Explore a comprehensive technical talk that delves into the innovative applications of TinyML in wearable technology, focusing on ultra-low power embedded systems design. Learn how Sensio Enterprises implements TinyML solutions to meet strict power constraints in wearable devices, with a detailed examination of their Orbyt Smart Ring product. Discover the engineering challenges and solutions behind integrating multiple biosensors into a compact form factor while maintaining extended battery life despite using a significantly smaller battery than traditional smartwatches. Gain insights into sensor abstraction, machine learning implementation for physiological parameter measurements, and the practical challenges of heart rate monitoring and cortisol detection. The presentation covers crucial aspects of embedded systems design, including power optimization strategies, sensor integration, and the role of TinyML in advancing wearable technology capabilities.
Overview
Syllabus
Introduction
Introducing Kenjo
About TinyML
Machine Learning Sensors
Sensor Abstraction
Smart Ring
TinyML benefits
Open problems
Heart rate
Conclusion
Why dont we have usable data
Simple analogy
Chest Patch
Cortisol
Taught by
EDGE AI FOUNDATION