The inspiration for Seizure Sensor came from a deeply personal place. Kevork's brother, who suffers from epilepsy, faces the constant threat of life-threatening seizures during the night. His parents relied on a basic webcam system to monitor him, often missing critical moments when seizures occurred. This pressing need for a more reliable monitoring system drove us to create Seizure Sensor.
Seizure Sensor is an innovative monitoring system that combines:
- Wearable technology with EMG sensors, accelerometers, and heart rate monitors
- Computer vision using OpenCV for motion detection
- A central MQTT server on a Raspberry Pi for data integration
- An ESP32-powered visual and auditory alarm system
This integrated system provides accurate, timely detection of seizure activity and alerts caregivers promptly, significantly improving the monitoring process for people with epilepsy.
- Initially, we attempted to develop an iOS app using Apple Watch for biometric data.
- Due to challenges with the Apple development platform, we pivoted to creating our own wearable using ESP32 microcontrollers.
- We developed custom hardware incorporating various sensors for comprehensive biometric data collection.
- We set up an MQTT server on a Raspberry Pi to integrate and process all sensor inputs.
- We implemented computer vision capabilities using OpenCV for motion detection.
- Finally, we created an alert system using ESP32 to provide clear visual and auditory alarms when a seizure is detected.
- Difficulties interfacing with the Apple development platform, leading to our pivot to custom hardware.
- Integrating multiple sensory inputs (EMG, accelerometer, heart rate) into a cohesive system.
- Implementing effective computer vision algorithms for seizure detection.
- Ensuring the system's reliability and accuracy without inducing actual seizures for testing.
- Successfully created a proof-of-concept system that meets and exceeds current FDA standards for seizure monitoring devices.
- Developed a custom wearable device that effectively collects and transmits critical biometric data.
- Integrated multiple technologies (wearables, computer vision, data processing) into a cohesive system.
- Created a system that not only detects motion but also corroborates it with EMG and heart rate data for more accurate seizure detection.
- The importance of flexibility in the development process, as demonstrated by our successful pivot from iOS to custom hardware.
- Techniques for integrating multiple sensory readings into an MQTT server for accurate biometric monitoring.
- The complexities and potential of computer vision in medical applications.
- The critical balance between innovation and ethical considerations in medical technology development.
- Further refine and enhance the computer vision model with specialized training on seizure footage.
- Conduct more extensive testing to validate the system's efficacy and reliability.
- Explore partnerships with medical institutions for clinical trials.
- Investigate the potential for miniaturization and commercialization of the technology.
- Develop a user-friendly interface for caregivers to easily monitor and respond to alerts.
Demo Video: https://youtu.be/o1jnZ2N-v0Q