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• Situated Understanding of Errors in Older Adults' Interactions with Voice Assistants: A Month-Long, In-Home Study

  Amama Mahmood, Junxiang Wang, Chien-Ming Huang · 2026 · ACM Transactions on Accessible Computing

  This month-long field study examined how 15 older adults (ages 66-94) interact with voice assistants in their homes, with a particular focus on errors and conversational breakdowns. The researchers deployed Amazon Echo Dot smart speakers augmented with custom audio recording…

  voice assistants · older adults · conversational AI · errors · smart speakers

• Synergy of Artificial Intelligence and Extended Reality in Patient-focused Health and Well-Being Applications—A Systematic Review

  Tim Schwirtlich, Cheolmin Matthew Lee, Molly Beestrum, David C. Mohr · 2026 · ACM Transactions on Computing for Healthcare

  This systematic review, conducted by researchers at Northwestern University's Feinberg School of Medicine, maps the landscape of applications that combine artificial intelligence and extended reality (XR) for direct patient health and well-being outcomes. The review follows…

  extended reality · artificial intelligence · rehabilitation · mental health · accessibility

• Mapping Caregiver Needs to AI Chatbot Design: Strengths and Gaps in Mental Health Support for Alzheimer's and Dementia Caregivers

  Jiayue Melissa Shi, Dong Whi Yoo, Keran Wang, Violeta J. Rodriguez, Ravi Karkar, Koustuv Saha · 2026 · ACM Transactions on Computing for Healthcare

  Family caregivers of individuals with Alzheimer's Disease and Related Dementias (AD/ADRD) face significant mental health challenges — including stress, anxiety, depression, compassion fatigue, anticipatory grief, and burnout — yet have limited access to timely, affordable…

  AI chatbots · dementia caregiving · mental health · caregiver wellbeing · conversational AI

• How Multimodal Large Language Models Support Access to Visual Information: A Diary Study With Blind and Low Vision People

  Ricardo E. Gonzalez Penuela, Crescentia Jung, Sharon Lin, Ruiying Hu, Shiri Azenkot · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This CHI 2026 paper reports a two-week diary study with 20 Blind and Low Vision (BLV) participants (ages 19–75, 11 female/9 male, 13 blind/7 low vision) investigating how multimodal large language models (MLLMs) support real-world access to visual information. The authors built…

  AI · accessibility · multimodal large language models · MLLM · visual question answering

4 results.