CMU-CS-20-102
Computer Science Department
School of Computer Science, Carnegie Mellon University


CMU-CS-20-102

Edge-Based Wearable Systems for Cognitive Assistance:
Design Challenges, Solution Framework, and Application to Emergency Healthcare

Siyan Zhao, Junjue Wang, Hongkun Leng, Yuqi Liu, Haodong Liu,
Daniel P. Siewiorek, Mahadev Satyanarayanan, Roberta L. Klatzky

March 2020

CMU-CS-20-102.pdf


Keywords: Empirical studies in ubiquitous and mobile computing, Ubiquitous and mobile computing systems and tools, Real-time system architecture, Edge computing

Cognitive assistants are computer-based interactive guides for complex activities such as emergency medical care. Recent advances in computing capability and edge computing make it possible to host such an assistant in a wearable device. We identify technical challenges facing the designer of a wearable cognitive assistant and describe pathways to solutions. We illustrate the solution space in the form of an automated end-to-end assistant to guide a novice through the application of an automatic external defibrillator (AED). Our results indicate that without such assistance, novices will fail, but technological barriers limit real-time success. Our work highlights challenges as well as new capabilities made possible by wearable technology in this domain.

24 pages

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