SOPHON ACADEMY / Task
Introduction

Introduction

  • Objective

Develop a snoring monitoring and analysis system that utilizes the audio processing capabilities of the Milk-V Duo to monitor and analyze the characteristics of a user's snoring in real time. The system aims to help users understand and improve sleep quality and prevent sleep apnea.

 

  • Detailed Task Description

1. Snoring Detection Algorithm Development:
a. Develop an algorithm capable of accurately identifying snoring from a user's sleep audio.
b. The algorithm should distinguish snoring from other sleep sounds (such as breathing sounds, environmental noise, etc.).

 

2. Snoring Characteristics Analysis:
a. Implement snoring characteristic extraction, including the frequency, intensity, duration, and intermittency of snoring.
b. Analyze snoring patterns, such as continuity, periodicity, and abnormal interruptions, to assess sleep quality.

 

3. User Interface and Data Presentation:
a. Design a user-friendly interface that displays the results of snoring monitoring and analysis data.
b. Sleep suggestions and feedback: Provide suggestions for improving sleep quality based on the results of snoring analysis.

 

  • Performance Requirements
  1. The accuracy of snoring detection should be no less than 95%, with a false positive rate below 5%.
  2. The system should be able to continuously monitor and analyze sleep audio throughout the night without affecting the user experience.
  3. Support at least 10 hours of continuous audio analysis.
  4. Memory Usage: Optimize memory allocation while ensuring the functionality of snoring monitoring and analysis, to not exceed the 256MB memory limit.

 

  • Acceptance Criteria
  1. The snoring monitoring system should run stably on the Milk-V Duo and accurately identify snoring.
  2. The snoring characteristic analysis should be accurate, providing a detailed sleep data report.
  3. The user interface should be clear, easy to operate, and intuitive in data presentation.
  4. Functionality Testing: The system should pass at least 5 days of continuous monitoring tests to ensure stability and accuracy.
  5. The submitted project should include complete source code, documentation, and necessary resource files for subsequent maintenance and optimization.

 

By completing this task, developers will be able to demonstrate the potential application of the Milk-V Duo in the field of health monitoring, providing users with a practical tool to better understand and manage their sleep health.