Biosignal-Sensitive Memory Improvement and Support Systems


Memory is necessary for our daily lives and activities, yet it is often fallible. Memory augmentation technology could improve and support our memory by facilitating memory training and providing memory assistance respectively. However, there remains a lack of research on utilising users’ internal states to enable just-in-time delivery of these interventions to improve receptivity and effectiveness. With the focus on helping older adults, my research involves the design, development and evaluation of memory training and memory assistance artifacts which infer users’ internal and cognitive context through physiological signals (biosignals). This work will contribute new concepts that build on previous research in the field of mobile computing and design guidelines for future work on augmenting human memory.

Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems
Samantha Chan
Samantha Chan
Postdoctoral Fellow

I create wearable, AI and digital interfaces to enhance human cognition and memory at the MIT Media Lab.