A device for recognizing facial expressions to prevent suicidality

Abstract

Device for recognizing facial expressions to prevent suicidal tendencies, comprising: a wrist-worn case with a digital display; embedded sensors, including a heart rate monitor, a skin conductance sensor, and an accelerometer, configured to continuously collect physiological and behavioral data indicative of mental health status; a microcontroller unit (MCU) that is operationally connected to the sensors and programmed to process sensor data in real time and execute machine learning algorithms to identify patterns associated with suicide risk; a wireless communication module that enables data transmission to an accompanying smartphone application; When high-risk patterns are detected based on combined physiological and behavioral metrics, the device automatically sends alerts to predefined emergency contacts, including the user's location and relevant health data, thus enabling immediate intervention.

Description

Technical field of the invention

[0001] The present invention relates to a device for detecting facial expressions to prevent suicidal tendencies. BACKGROUND OF THE INVENTION

[0002] The following background information relates to the present disclosure, but does not necessarily represent the state of the art.

[0003] Suicide rates are rising in today's society, particularly among people aged 15 to 35, who are often under immense pressure from academics, family expectations, and societal influences. This overwhelming pressure frequently leads to emotional distress that goes unnoticed until it is too late. Existing mental health support systems are typically reactive and unable to intervene immediately. There is a significant gap in the timely detection of suicidal tendencies and the alerting of those who can help. A proactive solution is needed that monitors emotional states and notifies close friends and family members when a person is at risk, so they can intervene and potentially prevent a tragedy.

[0004] To combat rising suicide rates among individuals aged 15 to 35, we propose a facial expression recognition device to prevent suicidal tendencies and continuously monitor the wearer's emotional and physiological state. The proposed system utilizes advanced sensors to track key metrics such as pulse rate and heart rate variability, which are crucial indicators of emotional stress. Employing AI algorithms, the device analyzes these metrics in real time to detect significant changes that could indicate a risk of suicidal behavior. When the proposed system detects critical emotional states, it triggers alerts that notify trusted contacts, such as family members and close friends, enabling them to provide immediate support and intervention.This proactive solution not only facilitates timely communication but also empowers users to select their own emergency contacts. The proposed system is designed to function discreetly as a normal accessory, ensuring comfort for daily wear. Furthermore, it synchronizes with a smartphone app that provides insights into the wearer's emotional health, boosting self-confidence and promoting proactive mental health management. By bridging the gap in existing mental health support systems, this wearable technology offers a vital tool for suicide prevention and promoting the well-being of vulnerable individuals.

[0005] The current state of the art / existing technology has several disadvantages. Therefore, there has long been a need in the arts. GOAL OF THE INVENTION

[0006] The main objective of the present invention is to provide a device for recognizing facial expressions in order to prevent suicidal tendencies.

[0007] Furthermore, the proposed system offers a comprehensive solution for monitoring the emotional and physiological states of individuals of all ages who may be at risk due to stress and emotional distress. The system aims to continuously track vital signs such as pulse rate and heart rate variability, utilizing advanced sensors and AI algorithms to detect early signs of emotional turmoil. By establishing a proactive alert system, the device notifies trusted contacts—such as family members and friends—if the wearer exhibits behaviors that could indicate potential suicidal tendencies, thus enabling timely intervention. In addition, the invention allows users to select their emergency contacts and control the alert mechanisms, thereby promoting a sense of security.Through a connected smartphone app, the proposed system promotes self-awareness and encourages proactive mental health management by providing insights into emotional well-being over time. Ultimately, this invention aims to reduce the stigma surrounding mental health issues by offering a discreet and accessible tool that facilitates early intervention and helps prevent tragedies by promoting the overall mental well-being of people of all ages.

[0008] These and other tasks and features of the present invention will become clear from the further disclosure, which is given in the detailed description below. SUMMARY OF THE INVENTION

[0009] Accordingly, the following invention provides a facial expression recognition device for preventing suicidal tendencies.

[0010] The invention is a smart wearable device specifically designed as a suicide prevention watch, aiming to combat rising suicide rates among people aged 15 to 35. This innovative device continuously monitors the wearer's emotional and physiological state using advanced sensors to measure vital parameters such as pulse rate and heart rate variability. These physiological indicators are crucial for detecting early signs of emotional distress, which often go unnoticed until a crisis occurs.

[0011] If the proposed system detects significant changes in the wearer's pulse or heart rate that could indicate an increased risk of suicidal behavior, it triggers an immediate alarm. This alert notifies trusted contacts such as family members, close friends, or caregivers, allowing them to intervene promptly and provide the necessary support. The device not only promotes a proactive approach to mental health but also empowers users by giving them control over who receives these alerts.

[0012] Furthermore, the proposed system synchronizes with a user-friendly smartphone app, providing insights into the wearer's emotional well-being over time. This feature fosters self-awareness and helps users manage their mental health more effectively. By combining continuous monitoring, real-time communication, and user support, this suicide prevention watch fills a significant gap in existing mental health support systems. It offers a vital tool for crisis prevention, promoting early intervention, and ultimately saving the lives of vulnerable individuals. DETAILED DESCRIPTION OF THE INVENTION

[0013] As used in the description herein and in the following claims, the meanings of "a", "an", and "the" also include plural references unless the context clearly indicates otherwise. In the description used herein, the meaning of "in" also includes "in" and "on" unless the context clearly indicates otherwise.

[0014] The present invention relates to a device for recognizing facial expressions to prevent suicidal tendencies.

[0015] The proposed system is an innovative wearable device designed to detect and prevent suicide attempts through real-time monitoring and alarm mechanisms. This advanced device integrates several key components and technologies to provide a comprehensive solution for suicidal individuals, ensuring timely intervention and support.

[0016] The proposed system resembles a standard smartwatch and features a slim and comfortable design suitable for everyday wear. It includes a digital display for user interaction and several embedded sensors for continuous health monitoring. The system is designed to be worn on the wrist, making it discreet and easy to use.

[0017] The proposed system includes a range of sensors that monitor various physiological and behavioral indicators associated with mental health and suicide risk: Heart rate monitor: This sensor continuously monitors the user's heart rate and heart rate variability (HRV). Abnormal heart rate patterns, such as an elevated resting heart rate or significant fluctuations, may indicate stress, anxiety, or panic attacks, which are potential warning signs of suicidal behavior.

[0018] Skin conductance sensor: This sensor measures skin conductance (SCL), which is an indicator of emotional arousal. High skin conductance is associated with heightened emotional states such as anxiety or stress, which are crucial for monitoring in suicide prevention.

[0019] Accelerometer: The accelerometer detects movement patterns and physical activity. Sudden inactivity, irregular movements, or patterns indicative of self-harming behavior can trigger alarms for further evaluation.

[0020] The core of the proposed system is its microcontroller unit (MCU), which processes the data collected by the sensors. The MCU executes sophisticated algorithms designed to analyze physiological and behavioral data in real time. These algorithms are trained to detect patterns and anomalies that may indicate a suicide risk. For example, a combination of elevated heart rate, high skin conductance, and sudden inactivity could indicate a high-risk situation requiring immediate attention.

[0021] A key feature of the proposed system is its ability to send real-time alerts. If the system detects a pattern indicating a potential crisis, it uses its wireless communication module (Bluetooth or Wi-Fi) to send alerts to predefined emergency contacts. These contacts can include family members, friends, mental health professionals, or emergency services. The alerts contain the user's location and relevant health data, enabling rapid intervention.

[0022] The proposed system is paired with an accompanying smartphone application that fulfills several functions: Data visualization: The app displays real-time and historical health data, allowing users and caregivers to monitor trends and identify potential problems.

[0023] Warnings and notifications: The system receives and displays warnings from the suggested system and provides additional details and options for responding to the warnings.

[0024] Mental health resources: The system provides access to mental health resources, including contact information for mental health professionals, crisis helplines, and self-help materials.

[0025] In addition to real-time monitoring, the proposed system uses machine learning techniques to perform predictive analytics. By analyzing long-term trends and historical data, the system can identify patterns indicating an increasing risk of suicide. This predictive capability allows for preventative measures to be taken before a crisis occurs.

[0026] The proposed system is equipped with a high-performance battery and an efficient energy management system, ensuring a long battery life and continuous operation. This minimizes the need for frequent charging and ensures that the proposed system can provide consistent monitoring.

[0027] Given the sensitivity of the data, the proposed system and its associated app employ robust encryption and data security measures. User data is securely stored and transmitted, ensuring that personal information remains confidential and protected from unauthorized access. Various steps:

[0028] The proposed AI-based system comprises a series of integrated processes and components that work together to detect and prevent suicidal behavior through real-time monitoring and warning mechanisms. Here are the steps of the process and its composition: The user carries the proposed system: The user wears the proposed system on their wrist like a normal smartwatch. Data collection: ◯ Heart rate monitor: ▪ Continuously measures the user's heart rate and heart rate variability (HRV). ◯ Skin conductance sensor: ▪ Monitors skin conductance to detect emotional arousal Accelerometer: ▪ Tracks physical activity and movement patterns. Data transmission to the microcontroller: The sensors send the collected data to the microcontroller unit (MCU) in the proposed system. Data preprocessing: The MCU filters and preprocesses the raw data to remove noise and prepare it for analysis. AI-based analysis: ◯ Pattern recognition: ▪ The AI ​​algorithms analyze the data to identify patterns that indicate stress, anxiety, or depression. ◯ Anomaly detection: ▪ Recognizes deviations from normal behavior that may indicate a risk of suicide. ◯ Risk assessment: ▪ Assess the risk level based on the identified patterns and anomalies. Decision making: ◯ Low risk: ▪ Continues monitoring without warnings. ◯ Medium risk: ▪ Notifies the user with a reminder to check their mental health. ◯ High risk: ▪ Triggers real-time alerts to emergency contacts and mental health professionals. Real-time alerts: ◯ Wireless communication module: ▪ Sends warnings and data via Bluetooth or Wi-Fi to the paired smartphone app. ◯ Smartphone app: ▪ Displays real-time data and alerts. ▪ Sends notifications to emergency contacts. Emergency response: ◯ Emergency contacts: ▪ Receive notifications with the user's location and health data. ▪ Can initiate immediate intervention and support. User interaction with smartphone app: o Display of health metrics: ▪ The app displays real-time and historical health metrics. ◯ Mental health resources: ▪ Provides access to resources and support for mental health. ◯ Emergency contact management: ▪ Allows users to manage their emergency contact list. Continuous monitoring: The proposed system continuously monitors the user's health metrics and repeats the data collection, processing, and alert cycle. Composition of the proposed AI-based system: Smartwatch device: ◯ Display screen: ▪ Displays health metrics and notifications. Comfortable design: ▪ Suitable for continuous wear. Embedded sensors: ◯ Heart rate monitor: Located on the back of the proposed continuous heart rate tracking system. ◯ Skin conductance sensor: ▪ Positioned to measure skin conductance. Accelerometer: ▪ Embedded to track movement and physical activity. Microcontroller Unit (MCU): ◯ Data processing: ▪ Receives and processes sensor data. ◯ Algorithm execution: ▪ Runs AI algorithms for pattern recognition and anomaly detection. Wireless communication module: ◯ Bluetooth / WLAN: ▪ Facilitates data transfer to the smartphone app. Battery and energy management: ◯ High-capacity battery: ▪ Ensures a long battery life for continuous monitoring. ◯ Energy management system: ▪ Optimizes battery consumption. Smartphone application: ◯ Data visualization: ▪ Displays real-time and historical data. ◯ Warning messages: ▪ Provides notifications and alerts for the user and emergency contacts. ◯ Resource access: ▪ Provides access to resources and support for mental health. Security features: ◯ Data encryption: ▪ Ensures secure data transmission and storage. ◯ Data protection controls: ▪ Protects user information and restricts access to authorized persons.

[0029] Although various embodiments of the present disclosure have been presented and described here, it is clear that the disclosure is not limited to these embodiments. Numerous modifications, changes, variations, substitutions, and equivalents will be obvious to the person skilled in the art without deviating from the spirit and scope of the disclosure as described in the claims.

Claims

[1] A facial expression detection device for preventing suicidal tendencies, comprising: a wrist-worn case with a digital display; embedded sensors, including a heart rate monitor, a skin conductance sensor, and an accelerometer, configured to continuously collect physiological and behavioral data indicative of mental health status; a microcontroller unit (MCU) operatively connected to the sensors and programmed to process sensor data in real time and execute machine learning algorithms to identify patterns associated with suicide risk; a wireless communication module that enables data transfer to a companion smartphone application; When high-risk patterns are detected, the device automatically sends alerts to predefined emergency contacts based on combined physiological and behavioral metrics, including the user's location and relevant health data, enabling immediate intervention.