Eye2Recall: Exploring the Design of Enhancing Reminiscence Activities via Eye Tracking-Based LLM-Powered Interaction Experience for Older Adults
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866908806611468288 |
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| author | Han, Lei Wei, Mingnan Chen, Qiongyan Wang, Anqi Pang, Rong Liu, Kefei Chen, Rongrong Yip, David |
| author_facet | Han, Lei Wei, Mingnan Chen, Qiongyan Wang, Anqi Pang, Rong Liu, Kefei Chen, Rongrong Yip, David |
| contents | Photo-based reminiscence has the potential to have a positive impact on older adults' reconnection with their personal history and improve their well-being. Supporting reminiscence in older adults through technological implementations is becoming an increasingly important area of research in the fields of HCI and CSCW. However, the impact of integrating gaze and speech as mixed-initiative interactions in LLM-powered reminiscence conversations remains under-explored. To address this, we conducted expert interviews to understand the challenges that older adults face with LLM-powered, photo-based reminiscence experiences. Based on these design considerations, we developed Eye2Recall, a system that integrates eye tracking for detecting visual interest with natural language interaction to create a mixed-initiative reminiscence experience. We evaluated its effectiveness through a user study involving ten older adults. The results have important implications for the future design of more accessible and empowering reminiscence technologies that better align with older adults' natural interaction patterns and enhance their positive aging. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_02232 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Eye2Recall: Exploring the Design of Enhancing Reminiscence Activities via Eye Tracking-Based LLM-Powered Interaction Experience for Older Adults Han, Lei Wei, Mingnan Chen, Qiongyan Wang, Anqi Pang, Rong Liu, Kefei Chen, Rongrong Yip, David Human-Computer Interaction Photo-based reminiscence has the potential to have a positive impact on older adults' reconnection with their personal history and improve their well-being. Supporting reminiscence in older adults through technological implementations is becoming an increasingly important area of research in the fields of HCI and CSCW. However, the impact of integrating gaze and speech as mixed-initiative interactions in LLM-powered reminiscence conversations remains under-explored. To address this, we conducted expert interviews to understand the challenges that older adults face with LLM-powered, photo-based reminiscence experiences. Based on these design considerations, we developed Eye2Recall, a system that integrates eye tracking for detecting visual interest with natural language interaction to create a mixed-initiative reminiscence experience. We evaluated its effectiveness through a user study involving ten older adults. The results have important implications for the future design of more accessible and empowering reminiscence technologies that better align with older adults' natural interaction patterns and enhance their positive aging. |
| title | Eye2Recall: Exploring the Design of Enhancing Reminiscence Activities via Eye Tracking-Based LLM-Powered Interaction Experience for Older Adults |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2508.02232 |