RemiAssist: A Therapist-Supporting System for Photo-Based Reminiscence Therapy in Dementia Care
Shuchang Xu, Minglong Tang, Junyan Mao, Xiaofu Jin, Wazeer Zulfikar, Yasith Samaradivakara, Jiayi Zhou, Huamin Qu, Yuling Sun, Pattie Maes
ACM Symposium on User Interface Software and Technology (UIST), 2026.
AbstractLinksBibTeXProject
Despite growing interest in applying AI to photo-based reminiscence therapy (PRT) for people with dementia (PwD), existing systems primarily focus on PwD-AI interaction and often overlook therapists' critical role in practical PRT delivery. We present RemiAssist, a system that supports therapist-in-the-loop PRT through AI-assisted planning and real-time facilitation. RemiAssist incorporates two core techniques: (1) a Memory Graph, which organizes key life events from a PwD's photo collection into a hierarchical graph to support theme-centered intervention planning; and (2) a Context-Aware Guiding Strategy, which provides real-time suggestions to help therapists guide reminiscence conversations and respond to sensitive situations. A field study with eight therapist-PwD dyads suggests that RemiAssist was associated with a 44% improvement in planning efficiency, a 54% increase in conversation duration, and timely support for handling sensitive situations. We highlight opportunities for AI systems to empower therapists and enable more personalized reminiscence therapy in dementia care.
@inproceedings{xu26_uist1,
title = {{{RemiAssist}}: {{A Therapist-Supporting System}} for {{Photo-Based Reminiscence Therapy}} in {{Dementia Care}}},
author = {Xu, Shuchang and Tang, Minglong and Mao, Junyan and Jin, Xiaofu and Zulfikar, Wazeer and Samaradivakara, Yasith and Zhou, Jiayi and Qu, Huamin and Sun, Yuling and Maes, Pattie},
year = {2026},
booktitle = {ACM Symposium on User Interface Software and Technology (UIST)},
doi = {10.1145/3830398.3830485},
shorttitle = {{RemiAssist}},
eprint = {2607.24536},
}
Sonic Stage: Auto-Generating Interactive Spatial Soundscapes to Facilitate Dialogue Video Comprehension for Blind Viewers
Shuchang Xu, Xiaofu Jin, Gaurav Jain, Wenshuo Zhang, Huamin Qu, Brian A. Smith, Yukang Yan
ACM Symposium on User Interface Software and Technology (UIST), 2026.
AbstractLinksBibTeXProject
Audio description (AD) makes film and television accessible to blind and low-vision (BLV) audiences by narrating characters' actions. However, in scenes with lots of dialogue, AD often omits important actions because it is constrained not to overlap with speech. It is not yet known how to convey characters' actions during dialogue. We present Sonic Stage, a system that transforms dialogue videos into interactive spatial soundscapes, enabling BLV audiences to intuitively understand characters' actions and movements through immersive auditory cues. Sonic Stage conveys essential visual information during dialogue through three auditory techniques: (1) spatialized dialogue to represent spatial layout, (2) diegetic sound to convey character actions, and (3) interactive descriptions to provide context-specific visual details. Evaluation with 12 BLV viewers showed that Sonic Stage significantly improved video comprehension, spatial presence, and narrative engagement. We highlight opportunities for enhancing video accessibility across diverse genres through immersive, interactive audio representations.
@inproceedings{xu26_uist2,
title = {Sonic {{Stage}}: {{Auto-Generating Interactive Spatial Soundscapes}} to {{Facilitate Dialogue Video Comprehension}} for {{Blind Viewers}}},
author = {Xu, Shuchang and Jin, Xiaofu and Jain, Gaurav and Zhang, Wenshuo and Qu, Huamin and Smith, Brian A. and Yan, Yukang},
year = {2026},
booktitle = {ACM Symposium on User Interface Software and Technology (UIST)},
doi = {10.48550/arXiv.2607.20835},
shorttitle = {Sonic {{Stage}}},
}