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💡[Feature]: "Detecting Stress Levels from PPG Sensor Data using ANN," including the README, requirements, and LICENSE files. #1590

@Pratik-Tech-Wizard

Description

@Pratik-Tech-Wizard

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Feature Description

Combined Biometrics:
-Heart Rate Variability (HRV): Calculate HRV metrics, which can provide insights into autonomic nervous system activity.
-Respiration Rate: If available, combine data from a respiration sensor to create a comprehensive stress profile.

Use Case

By integrating Heart Rate Variability (HRV) and Respiration Rate (RR) into the stress detection project, we can significantly enhance its effectiveness:

  1. Real-Time Monitoring: Continuously analyzes PPG data to detect changes in HRV and RR, providing immediate insights during stressful situations.

  2. Personalized Feedback: Offers tailored recommendations, such as breathing exercises, when heightened stress levels are detected.

  3. Longitudinal Analysis: Tracks HRV and RR over time, helping users identify patterns and triggers related to their stress levels.

  4. Enhanced Accuracy: Combines metrics for a more reliable assessment of stress, improving overall insights compared to PPG data alone.

  5. Health and Wellness Applications: Useful in fields like sports psychology and mental health, allowing practitioners to tailor interventions based on real-time data.

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Benefits

  1. Improved Accuracy: The integration of HRV and RR provides a more comprehensive assessment of stress levels, leading to better identification of stress triggers.

  2. Proactive Management: Users receive real-time feedback and actionable insights, enabling them to manage stress effectively through tailored interventions.

  3. Enhanced User Engagement: Personalized experiences can increase user motivation to monitor and improve their mental health.

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