NEURO-SMART PILLOW: AI-DRIVEN PREDICTIVE HEALTHCARE FOR NEUROLOGICAL PATIENTS

Abstract

This invention discloses a smart pillow for continuous monitoring and predictive healthcare of neurological patients. The device uses embedded sensors, AI algorithms, and a mobile application to provide real-time physiological data, predictive alerts for critical events, and personalized recommendations, enhancing patient care and outcomes.

Specification

Description:FIELD OF THE INVENTION
This invention pertains to the field of medical devices, specifically wearable sensors and AI-powered predictive healthcare for neurological conditions. It integrates sensor technology, data analytics, and mobile application development to improve patient monitoring and treatment.
BACKGROUND OF THE INVENTION
Current methods for monitoring neurological patients, such as those with epilepsy or Parkinson's disease, often rely on infrequent clinical visits and patient self-reporting of symptoms. This approach lacks continuous monitoring, leading to delayed detection of critical events, potentially resulting in adverse health outcomes and reduced quality of life for patients. Caregivers also experience increased stress due to this lack of continuous monitoring.
While some wearable health monitoring devices exist, they frequently lack the sophisticated predictive capabilities and integrated AI analysis needed for proactively managing neurological conditions. Existing systems often focus on a limited set of vital signs or fail to provide timely, actionable insights. The integration of multiple sensor modalities for a comprehensive view of a patient's neurological state remains a challenge. Existing systems often lack the necessary sensitivity and accuracy for reliable early warning of critical events.
The use of AI in healthcare is increasingly prevalent, but applying AI algorithms to predict critical events in real-time from continuous physiological data collected in a comfortable and unobtrusive manner (like during sleep) is a significant technical hurdle. Accurately predicting seizure onset, sleep disturbances, or other neurological episodes requires complex pattern recognition and machine learning capabilities, along with robust data preprocessing techniques to handle noise and artifacts inherent in physiological signals.
Existing smart pillows offer limited functionality, primarily focusing on comfort features such as temperature regulation or ergonomic support. There is a lack of integrated, comprehensive monitoring and predictive analytics capabilities specifically tailored for neurological patients. The integration of sophisticated sensing, AI, and mobile app functionality in a comfortable pillow form factor represents a novel advancement in patient care.
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 Neuro-Smart Pillow is a novel medical device that continuously monitors key physiological parameters of neurological patients during sleep, using a combination of embedded sensors and advanced AI algorithms. The system provides real-time health insights, predictive alerts for critical events, and personalized recommendations to improve patient well-being. Data is transmitted via a companion mobile application, allowing for remote monitoring by caregivers and medical professionals.
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: WORKING MECHANISM OF THE NEURO-SMART PILLOW
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 Neuro-Smart Pillow uses a multi-layered design, incorporating a breathable outer layer for comfort, a memory foam core for support, and an embedded sensor array positioned to minimize disruption to sleep. The sensor array includes EEG sensors for brainwave activity monitoring, heart rate and respiration sensors for vital sign measurements, and potentially motion sensors for detecting changes in sleep posture. The specific sensors and their placement are optimized for accurate data acquisition while ensuring user comfort.
The embedded sensors collect continuous data throughout the night. This data is preprocessed by the AI processing unit to remove noise and artifacts before being fed into the machine learning algorithms. The AI processing unit employs advanced machine learning algorithms trained on a large dataset of physiological data from neurological patients to detect patterns and predict potential neurological events, such as seizures or sleep apneas. The algorithms are designed for high sensitivity and specificity to minimize false positives and negatives.
The AI processing unit wirelessly transmits data to a companion mobile application via Bluetooth or Wi-Fi, employing robust security protocols to protect patient data. The app provides real-time visualizations of the patient's physiological data, predictive alerts of potential health events, and personalized recommendations for sleep hygiene and overall health management. The visualization tools are designed for ease of use by both patients and caregivers.
The mobile application allows for remote access by caregivers and medical professionals, enabling timely interventions and improved healthcare coordination. It also offers historical data analysis for long-term trend monitoring and treatment optimization. The application includes features for managing user profiles, settings, and alert preferences.
, Claims:1. A smart pillow for monitoring neurological patients comprising: a multi-layered structure incorporating comfort layers and embedded sensors; a sensor array including at least EEG, heart rate, and respiration sensors; an AI processing unit to analyze sensor data and predict neurological events; and wireless communication capabilities for transmitting data to a mobile application.
2. The smart pillow, as claimed in Claim 1, wherein said AI processing unit utilizes machine learning algorithms trained on a large dataset of physiological data from neurological patients to identify patterns indicative of neurological events and generate predictive alerts.
3. The smart pillow, as claimed in Claim 2, wherein said mobile application provides real-time visualization of sensor data, predictive alerts, personalized recommendations to improve patient health and well-being, and historical data analysis for long-term trend monitoring and treatment optimization.
4. The smart pillow, as claimed in Claim 3, further comprising a rechargeable battery for extended operational time and robust security protocols for data transmission.
5. A method for monitoring the health of a neurological patient comprising: continuously acquiring physiological data from a smart pillow; pre-processing said data to remove noise and artifacts; processing said data with an AI algorithm to predict neurological events; and transmitting alerts and data via secure wireless communication to a mobile application for caregiver and medical professional access.
6. The smart pillow, as claimed in Claim 1, wherein said sensor array includes at least one motion sensor for detecting changes in patient sleep posture and generating corresponding data for analysis by the AI processing unit.
7. The smart pillow, as claimed in Claim 2, wherein said AI processing unit incorporates a noise reduction and artifact removal algorithm to improve the accuracy and reliability of the predictive alerts generated.
8. The method, as claimed in Claim 5, further comprising the step of providing personalized recommendations to the patient or caregiver based on the analysis of the physiological data and predicted neurological events. These recommendations may include adjustments to sleep hygiene practices, medication reminders, or other relevant guidance.
9. The mobile application, as claimed in Claim 3, wherein said application includes features for securely storing and managing patient health data, providing access controls for authorized caregivers and healthcare professionals, and generating reports for clinical use.

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