality, this method incorporates a calibration step. Here, users can input known glucose levels, allowing the system to adjust its readings and ensuring its results remain accurate over time.
[00028] However, this method doesn't restrict its utility to mere monitoring. Introduction of a proactive component, a predetermined glucose range can be set, functioning as a safety threshold. Should detected glucose levels deviate from this range, an alert mechanism is activated. This step ensures that users are promptly notified of potential health risks, encouraging swift corrective actions.
[00029] The modern world values connectivity, and this method acknowledges that. After the monitoring and processing of glucose data, there's an option to transmit this crucial information wirelessly to external devices. Whether it's for personal record-keeping, sharing with healthcare professionals, or integrating with other digital health tools, this transmission ensures users and medical professionals remain informed.
[00030] In essence, this method amalgamates advanced techniques, proactive health management, and user-friendly procedures to redefine the paradigm of glucose monitoring. Offering a seamless blend of accuracy, safety, and connectivity, it represents a leap forward in diabetes management.
Brief Description of the Drawings
[00031] 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:
[00032] FIG. 1 represents an architectural overview of a non-invasive glucose monitoring system, according to some embodiments of the present disclosure.
[00033] FIG. 2 shows an exemplary detailed schematic flow diagram of a method for non-invasive glucose monitoring, according to some embodiments of the present disclosure.
Detailed Description
[00034] In the following detailed description of the invention, reference is made to the accompanying drawings that form a part hereof, and in which is shown, by way of illustration, specific embodiments in which the invention may be practiced. In the drawings, like numerals describe substantially similar components throughout the several views. These embodiments are described in sufficient detail to claim those skilled in the art to practice the invention. Other embodiments may be utilized and structural, logical, and electrical changes may be made without departing from the scope of the present invention. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is defined only by the appended claims and equivalents thereof.
[00035] The use of the terms “a” and “an” and “the” and “at least one” and similar referents in the context of describing the invention (especially in the context of the following claims) are to be construed to cover both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context. The use of the term “at least one” followed by a list of one or more items (for example, “at least one of A and B”) is to be construed to mean one item selected from the listed items (A or B) or any combination of two or more of the listed items (A and B), unless otherwise indicated herein or clearly contradicted by context. The terms “comprising,” “having,” “including,” and “containing” are to be construed as open-ended terms (i.e., meaning “including, but not limited to,”) unless otherwise noted. Recitation of ranges of values herein are merely intended to serve as a shorthand method of referring individually to each separate value falling within the range, unless otherwise indicated herein, and each separate value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g., “such as”) provided herein, is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention unless otherwise claimed. No language

in the specification should be construed as indicating any non-claimed element as essential to the practice of the invention.
[00036] 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.
[00037] The present invention relates generally to medical monitoring devices, and more specifically, to a system and method for non-invasive glucose monitoring. The invention provides an innovative approach to measure glucose levels in individuals without the need for skin penetration, offering enhanced comfort, reduced risk of infection, and continuous or frequent monitoring capabilities. Utilizing advanced sensing techniques and data interpretation algorithms, the system allows for accurate and reliable glucose readings, thereby supporting effective diabetes management and monitoring.
[00038] 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.
[00039] Diabetes, a condition that impacts millions globally, demands constant monitoring of blood glucose levels to ensure that they are maintained within a healthy range. Traditional methods of glucose monitoring involve piercing the skin to draw blood, a procedure that can be both painful and inconvenient. Enter the new-age non-invasive glucose monitoring system 100, designed to alleviate these pains and provide an efficient, painless, and accurate means of keeping tabs on blood glucose levels.
[00040] According to a pictorial portrayal in FIG. 1, illustrating an architectural setup of the system 100, comprising a sensor unit 102 designed to detect glucose level changes through the skin without piercing it, a signal processing module 104 configured to receive and process data from said sensor unit, a display module 106 to showcase real-time glucose levels to the user, a calibration module 108 allowing users to input known glucose levels for system accuracy adjustment, and a communication interface 110 for transferring glucose data to external devices.
[00041] In an embodiment, the cornerstone of this innovative system 100 is its sensor unit. Unlike traditional lancets that prick the skin to draw blood, this sensor unit is specifically crafted to detect glucose level changes through the skin, sans any piercing. Imagine the convenience of just placing a device against the skin and receiving real-time glucose readings without the associated pain of a needle prick. For instance, consider the sensor as a sophisticated scanner, akin to how a barcode scanner decodes information without making physical contact with the product label. This sensor deciphers the glucose information just below the skin's surface.
[00042] Delving deeper into the workings of the sensor, its foundation lies in near-infrared (NIR) spectroscopy. NIR spectroscopy is a technique that uses light waves in the near-infrared range to ascertain the concentration of certain molecules, in this case, glucose. For instance, a good analogy is how different substances have distinct "signatures" when exposed to specific light wavelengths. For glucose, near-infrared light provides the means to identify its unique signature, allowing the sensor to detect its concentration.
[00043] Once the sensor detects glucose concentrations, the data is forwarded to the signal processing module. This module isn't just a passive receiver; it's an active data processor. The system 100 introduces an even more intriguing aspect: the incorporation of machine learning algorithms. These algorithms have been trained to correlate the detected signals with actual blood glucose levels, ensuring the results are not only real-time but also accurate. For instance, consider the signal processing module as the brain behind the system. If the sensor provides the eyes that "see" the glucose levels, the signal processor interprets what's seen, akin to how our brains interpret visual stimuli.
[00044] Accuracy is meaningless if the results are not presented in a comprehensible manner. The display module is precisely for that. It showcases real-time glucose levels, rendered in an intuitive, user-friendly manner, ensuring that users, even without medical expertise, can understand their current glucose status. The display can be equated to a car dashboard that shows speed, fuel levels, and the like, in a manner that drivers can quickly understand and act upon.
[00045] Every machine requires occasional calibration to maintain its accuracy, and this system is no exception. It comprises a calibration module, allowing users to input known glucose levels. This ensures the system's readings remain in sync with actual blood glucose levels, bolstering the trust users place in the device. For instance, similar to how a weighing scale might need recalibration using known weights, the glucose monitor can be recalibrated using known glucose concentrations to ensure accuracy.
[00046] Beyond just displaying results, the system goes a step further. It incorporates an alert mechanism. Should the detected glucose levels stray outside a predetermined healthy range, the system immediately warns the user, ensuring timely interventions and corrective actions. For instance, it's akin to a car's warning system, which alerts the driver if, say, the engine temperature rises beyond a safe level or if the fuel level drops critically low.
[00047] In an age dominated by digital devices and interconnectedness, the system doesn't lag. The communication interface, one that's wireless and compatible across multiple device platforms. This ensures glucose data can be seamlessly transferred to external devices, be it smartphones, tablets, or even dedicated medical equipment. For instance, as modern smartphones connect to various other devices via Bluetooth, sharing data, music, or pictures.
[00048] Referring to one or more preceding embodiments, the non-invasive glucose monitoring system 100 embodies the next frontier in diabetic care. By amalgamating advanced sensing techniques, machine learning, and user-centric features, it promises to redefine the diabetes management landscape, making it more convenient, efficient, and user-friendly. As the world grapples with rising diabetic cases, such innovations are not just conveniences; they are necessities.
[00049] In the modern age, where convenience and technology go hand in hand, non-invasive methods of medical testing have become a focal point for research and development. The ability to monitor blood glucose levels without the need for invasive procedures is a revolutionary advancement. This narrative dives deep into the steps of a method 200 that has transformed the way we monitor glucose, elucidating each step with detailed explanations and illustrative examples.
[00050] Figuratively depicted in FIG. 2, representing a flow diagram of the method 200 comprising the steps of (at step 202) placing a sensor unit against a user's skin, (at step 204) detecting glucose level changes through the skin using said sensor, (at step 206) processing the detected signals to determine glucose concentration, (at step 208) displaying the real-time glucose concentration to the user, and (at step 210) calibrating the system based on inputted known glucose levels.
[00051] The initial step in this procedure is seemingly simple, placing a sensor unit against the skin. For example, the skin acts as a barrier, shielding our inner body from external harm. However, it also contains a wealth of information that can be harnessed with the right tools. The sensor unit, designed specifically for this purpose, makes contact with the skin to begin its monitoring. Further, using a thermometer to check for fever. You place it under the tongue or the armpit, and it does its job. Similarly, the sensor, when placed against the skin, begins its work.
[00052] Through the sensor, once placed, detects glucose level changes occurring just below the skin. Beneath the surface, the body undergoes countless chemical reactions. The sensor taps into these reactions to detect the presence and concentration of glucose molecules, all without piercing the skin. For instance, similarly how metal detectors at airports detect metal objects without touching you. They sense what's beneath without direct contact.
[00053] In yet another embodiment, the method 200 doesn't just rely on any technology; it employs near-infrared spectroscopy. This technique harnesses light in the near-infrared range to detect glucose concentrations. For instance, visualize shining a specialized flashlight onto an object and determining its composition based on how the light is absorbed or reflected. That's essentially what the sensor does with near-infrared light and glucose.
[00054] In yet another embodiment, the detected signals are then processed to ascertain glucose concentrations. Raw data, without proper interpretation, can be like an undeciphered code. The system takes these signals and processes them to derive meaningful results. For instance, it's analogous to how radios catch raw signals and convert them into clear music or speech.
[00055] In yet another embodiment, the innovation doesn't stop at mere processing. Machine learning algorithms are incorporated, which have been trained to associate detected signals with genuine blood glucose levels. For example, consider these algorithms as a seasoned detective who, over time, has learned to pick out subtle clues from a scene to solve a mystery. Similarly, the machine learning algorithms, with their training data, can interpret subtle changes in the signals to deduce glucose levels.
[00056] Once processed, the glucose concentration is displayed in real-time for the user. The system is designed with user-friendliness in mind. By providing immediate readings, users are kept informed about their glucose status without delays. For instance, like the modern cars display real-time fuel efficiency, the system gives users an immediate understanding of their glucose levels.
[00057] Periodically, or when needed, the system can be calibrated using known glucose levels. To maintain the system's precision, calibration acts as a tuning tool, ensuring that the readings align with actual glucose levels. For instance, musicians tune their instruments before performances to ensure they produce the correct notes. Similarly, calibration ensures the system's "notes" (readings) are accurate.
[00058] In an embodiment, the system can transmit glucose data wirelessly to external devices. In our interconnected age, data sharing is crucial. By sending data to other devices, users or healthcare professionals can track, analyze, or even store these readings for future reference. It's akin to syncing your fitness tracker with your smartphone to get a detailed view of your physical activities.
[00059] In an embodiment, the system is not just passive. If glucose levels stray outside a set range, an alert mechanism springs into action. This feature ensures users are not just informed, but also warned. Should glucose levels become critically high or low, the system sends out an alert, allowing users to take timely action. Modern home security systems send alerts when a breach is detected. Similarly, the alert mechanism acts as a guardian, monitoring glucose levels and signaling any anomalies.
[00060] Referring to one or more preceding embodiments, the non-invasive glucose monitoring method 200, with its intricate steps and state-of-the-art technologies, exemplifies how modern healthcare is gravitating towards comfort without compromising on accuracy. With the integration of advanced sensing, machine learning, and user-centric features, the future of glucose monitoring seems not just promising, but revolutionary. As diabetes continues to be a global concern, such groundbreaking methodologies will undoubtedly play a pivotal role in enhancing patient care and wellbeing.
[00061] For individuals with diabetes, regularly tracking blood glucose levels is critical for extending their lifespan. There are two primary monitoring approaches: invasive and non-invasive. The invasive technique requires finger pricking to collect a blood sample, whereas the non-invasive technique avoids breaking the skin or any bodily intrusion, making it a safer alternative. The absence of pricking in non-invasive measurements allows for more frequent monitoring without causing discomfort to the patient.
[00062] Non-invasive glucose monitoring could serve as a proactive measure against diabetes, although it's not yet commercially available. Currently, the most effective method to manage the severe challenges posed by diabetes involves monitoring its indicators. Keeping track of blood glucose levels has shown to increase life expectancy for diabetics. It aids in regulating episodes of low or high blood sugar, granting individuals better control over their health and minimizing severe complications. Moreover, glucose monitoring assists in refining treatment plans and offers insights into the impacts of medication, physical activity, and diet on patients. Despite its importance, the current gold standard for glucose measurement is based on the invasive approach. For non-diabetic individuals, blood glucose concentrations hover between 4.9–6.9 mm/ml, but can soar up to 40 mm/ml in diabetics post meals.
[00063] To address this, various commercial self-monitoring glucose devices and test strips are now available. These include enzymatic strips, electrochemical sensors, and other invasive tools. Efforts have been made to develop non-invasive methods using optical techniques, such as photodetectors, Raman spectroscopy, polarimetry, near-infrared absorption, and scattering. However, these attempts have found only limited physiological success. Presently, there are no commercial products based on non-invasive techniques, even though they are being actively researched. Previous studies indicate that many self-monitoring systems only deliver about 63% of dependable results and often struggle to accurately measure high glucose concentrations.
[00064] Example embodiments herein have been described above with reference to block diagrams and flowchart illustrations of methods and apparatuses. It will be understood that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, respectively, can be implemented by various means including hardware, software, firmware, and a combination thereof. For example, in one embodiment, each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations can be implemented by computer program instructions. These computer program instructions may be loaded onto a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions which execute on the computer or other programmable data processing apparatus create means for implementing the functions specified in the flowchart block or blocks.
[00065] 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.
[00066] Throughout the present disclosure, the term ‘processing means’ or ‘microprocessor’ or ‘processor’ or ‘processors’ includes, but is not limited to, a general purpose processor (such as, for example, a complex instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a microprocessor implementing other types of instruction sets, or a microprocessor implementing a combination of types of instruction sets) or a specialized processor (such as, for example, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), or a network processor).
[00067] The term “non-transitory storage device” or “storage” or “memory,” as used herein relates to a random access memory, read only memory and variants thereof, in which a computer can store data or software for any duration.
[00068] Operations in accordance with a variety of aspects of the disclosure is described above would not have to be performed in the precise order described. Rather, various steps can be handled in reverse order or simultaneously or not at all.
[00069] While several implementations have been described and illustrated herein, a variety of other means and/or structures for performing the function and/or obtaining the results and/or one or more of the advantages described herein may be utilized, and each of such variations and/or modifications is deemed to be within the scope of the implementations described herein. More generally, all parameters, dimensions, materials, and configurations described herein are meant to be exemplary and that the actual parameters, dimensions, materials, and/or configurations will depend upon the specific application or applications for which the teachings is/are used. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific implementations described herein. It is, therefore, to be understood that the foregoing implementations are presented by way of example only and that, within the scope of the appended claims and equivalents thereto, implementations may be practiced otherwise than as specifically described and claimed. Implementations of the present disclosure are directed to each individual feature, system, article, material, kit, and/or method described herein. In addition, any combination of two or more such features, systems, articles, materials, kits, and/or methods, if such features, systems, articles, materials, kits, and/or methods are not mutually inconsistent, is included within the scope of the present disclosure.

Claims
I/We Claim:
1. A non-invasive glucose monitoring system, comprising: a sensor unit designed to detect glucose level changes through the skin without piercing it; a signal processing module configured to receive and process data from said sensor unit; a display module to showcase real-time glucose levels to the user; a calibration module allowing users to input known glucose levels for system accuracy adjustment; and a communication interface for transferring glucose data to external devices.
2. The system of claim 1, wherein the sensor unit utilizes near-infrared spectroscopy to detect glucose concentrations.
3. The system of claim 1, wherein the signal processing module further comprises machine learning algorithms trained to correlate detected signals with actual blood glucose levels.
4. The system of claim 1, further comprising an alert mechanism configured to warn the user when detected glucose levels are outside a predetermined range.
5. The system of claim 1, wherein the communication interface is wireless and compatible with multiple device platforms for data access and sharing.
6. A method for non-invasive glucose monitoring, comprising the steps of: placing a sensor unit against a user's skin; detecting glucose level changes through the skin using said sensor; processing the detected signals to determine glucose concentration; displaying the real-time glucose concentration to the user; and calibrating the system based on inputted known glucose levels.
7. The method of claim 6, further comprising the step of transmitting glucose data to an external device through a wireless communication interface.
8. The method of claim 6, wherein the step of detecting involves employing near-infrared spectroscopy.
9. The method of claim 6, further comprising the step of: setting a predetermined glucose range; and activating an alert mechanism when detected glucose levels fall outside the said range.
10. The method of claim 6, wherein the step of processing involves utilizing machine learning algorithms to correlate detected signals with actual blood glucose levels.

Non-invasive glucose monitoring system
Abstract
The present invention introduces a non-invasive glucose monitoring system designed to enhance user comfort and accuracy in diabetes management. This system comprises a sensor unit that detects glucose level variations through the skin without necessitating penetration. An integrated signal processing module receives and processes the acquired data from the sensor, ensuring precision in readings. Users benefit from a display module that provides real-time visualization of their glucose concentrations. A unique calibration module is incorporated, allowing users to input known glucose levels, thus fine-tuning the system's accuracy. Furthermore, the system boasts a communication interface, facilitating seamless transfer of glucose data to external devices, enhancing interoperability and data sharing capabilities. , Claims:Claims
I/We Claim:
1. A non-invasive glucose monitoring system, comprising: a sensor unit designed to detect glucose level changes through the skin without piercing it; a signal processing module configured to receive and process data from said sensor unit; a display module to showcase real-time glucose levels to the user; a calibration module allowing users to input known glucose levels for system accuracy adjustment; and a communication interface for transferring glucose data to external devices.
2. The system of claim 1, wherein the sensor unit utilizes near-infrared spectroscopy to detect glucose concentrations.
3. The system of claim 1, wherein the signal processing module further comprises machine learning algorithms trained to correlate detected signals with actual blood glucose levels.
4. The system of claim 1, further comprising an alert mechanism configured to warn the user when detected glucose levels are outside a predetermined range.
5. The system of claim 1, wherein the communication interface is wireless and compatible with multiple device platforms for data access and sharing.
6. A method for non-invasive glucose monitoring, comprising the steps of: placing a sensor unit against a user's skin; detecting glucose level changes through the skin using said sensor; processing the detected signals to determine glucose concentration; displaying the real-time glucose concentration to the user; and calibrating the system based on inputted known glucose levels.
7. The method of claim 6, further comprising the step of transmitting glucose data to an external device through a wireless communication interface.
8. The method of claim 6, wherein the step of detecting involves employing near-infrared spectroscopy.
9. The method of claim 6, further comprising the step of: setting a predetermined glucose range; and activating an alert mechanism when detected glucose levels fall outside the said range.
10. The method of claim 6, wherein the step of processing involves utilizing machine learning algorithms to correlate detected signals with actual blood glucose levels.