PulseGuard

How we built it: PulseGuard was built using a webcam-based system that captures real-time video input from the user. We integrated the VitalLens API to analyze the webcam feed and estimate the user’s heart rate (BPM). Using Python, we processed this data to determine whether the person is in danger based on abnormal heart rate readings. If a critical threshold was detected, the system would trigger an emergency response. We also integrated Twilio, which allowed the system to automatically send alerts or contact emergency services when needed.

Challenges we ran into: We faced several challenges during development. Our Raspberry Pi and light sensor were damaged during the process, which disrupted our hardware testing. We also dealt with many bugs throughout the project, making it difficult to get all components working smoothly together. In addition, data was not consistently being saved, which affected testing and reliability. Another major challenge was connecting the VitalLens API properly with our Python code, which required a lot of debugging and troubleshooting.

Accomplishments that we're proud of: Despite the challenges, we are proud that we successfully integrated Twilio and got the emergency messaging system working reliably. The camera system was also able to function properly and capture live input data. In addition, we eventually managed to get the API working with the live video feed after troubleshooting, which was a major milestone for the project.

What we learned: Through building PulseGuard, we learned how to use Twilio for automated messaging and emergency alerts. We also gained a better understanding of the capabilities and limitations of AI in real-time health monitoring. A major takeaway was learning how to connect and integrate external APIs into a Python project, as well as improving our debugging skills when dealing with both software and hardware issues.

What's next for PulseGuard: A heart rate detector using a webcam Logs beats per minute (bpm) If the heart rate goes below or above a certain number based on age Triggers an emergency alert Calls an emergency contact or service

Built With: PulseGuard was built using Python, the VitalLens API, and the Twilio API. We also used OpenCV for webcam input, and experimented with Raspberry Pi for hardware integration.