Memento: Augmenting Personalized Memory via Practical Multimodal Wearable Sensing in Visual Search and Wayfinding Navigation

dc.contributor.authorGhosh, Indrajeet
dc.contributor.authorJayarajah, Kasthuri
dc.contributor.authorWaytowich, Nicholas
dc.contributor.authorRoy, Nirmalya
dc.date.accessioned2025-06-17T14:46:45Z
dc.date.available2025-06-17T14:46:45Z
dc.date.issued2025-04-28
dc.description ACM UMAP June 16-19 2025, New York, USA
dc.description.abstractWorking memory involves the temporary retention of information over short periods. It is a critical cognitive function that enables humans to perform various online processing tasks, such as dialing a phone number, recalling misplaced items' locations, or navigating through a store. However, inherent limitations in an individual's capacity to retain information often result in forgetting important details during such tasks. Although previous research has successfully utilized wearable and assistive technologies to enhance long-term memory functions (e.g., episodic memory), their application to supporting short-term recall in daily activities remains underexplored. To address this gap, we present Memento, a framework that uses multimodal wearable sensor data to detect significant changes in cognitive state and provide intelligent in situ cues to enhance recall. Through two user studies involving 15 and 25 participants in visual search navigation tasks, we demonstrate that participants receiving visual cues from Memento achieved significantly better route recall, improving approximately 20-23% compared to free recall. Furthermore, Memento reduced cognitive load and review time by 46% while also substantially reducing computation time (3.86 seconds vs. 15.35 seconds), offering an average of 75% effectiveness compared to computer vision-based cue selection approaches.
dc.description.sponsorshipThis work has been partially supported by NSF CNS EAGER Grant 2233879 US Army Grant W 911N F 2120076 US Army Grant W911NF2410367 ONR Grant N000142312119 NSF CAREER Award 1750936 and NSF REU Site Grant 2050999 In addition the authors would like to thank all our volunteers who provided the data at the University of Maryland Baltimore County
dc.description.urihttp://arxiv.org/abs/2504.19772
dc.format.extent11 pages
dc.genrejournal articles
dc.genrepostprints
dc.identifierdoi:10.13016/m2y9tg-aoih
dc.identifier.urihttps://doi.org/10.48550/arXiv.2504.19772
dc.identifier.urihttp://hdl.handle.net/11603/39076
dc.language.isoen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Center for Real-time Distributed Sensing and Autonomy
dc.relation.ispartofUMBC Student Collection
dc.relation.ispartofUMBC Information Systems Department
dc.rightsThis work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
dc.rightsPublic Domain
dc.rights.urihttps://creativecommons.org/publicdomain/mark/1.0/
dc.subjectComputer Science
dc.subjectUMBC Mobile, Pervasive and Sensor Computing Lab (MPSC Lab)
dc.subjectHuman-Computer Interaction Computer Science
dc.subjectMultimedia
dc.titleMemento: Augmenting Personalized Memory via Practical Multimodal Wearable Sensing in Visual Search and Wayfinding Navigation
dc.typeText
dcterms.creatorhttps://orcid.org/0000-0003-2868-3766

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