AN AI-BASED PREDICTIVE HEALTHCARE DEVICE FOR REAL-TIME PATIENT MONITORING

Abstract

An AI-based predictive healthcare device for real-time patient monitoring is disclosed in the present invention. The device comprises a sensor module, an AI system, and a communication module. The device is configured to collect physiological data, analyze the data using AI algorithms, and provide real-time feedback and alerts to healthcare providers.

Specification

Description:FIELD OF THE INVENTION
This invention relates to a healthcare system, and more particularly to an AI-based predictive healthcare device for real-time patient monitoring.
BACKGROUND OF THE INVENTION
Traditional healthcare systems often rely on periodic check-ups and reactive treatments. This approach can lead to delays in identifying potential health risks and may not be optimal for managing chronic conditions. Early detection of health issues is crucial for effective healthcare, especially for chronic diseases. Timely intervention can significantly improve patient outcomes and reduce healthcare costs.
PRIOR ART
Following are some relevant prior arts to the present invention:
US20220302716A1: A computer-implemented system for automatically recording and generating predictive outputs relating to a medical procedure. The system uses biometric sensory data from a healthcare practitioner to estimate their stress level and potentially improve the procedure's outcome.
US10194862B2: A wearable device with a display dial for displaying health parameters and an ejectable tray for blood sample collection. This invention focuses on the convenience and functionality of the wearable device itself.
US10456078B2: A wearable device for manual wheelchair users that provides alerts for increased risk of injury. The device uses sensors to monitor the user's physical activity and alert them to potential injury risks.
SUMMARY OF THE INVENTION
This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention.
This summary is neither intended to identify key or essential inventive concepts of the invention and nor is it intended for determining the scope of the invention.
To further clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.
The present invention provides an AI-based predictive healthcare device for real-time patient monitoring. The device comprises a sensor module for collecting physiological data, an AI system for analyzing the data and predicting potential health risks, and a communication module for transmitting alerts to healthcare providers.
The device is configured to provide continuous monitoring, real-time analysis, and predictive alerts to facilitate proactive healthcare interventions. This approach enables early detection of potential health issues and allows for timely medical intervention, leading to improved patient outcomes and reduced healthcare costs.
BRIEF DESCRIPTION OF THE DRAWINGS
The illustrated embodiments of the subject matter will be understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The following description is intended only by way of example, and simply illustrates certain selected embodiments of devices, systems, and methods that are consistent with the subject matter as claimed herein, wherein:
FIGURE 1: ILLUSTRATES GENERAL ARCHITECTURE OF REAL TIME HEALTH CARE SYSTEM
FIGURE 2: ILLUSTRATES BLOCK DIAGRAM OF WEARABLE HEALTHCARE DEVICE
FIGURE 3: ILLUSTRATES FLOW CHART OF AI BASED ALGORITHM PROCESS
The figures depict embodiments of the present subject matter for the purposes of illustration only. A person skilled in the art will easily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.
DETAILED DESCRIPTION OF THE INVENTION
The detailed description of various exemplary embodiments of the disclosure is described herein with reference to the accompanying drawings. It should be noted that the embodiments are described herein in such details as to clearly communicate the disclosure. However, the amount of details provided herein is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the present disclosure as defined by the appended claims.
It is also to be understood that various arrangements may be devised that, although not explicitly described or shown herein, embody the principles of the present disclosure. Moreover, all statements herein reciting principles, aspects, and embodiments of the present disclosure, as well as specific examples, are intended to encompass equivalents thereof.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms "a"," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes" and/or "including," when used herein, specify the presence of stated features, integers, steps, operations, elements and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof.
It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
In addition, the descriptions of "first", "second", "third", and the like in the present invention are used for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Thus, features defining "first" and "second" may include at least one of the features, either explicitly or implicitly.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which example embodiments belong. It will be further understood that terms, e.g., those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The AI-Based Predictive Healthcare System utilizes wearable technology to collect physiological data such as heart rate, blood pressure, oxygen saturation, and body temperature. This data is transmitted wirelessly to a centralized cloud server or a local processing unit. The AI system, trained on extensive historical patient data and medical knowledge, analyzes the data in real-time.
The AI system employs machine learning techniques, including but not limited to, regression analysis, decision trees, neural networks, deep learning models, and natural language processing (NLP). This comprehensive analysis allows the system to identify patterns, trends, and anomalies that may be indicative of potential health risks.
The system provides real-time feedback to healthcare practitioners and caregivers through an intuitive dashboard, accessible on various devices such as smartphones, tablets, and computers. The dashboard visualizes the patient's health data, highlights critical metrics, and provides predictive insights.
In case of any detected anomalies or potential health risks, the system sends out alerts via various communication channels, including SMS, email, and push notifications. This timely notification allows healthcare providers to intervene promptly and provide necessary medical assistance.
The system also incorporates a feedback mechanism where healthcare professionals can provide input on the system's predictions and alerts. This feedback is used to continuously refine the AI algorithms and improve the system's accuracy and effectiveness.
, Claims:1. An AI-based predictive healthcare device for real-time patient monitoring, comprising:
a sensor module configured to collect physiological data from a patient;
an AI system configured to analyze the physiological data and predict potential health risks; and
a communication module configured to transmit alerts to healthcare providers based on the predicted potential health risks.
2. The device as claimed in claim 1, wherein the sensor module is configured to collect physiological data selected from a group consisting of heart rate, blood pressure, oxygen saturation, and body temperature.
3. The device as claimed in claim 1, wherein the AI system is trained on historical patient data and medical knowledge.
4. The device as claimed in claim 1, wherein the AI system employs machine learning techniques selected from a group consisting of regression analysis, decision trees, neural networks, deep learning models, and natural language processing (NLP).
5. The device as claimed in claim 1, further comprising a feedback mechanism configured to receive input from healthcare professionals on the system's predictions and alerts.
6. The device as claimed in claim 1, wherein the communication module is configured to transmit alerts via one or more communication channels selected from a group consisting of SMS, email, and push notifications.
7. A method for real-time patient monitoring, comprising:
collecting physiological data from a patient using a sensor module;
wirelessly transmitting physiological data to an AI system;
analyzing physiological data using the AI system to predict potential health risks; and
transmitting alerts to healthcare providers based on the predicted potential health risks.
8. The method as claimed in claim 7, further comprising:
providing real-time feedback to healthcare practitioners and caregivers through an intuitive dashboard accessible on various devices.
9. The method as claimed in claim 7, further comprising:
receiving input from healthcare professionals on the system's predictions and alerts; and
refining the AI algorithms based on the received input.
10. A system for real-time patient monitoring, comprising:
a wearable device configured to collect physiological data from a patient;
a cloud server or a local processing unit configured to receive the physiological data from the wearable device; and
an AI system configured to analyze the physiological data and predict potential health risks, wherein the AI system is trained on historical patient data and medical knowledge.

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