Customized Assistant Glasses for Brain Paralysis People

Abstract

This invention relates to the field of Biomedical device development. These glasses offer a range of sophisticated features, including sleep detection, object recognition, and seamless interaction with mobile devices. The methodology begins with the setup of hardware components and the establishment of Bluetooth connectivity. Through mobile interaction, users can effortlessly access and view relevant information on an OLED display, enhancing user engagement. Integration of various sensors such as IR, ultrasonic, and an ESP-32 camera module empowers the glasses with functionalities like blind assistance, sleep monitoring, and surveillance capabilities. An alert system comprising LEDs, a buzzer, and real-time camera feeds ensures users receive timely notifications. The project utilizes input from blinking and ultrasonic sensors, which are processed by Processor, and alerts are communicated through the buzzer. Furthermore, the glasses receive input from smart lenses via Bluetooth connectivity, which is then analyzed by a Processor and presented on the OLED screen.

Specification

Description:FIELD OF THE INVENTION:
This invention relates to the field of Biomedical device development. Still further, the invention relates Assistant Glasses for Brain Paralysis People. Furthermore, it developed with EEG sensors to detect the Brain activity for paralysis people. Still, it detects the both eye sizes to measure the difference between the them. For paralysis patience, the size of both eyes are not same. It relates to the development of sleep detection features. Additionally, it relates to camera functionality, supported by ESP32 technology for versatile storage options and seamless interaction with mobile devices.

BACKGROUND OF THE INVENTION:
In recent years, we've witnessed impressive technological strides aimed at improving the lives of those with Paralysis and enhancing safety across various domains. Notable research has explored the potential of smart glasses, incorporating features like EEG brain activity monitoring, obstacle detection, drowsiness monitoring, and object recognition and navigation assistance to assist for paralysis people. EoG sensor is used measured the eye movement of the paralysis patient. EOG, or Electrooculography, is a method for determining the corneo-retinal standing potential between the front and back of the human eye. Electrodes are usually located above and below the eyes, or to the left and right of the eyes. EOG is generally used to detect eye movements. Using EOG sensors can help correlate eye movement artefacts in EEG recordings, assisting in their rejection.
However, a closer look at these initiatives reveals certain limitations, often stemming from their singular functionalities and a lack of adaptability to individual user needs. While some research focus on specific aspects like obstacle detection or drowsiness monitoring, few integrate these functionalities within a customizable framework. Moreover, the reliance on predefined algorithms may not cater to the dynamic requirements of users with varying degrees of visual impairment.
In this present invention, " Customized Assistant Glasses for Brain Paralysis People", navigation assistance and mobile connectivity for Paralysis people," designed to overcome these limitations by offering a versatile and personalized solution. By integrating an array of sensors, including IR and ultrasonic sensors for blind assistance, sleep detection capabilities, and an ESP-32 for camera-based surveillance, our smart glasses provide a comprehensive approach to address the unique needs of users. Going beyond existing solutions, our research empowers users by allowing them to customize functionalities based on their preferences, thereby fostering independence and inclusivity.
From the initialization phase, establishing Bluetooth connections with mobile devices, to the seamless integration of sensors for blind assistance and sleep detection, a user-centric and comprehensive solution. The alert system, utilizing LED, buzzer, and camera streams for surveillance, enhances user safety and awareness across various scenarios. A survey conducted to gauge user preferences and expectations revealed a growing demand for customizable solutions addressing visual impairments and diverse daily needs. The research aligns seamlessly with these insights, marking a substantial advancement in smart glasses technology and offering a user-centric and pioneering contribution to the field of assistive smart glasses.
In recent years, we've witnessed impressive technological strides aimed at improving the lives of those with Paralysis and enhancing safety across various domains. Notable research has explored the potential of smart glasses, incorporating features like EEG brain activity monitoring, obstacle detection, drowsiness monitoring, and object recognition and navigation assistance to assist for paralysis people. EoG sensor is used measured the eye movement of the paralysis patient. EOG, or Electrooculography, is a method for determining the corneo-retinal standing potential between the front and back of the human eye. Electrodes are usually located above and below the eyes, or to the left and right of the eyes. EOG is generally used to detect eye movements. Using EOG sensors can help correlate eye movement artefacts in EEG recordings, assisting in their rejection.
However, a closer look at these initiatives reveals certain limitations, often stemming from their singular functionalities and a lack of adaptability to individual user needs. While some research focus on specific aspects like obstacle detection or drowsiness monitoring, few integrate these functionalities within a customizable framework. Moreover, the reliance on predefined algorithms may not cater to the dynamic requirements of users with varying degrees of visual impairment.
In this research, " Customized Assistant Glasses for Brain Paralysis People", navigation assistance and mobile connectivity for Paralysis people," designed to overcome these limitations by offering a versatile and personalized solution. By integrating an array of sensors, including IR and ultrasonic sensors for blind assistance, sleep detection capabilities, and an ESP-32 for camera-based surveillance, our smart glasses provide a comprehensive approach to address the unique needs of users. Going beyond existing solutions, our research empowers users by allowing them to customize functionalities based on their preferences, thereby fostering independence and inclusivity.
From the initialization phase, establishing Bluetooth connections with mobile devices, to the seamless integration of sensors for blind assistance and sleep detection, a user-centric and comprehensive solution. The alert system, utilizing LED, buzzer, and camera streams for surveillance, enhances user safety and awareness across various scenarios. A survey conducted to gauge user preferences and expectations revealed a growing demand for customizable solutions addressing visual impairments and diverse daily needs. Our research aligns seamlessly with these insights, marking a substantial advancement in smart glasses technology and offering a user-centric and pioneering contribution to the field of assistive smart glasses.
OBJECT OF THE INVENTION:
The primary object of the invention is to provide customized assistant glasses for brain paralysis people.
SUMMARY OF THE INVENTION:
This invention introduces a versatile and multifunctional smart glasses system designed to significantly enhance the quality of life for individuals with diverse needs, particularly those with partial blindness or paralysis. By integrating advanced hardware and software technologies, the system offers a user-friendly solution that combines real-time data processing, navigation assistance, sleep monitoring, brain activity analysis, and multimedia capabilities in a single wearable device. One of the core features of the invention is its EEG-based brain activity monitoring system. Using an EEG sensor, the smart glasses capture brain wave signals, which are then preprocessed to remove noise and artifacts. The system filters the signals into delta, theta, alpha, beta, and gamma waves for analysis. By applying machine learning algorithms and techniques like power spectral density calculations and mean amplitude measurements, the system provides insights into brain activity, facilitating applications such as cognitive health monitoring.
The invention also includes an EOG-based eye movement detection system, which measures left and right eye movements using EOG sensors. Deep learning models analyze the sensor data to identify patterns indicative of paralysis in specific areas of the body. This feature is particularly beneficial for individuals requiring precise assessments of neural or muscular impairments. In terms of communication and real-time data access, the smart glasses feature an OLED display integrated with a processor and a Bluetooth module. This setup enables seamless connectivity with mobile devices, allowing users to access real-time information such as date, time, notifications, messages, and battery status directly on the glasses' display. This functionality ensures a streamlined and efficient user experience, particularly for users who require hands-free operation.
The system's navigation assistance is powered by an ultrasonic sensor, which continuously monitors the user's surroundings to detect obstacles. When an obstacle is identified, feedback mechanisms, including vibrating buzzers or LED lights, are activated to alert the user. This feature enhances mobility and safety, making the glasses particularly valuable for partially blind individuals. Additionally, an IR sensor monitors eye blinking patterns to detect drowsiness. If drowsiness is detected, the system triggers alerts, such as vibrating the buzzer, to keep the user alert, especially during critical tasks like driving.
The ESP32 processor, combined with a camera module, extends the glasses' functionality to multimedia applications. The camera captures video and images, supports minor hand gesture recognition, and provides flexible storage options via SD cards or FTP servers. With built-in Wi-Fi connectivity, the camera module allows seamless access to stored media across multiple networks, enhancing usability and accessibility. To ensure a robust, lightweight, and ergonomic design, all hardware components are securely integrated into a custom-designed sunglasses frame manufactured using advanced 3D printing technology. This design not only offers durability and functionality but also accommodates aesthetic preferences and comfort for a diverse range of users.
BRIEF DESCRIPTION OF THE DRAWINGS
A preferred embodiment of the invention is now described in detail. Referring to the drawings, numbers indicate parts throughout the views. Unless explicitly stated in the following disclosure, the drawings are not necessarily drawn to scale. As used in the description herein and throughout the claims, the following terms take the meanings explicitly associated herein unless the context dictates otherwise: the meaning of "a," "an." And "the" includes plural reference, the meaning of "in" includes "in" and "on.". The summary of the present invention, as well as the detailed description, are better understood when read in conjunction with the accompanying drawings that illustrate one or more possible embodiments of the present invention, which:
Fig. 1: Schematic of Assistant Glasses for Brain Paralysis People
Fig. 2: The components of a Glasses for Brain Paralysis People

DETAILED DESCRIPTION OF THE INVENTION
The present invention presents a comprehensive system combining EEG-based brain activity monitoring, obstacle detection, drowsiness monitoring, object recognition, and navigation assistance for individuals with paralysis or partial blindness, offering a versatile and user-friendly design. One of the key features is the monitoring of brain activity using electroencephalogram (EEG) signals. The system captures EEG signals, which are then preprocessed to remove noise and artifacts. Filtering methods extract delta, theta, alpha, beta, and gamma waveforms, which are further analyzed using advanced techniques such as power spectral density (PSD) calculations and mean amplitude measurements. This process, performed using tools like LabVIEW software, provides valuable insights into the user's cognitive state, facilitating health monitoring and therapeutic interventions.
In addition, the invention employs electrooculography (EOG) to assess eye movement. This technique measures the corneo-retinal standing potential to capture left and right eye movements. Leveraging deep learning algorithms, the system analyzes this data to identify paralysis on specific sides of the patient, enabling precise diagnostic capabilities for neurological and muscular impairments.

A robust processor forms the backbone of the device, managing real-time data transmission and display via an OLED screen. Paired with a Bluetooth module, the processor establishes seamless communication with the user's mobile device, enabling the reception and display of data such as date, time, messages, notifications, and battery status. This hands-free interaction enhances convenience, particularly for users requiring accessibility solutions.
Navigation assistance is provided through an integrated ultrasonic sensor, which emits waves to detect obstacles in the user's environment. The system processes these signals to identify hazards, triggering alerts like vibrating buzzers or activating LED lights. This functionality ensures enhanced mobility and safety for users with visual impairments. Additionally, an IR sensor monitors blinking patterns to detect drowsiness, triggering similar feedback mechanisms to keep users alert during critical activities, such as driving or operating machinery. The glasses are equipped with a camera module powered by the ESP32 processor, expanding their functionality to multimedia applications. The module supports video and image capture, hand gesture recognition, and flexible storage options, including SD cards and private FTP servers. Built-in Wi-Fi connectivity facilitates seamless access to captured media across networks, ensuring data accessibility and secure storage.
To accommodate the hardware components, the device incorporates a custom 3D-printed frame. This frame ensures a compact, lightweight, and ergonomic design that is both durable and aesthetically pleasing. The design integrates the processor, sensors, OLED display, and other components securely, providing optimal functionality and comfort tailored to user preferences.
This invention represents a significant advancement in wearable technology, addressing a wide range of user challenges. By combining state-of-the-art sensing, processing, and connectivity technologies, these smart glasses provide a comprehensive solution for medical monitoring, navigation assistance, multimedia functionality, and accessibility. The system offers unparalleled support for individuals with partial blindness, paralysis, or other disabilities, blending cutting-edge technology with practicality in a single, easy-to-use device.
The Customized Assistant Glasses for Brain Paralysis People represent a groundbreaking innovation designed to address the unique challenges faced by individuals with paralysis. By integrating multiple advanced technologies into a single wearable device, these glasses offer diagnostic, assistive, and safety-enhancing features, ensuring both functionality and ease of use.
The glasses include an EEG-based brain activity detection module, which monitors and analyzes brain wave patterns such as delta, theta, alpha, beta, and gamma waves. Using a combination of preprocessing techniques and machine learning algorithms, this module filters out noise and artifacts from EEG signals, providing insights into the user's cognitive states. This feature not only assists in tracking the mental health and rehabilitation progress of users but also opens avenues for personalized therapeutic interventions.
An eye movement detection module further enhances the glasses' diagnostic capabilities. This module employs an EOG sensor to measure left and right eye movements, using deep learning techniques to assess paralysis on specific sides of the user's body. Such a feature provides clinicians and caregivers with a precise, non-invasive method of monitoring and understanding the extent of the patient's motor impairments.
For seamless connectivity and accessibility, the glasses are equipped with a wireless communication module that facilitates real-time data exchange via Bluetooth. Notifications, messages, and other system updates are sent directly from a paired mobile device to the glasses, ensuring that users stay informed without needing to access their phones manually. Complementing this is the dynamic display module, which uses an OLED screen to present information like date, time, battery status, and alerts. The clear, user-friendly interface enhances convenience and usability.
To ensure user safety and mobility, the glasses integrate an object detection system with an ultrasonic sensor that identifies obstacles in the user's path. The system alerts the wearer through feedback mechanisms like a vibrating buzzer, enabling independent navigation. In addition, the proactive sleep detection system, powered by an IR sensor, monitors eye-blinking patterns to detect signs of drowsiness. This system triggers alerts to prevent accidents or lapses in concentration, particularly in scenarios requiring sustained attention, such as driving or operating machinery.
The glasses are further enhanced by an advanced camera system, which incorporates an ESP32 processor and camera module. This system supports video and image capture, gesture recognition, and flexible data storage options, such as SD cards or private FTP servers. The camera's ability to connect to multiple Wi-Fi networks ensures that captured data can be accessed or transferred seamlessly, making this feature highly versatile for personal, professional, or therapeutic use.

All these hardware components are integrated into a customized 3D-printed frame. Designed for durability and compactness, the frame securely houses the electronics while maintaining a lightweight and ergonomic structure. The use of 3D printing technology ensures that the frame can be tailored to meet individual preferences and needs, enhancing both functionality and aesthetic appeal.
, Claims:1. Customized Assistant Glasses for Brain Paralysis People, the glasses comprising:
a) a brain activity detection module, including an EEG sensor (4) and a processor configured to acquire, preprocess, and analyze delta, theta, alpha, beta, and gamma brain waves using machine learning algorithms;
b) an eye movement detection module, including an EOG sensor (6) and a deep learning model configured to measure left and right eye movements and assess paralysis on specific sides of a patient;
c) a wireless communication module, including a processor configured for seamless Bluetooth connectivity with a mobile device to enable real-time data exchange;
d) a dynamic display module, utilizing an OLED display (1) to present sorted and formatted real-time information such as notifications, date, time, and battery status;
e) an object detection system, incorporating an ultrasonic sensor to identify obstacles and a feedback mechanism to alert the user via a vibrating buzzer;
f) a pulse sensor (5) in the smart glasses which adds another layer of functionality, particularly focusing on health monitoring and real-time physiological assessment.
g) a proactive sleep detection system, featuring an IR sensor and processor to monitor blinking patterns and detect drowsiness, triggering alerts for user safety;
h) an advanced camera system, including an ESP32 processor and camera module (2) for image and video capture, gesture recognition, and flexible data storage options; and
i) a customized 3D-printed frame, designed to securely integrate all hardware components while ensuring functionality, durability, and aesthetic appeal.
2) The smart glasses system of claim 1, wherein: the modules operate synergistically to enhance user experience, mobility, and safety; the processor dynamically optimizes performance across functionalities, including data processing, connectivity, and user interaction; and the design supports modularity, enabling easy maintenance and customization for diverse user preferences.
3) A system for detecting brain activity, comprising:
a) an EEG sensor configured to acquire brain wave signals;
b) a processing unit for preprocessing the acquired brain wave signals; and
c) a machine learning algorithm implemented in the processing unit, wherein the algorithm analyzes delta, theta, alpha, beta, and gamma waves to classify or interpret brain activity patterns.
4) The system as claimed in claim 3, wherein the preprocessing includes signal filtering, noise reduction, and feature extraction to enhance the accuracy of the machine learning analysis.
5) A system for detecting eye movement and assessing paralysis, comprising:
a) an EOG sensor configured to measure left and right eye movements;
b) a deep learning model implemented in a processing unit, wherein the model analyzes the sensor data to identify and classify paralysis-related patterns specific to a side of the patient's body.
6) The system as claimed in claim 5, further comprising a user interface for displaying paralysis assessment results in real-time.
7) A wireless communication system for smart glasses, comprising:
a) a processor configured to establish seamless Bluetooth (3) connectivity with a mobile device;
b) a module for real-time data exchange between the smart glasses and
c) a mobile device, enabling enhanced user experience and convenience.
8) The system as claimed in claim 7, wherein the processor dynamically adjusts connection parameters to optimize energy efficiency and connection stability.

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