While building wearables to measure emotional stress, we learned that deep brain activation during seizures could show up as a change in electrical signals measured on the wrist. This unexpected finding led us to develop a wristband, “Embrace” that today is worn to alert to neurological events that might be potentially life-threatening. This talk will tell the story of Empatica’s development of a product that wins design prizes for its appearance, looks like a cool consumer timepiece, and yet is collecting clinical quality data and running analytics based on sophisticated machine learning to advance personalized health.
The design, testing, and processing of metals is becoming increasingly driven by computation and automation—for instance, gaps in physical models are addressed by machine learning, and additive manufacturing is crossing from prototyping to production. These developments foreshadow a digital transformation in the manufacturing of metal components and structures, optimizing performance across scales, from atoms to meters.
Can data series from a broad patient population be relevant and reliable tools in predicting individual outcomes when compared to personal wellness sensor data? Or, simply put from a patient perspective, “Can what happen to them, happen to me?” Retrieving and making use of “like-me” signal data based on similarity presents challenges far beyond digital marketing’s effectiveness in making targeted book and movie recommendations. By investigating and understanding those unique challenges, our research group has developed an approach based upon locality sensitive hashing (LSH). We will provide an update on our progress towards adapting LSH for fast and accurate Signal Like-Me capability.
2016 MIT Digital Health Conference
Principal Investigator Sherry Turkle
AI is transforming many industries. But addressing the full cycle, from development through deployment, requires key system engineering building blocks. Without these frameworks, efforts can be costly and unsuccessful. Learn how an AI systems engineering approach can avoid implementation pitfalls in this live webinar—a preview of the upcoming live virtual course AI Strategies and Roadmap: Systems Engineering Approach to AI Development and Deployment.