LEADING AI IN EARLY DISEASE DETECTION WITH SURVEIL HEALTH APPLICANTS

Abstract

The proposed invention Surveil Early Health Detection System (SEHDS), set to revolutionize the healthcare landscape, particularly in the realm of preventive monitoring of infant well-being. By effortlessly merging artificial intelligence, augmented reality, and state-of-the-art surveillance technology, the SEHDS streamlines the detection of possible health concerns, reducing the reliance on human input. Utilizing machine learning algorithms refined through a varied data set encompassing numerous health conditions and their respective treatments, the system shines in delivering precise and instantaneous health condition forecasts.The integration of expanded reality interfacing upgrades the involvement for healthcare professionals, giving an instinctive and immersive environment for speaking to complex wellbeing data. Moreover, the SEHDS caution framework utilizes speakers to ensure incite notices to healthcare suppliers upon recognizing potential wellbeing dangers, advancing quick and centered reactions. Fundamental equipment components contain high-definition observation cameras, imperative sign screens, miniaturized scale controllers for productive information dealing with, and communication units for consistent network. Past its innovative advancement, the SEHDS emphasizes security, security, and adherence to directions. Scrambled communication conventions and rigid security measures ensure understanding data, whereas compliance with healthcare guidelines advances moral execution. This groundbreaking activity means a major headway in early wellbeing distinguishing proof, advertising a all encompassing and successful arrangement for preventive wellbeing measures, particularly pivotal for guaranteeing the imperativeness of newborn children. 3 claims and 3 figures

Specification

Description:LEADING AI IN EARLY DISEASE DETECTION WITH SURVEIL HEALTH APPLICANTS
Field of the Invention
The proposed invention is to revolutionize healthcare by employing AI, computer vision, and augmented reality to enable early detection of severe health conditions through advanced surveillance, fostering timely interventions and ultimately improving patient outcomes.
Objectives of the Invention
The primary objective of propounding this idea of Surveil Health Early Detection System is to revolutionize healthcare by creating an integrated system that employs AI, augmented reality, and advanced surveillance for comprehensive infant or adult monitoring. The objective is to analyze vital signs, including heart rate, breathing rate, and oxygen levels, to detect early signs of severe health conditions. By providing real-time alerts to healthcare professionals through an augmented reality interface, the system facilitates rapid intervention and personalized care. This innovative approach strives to enhance patient outcomes, particularly in infants, by ensuring timely and proactive responses to potential critical health situations.
Background of the Invention
Surveil Health emerges from the exigency for sophisticated healthcare solutions, particularly in the realm of infant health monitoring. Prevailing methodologies for early detection of severe health conditions exhibit limitations in real-time, all-encompassing surveillance. The inventive concept herein addresses this lacuna by introducing an amalgamated system synergizing artificial intelligence, augmented reality, and cutting-edge surveillance technologies. The impetus for this innovation lies in establishing a proactive healthcare paradigm, empowering healthcare practitioners with continuous vital sign monitoring, expeditious anomaly detection, and early intervention capabilities. The underlying commitment is to elevate patient outcomes, especially within the susceptible cohort of infants, through avant-garde technology and bespoke healthcare interventions.
For instance, US9843743B2 has various techniques that are disclosed for systems and methods using thermal imaging to monitor an infant or other persons that may need observation. For example, an infant monitoring system may include an infrared imaging. Module, a visible light camera, a processor, a display, a communication module, and a memory. The monitoring system may capture thermal images of a scene including at least a partial view of an infant, using the infrared imaging module enclosed in a portable or mountable housing configured to be positioned for remote monitoring of the infant. Various thermal image processing and analysis operations may be performed on the thermal images to generate monitoring information relating to the infant. The monitoring information may include various alarms that actively provide warnings to caregivers, and user-viewable images of the scene. The monitoring information may be presented at external devices or the display located remotely for convenient viewing by caregivers.Similarly, JPH09275518A relates to The present invention is provided in an infrared camera head used in a thermographic device, and is used for mixing a thermal image and a visible image by imaging the same object as the infrared camera head. The present invention relates to a mechanism for changing a mounting angle provided on a mounting base of a visible image camera to be used.
WO2011151806A1 provides a method for determining a body temperature of a patient or subject is disclosed, in which a contact less infrared thermometer is manually positioned such as to point at a target area, and by activating the thermometer such that it measures the internal temperature of a patient and reads, via the thermometer, and for a predetermined time interval, the intensity of an infrared radiation in arrival from the target area. The target area is a body surface of a human or animal patient selected from a body location group comprising the ethmoid sinus, the canthus, the open eyelid or the closed eyelid.
US10758184B2 provides unique methods and bio-imaging systems are introduced herein for self-automated self-operable biomedical devices and methods for bio-signal monitoring, such as electrocardiograms (ECG), heart rate, and other vital signs, requiring no trained medical assistance or minimal assistance. In particular, methods and devices disclosed herein may require no dedicated medical resources, generate diagnostic quality results, and provide for motion artifact correction without inducing discomfort or irritation. Moreover, long term recording is realizable. Such methods and devices reduce the backlog of patients at out-patient wards as well as emergency response in remote areas.EP2663228B1 proposes this invention relates to the determination and representation of physiological information relating to a heart surface such as electro anatomical mapping and annotation.
Summary of the Invention
This innovative healthcare system represents a paradigm shift in the monitoring and management of infant health. By intricately integrating cutting-edge technologies, including artificial intelligence, augmented reality, and advanced surveillance mechanisms, the invention seeks to establish a robust and proactive healthcare framework.
The system offers real-time analysis of crucial vital signs, such as heart rate, breathing rate, and oxygen levels, ensuring continuous surveillance of infants. Rapid anomaly detection triggers immediate alerts to healthcare professionals, facilitating swift and personalized interventions.
The augmented reality interface further enriches data visualization, empowering medical practitioners with an unparalleled depth of information for informed decision-making. The overarching objective is to rethink early discovery and mediation techniques, with a specific accentuation on upgrading understanding results, particularly within the basic wellbeing scenarios confronted by newborn children.
Brief Description of Drawings
The innovation will be depicted in detail with the reference to the model epitomes appeared within the figures wherein:
Figure-1: Flowgorithm speaking to the work stream of the Surveil Early Wellbeing Location Framework
Figure-2: Diagrammatic representation of capacity of the details of each quiet within the database
Figure-3: Stream chart speaking to the fundamental engineering and workflow of the created model.
Detailed Description of the Invention
By computerizing the discovery of conceivable wellbeing issues and lessening the require for human intercession, the early wellbeing discovery framework looks for to convert understanding checking. It employments pictures of diverse ailments to foresee and create wellbeing conditions after being prepared on a wide run of information. Infection names, pictures of shifting degrees of tribulation, and coordinating treatments are all included within the information set as key-value sets. In expansion to speeding up information recovery, this framework is fundamental for the early recognizable proof of restorative disarranges. When conceivable issues are recognized, it informs restorative work force by means of speaker-based alarms and expanded reality (AR), permitting for incite activity. To guarantee smooth integration and valuable application in healthcare settings, usage calls for components like modern reconnaissance cameras, increased reality interfacing, and successful information capacity frameworks.
The components in a testing system for an introductory wellbeing observing framework, especially one that joins observation innovation, can change broadly and ought to envelop numerous aspects of the system's capability, effectiveness, and steadfastness. Within the Beginning Wellbeing Checking Framework (IHMS), an all-encompassing equipment setup is utilized for productive real-time wellbeing following. The fundamental components comprise of a central preparing unit (CPU), sensors, and communication modules, taking after the elemental parts utilized within the IHMS system. The IHMS utilizes a vigorous CPU, just like the Raspberry Pi, to oversee picture preparing, machine insights, and expository capacities for wellbeing information. The Raspberry Pi 4B, highlighting its 32-bit micro-processing unit and 8GB Smash, ensures compelling handling of wellbeing data and underpins clear administration of video shows for picture preparing. A photoplethysmography (PPG) sensor or an electrocardiogram (ECG) sensor is regularly utilized to gage heart rate. PPG sensors can be connected to the skin surface to watch blood volume changes, whereas ECG sensors survey the electrical action of the heart. Infrared temperature sensors or thermocouples are commonly sent to degree body temperature. These sensors can capture varieties in skin temperature, conveying basic information for assessing an individual's wellbeing. Beat oximeters are customarily utilized to decide oxygen immersion levels within the circulation system. These sensors regularly utilize infrared light to evaluate the amount of oxygen-carrying hemoglobin show within the blood. Near-infrared light falls within the wavelength range of roughly 700 to 2500 nanometers. When near-infrared light interatomic with natural tissues, it is somewhat retained, transmitted, or scattered. The assimilation of light is influenced by the nearness of specific particles, counting glucose. Optical sensors containing light-emitting diodes (LEDs) and finders are generally incorporated into NIRS gadgets. The LEDs emanate near-infrared light into the tissue, and the locators assess the sum of light that's either retained or scattered by the tissue.
The integration of an AI right hand with stages like GitHub sets up a coordinate and proficient interface between clients and healthcare experts, empowering the consistent trade of wellbeing information, experiences, and criticism. This collaborative approach cultivates proactive healthcare mediations by encouraging real-time communication and personalized suggestions. Clients can share their restorative data, concerns, and way of life information, accepting opportune input and master direction. The stage, leveraging secure and organized highlights associated to GitHub, guarantees protection and compliance with healthcare guidelines. This imaginative integration enables people to effectively take part in their wellbeing administration, advancing a association with healthcare experts for educated decision-making and proactive intercessions.
The Surveil Early Wellbeing Location Framework (SEHDS) coordinating information analytics to comprehensively analyze wellbeing patterns, development designs, and generally well-being, giving clients with profitable bits of knowledge to create educated choices around their wellbeing. By leveraging progressed expository methods, the SEHDS distinguishes designs in wellbeing information, empowering proactive measures for early location of potential wellbeing issues. This explanatory approach not as it were engages people to effectively oversee their well-being but too encourages a personalized and data-driven approach to healthcare. The SEHDS's capacity for in-depth wellbeing examination contributes to a all encompassing understanding of person wellbeing directions, cultivating early mediation and preventive techniques for made strides wellbeing results.
The wellbeing information amassed within the Surveil Early Wellbeing Discovery Framework (SEHDS) fulfills a double part, not as it were empowering real-time supervision but too serving as a pivotal preparing asset for the system's demonstrate. This double usefulness is crucial for progressing the accuracy and prescient ability of the SEHDS in up and coming wellbeing checking activities. The data assembled amid real-time oversight constitutes a profitable store of shifted wellbeing circumstances, reflecting changes in person wellbeing states over time. By repurposing this information for show preparing, the framework utilizes a careful and agent dataset, empowering the demonstrate to memorize and generalize over a wide extend of wellbeing conditions. This iterative learning approach from chronicled information guarantees that the SEHDS persistently improves its capacity to identify designs, inconsistencies, and unpretentious signs of wellbeing concerns, in this manner cultivating progressing change and refinement of its prescient capabilities for more viable and custom-made wellbeing observing within the long run. In conclusion, the SEHDS utilizes an progressed equipment setup to handle the squeezing require for early wellbeing location and intervention. Its adaptability and consolidation of cutting-edge advances outline its capacity to convert healthcare by advertising proactive and personalized wellbeing checking arrangements. Also, this information, once collected and produced, can be reapplied as preparing fabric to further improve the show and surrender progressed expectations amid consequent information collections. It can encourage more viable administration, examination, visualization, and translation to realize better and hoisted results.
Advantages of Surveil Early Health Detection System (SEHDS),
SEHDS encourages intensive perception of fundamental signs imperative for assessing newborn child wellness, counting beat rate, respiratory rate, body warm, and blood oxygen immersion. Joining of Progressed Advancements: The framework easily blends state-of-the-art innovations like fake insights (AI), expanded reality (AR), and checking for a comprehensive technique to newborn child wellbeing evaluation. Quick Peculiarity Acknowledgment: AI calculations reliably scrutinize accumulated information, instantly recognizing inconsistencies in crucial signs and actuating moment alarms for opportune activities in basic healthcare circumstances. Expanded Reality Visualization: AR innovation improves the client interface, engaging healthcare laborers to see real-time wellbeing markers and superimpose pertinent data, helping in educated decision-making. Continuous Wellbeing Assessment: The system's information preparing capabilities rise above irregularity acknowledgment, empowering the distinguishing proof of designs and patterns in newborn child wellbeing information over time for a more point by point comprehension. Quick and Sound-related Notices: A particular include incorporates an sound-related alarm framework that reports the patient's title within the confront of recognized serious wellbeing conditions, guaranteeing quick reactions in active healing center settings. Progressed Situational Mindfulness: Progressed observation components offer a wide viewpoint, upgrading by and large situational understanding for healthcare suppliers and avoiding pivotal wellbeing pointers from being missed. Information Security and Security Methodologies: Unbending measures are put in put to ensure delicate wellbeing data, guaranteeing adherence to healthcare controls and moral measures, in this way prioritizing quiet privacy and security. Coordinates Information Visualization: The AR interface not as it were exhibits real-time wellbeing measurements but moreover overlays related data, such as past wellbeing information and related restorative histories, giving healthcare experts a total diagram. Customized and Preventive Healthcare: The system's functionalities cultivate custom-made and expectant healthcare approaches by setting up progressing wellbeing designs and empowering educated choices based on nitty gritty wellbeing examinations.

3 Claims and 3 Figures
Equivalents
The current development, "Spearheading AI in Early Ailment Distinguishing proof with Surveil Wellbeing," utilizes data-centric oversight to distinguish wellbeing dangers at an early arrange, empowering quick intercession that improves understanding comes about, optimizes treatment, and hoists generally living standards. , Claims:The scope of the innovation is characterized by the taking after claims:

Claim
1. A Leading AI In Early Disease Detection with Surveil Health Applicants comprising
a) The system Integration of augmented reality (AR) technology to provide a real-time visualization of health metrics, overlaying contextual information for enhanced decision-making by healthcare professionals.
b) The attention gates Artificial intelligence (AI) algorithms configured for efficient anomaly detection, swiftly identifying deviations from established baseline health metrics and triggering alerts upon detecting severe health conditions.
c) A comprehensive surveillance system utilizing strategically positioned cameras to continuously capture real-time health data, including vital signs such as heart rate, breathing rate, body temperature, and blood oxygen levels.
2. According to claim 1 , the AI algorithms capable of establishing longitudinal patterns and trends in an individual's health metrics over time, contributing to personalized and proactive healthcare strategies.
3. As per claim 1, the continuous real-time monitoring of health metrics, coupled with a notification system that immediately alerts healthcare professionals when potential health issues are detected, ensuring timely intervention.

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