Prompto

Author:

Chan Samantha W. T.1,Sapkota Shardul1,Mathews Rebecca1,Zhang Haimo1,Nanayakkara Suranga1

Affiliation:

1. Augmented Human Lab

Abstract

Prospective memory lapses, which involve forgetting to perform intended actions, affect independent living in older adults. Although memory training using smartphone applications could address them, users are sometimes unaware of available times for training or forget about it, presenting a need for proactive prompts. Existing applications mostly provide time-based prompts and prompts based on users' cognitive contexts remain an under-explored area. We developed Prompto, a conversational memory coach that detects physiological signals to suggest training sessions when users are relaxed and potentially more receptive. Our study with 21 older adults showed that users were more receptive to prompts and memory training under low cognitive load than under high cognitive load. Interviews and an in-the-wild deployment of Prompto indicated that majority of users appreciated the concept, found it helpful and were likely to respond to its prompts. We contribute towards developing technologies with cognitive context-aware prompting based on users' physiological readings.

Funder

TEC, New Zealand

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture,Human-Computer Interaction

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1. Memoro: Using Large Language Models to Realize a Concise Interface for Real-Time Memory Augmentation;Proceedings of the CHI Conference on Human Factors in Computing Systems;2024-05-11

2. LAUREATE;Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies;2023-09-27

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