IoT and Older Adults: Towards Multimodal EMG and AI-Based Interaction with Smart Home
Wies{\l}aw Kope\'c, Jaros{\l}aw Kowalski, Aleksander Majda, Anna Duszyk-Bogorodzka, Anna Jaskulska, Cezary Biele

TL;DR
This study explores the use of EMG and EOG bioelectric signals as non-invasive, multimodal interfaces for smart home technology, focusing on older adults and impaired users, revealing potential and challenges.
Contribution
It introduces preliminary insights into EMG/EOG-based multimodal interfaces for smart homes tailored to vulnerable user groups.
Findings
EMG/EOG interfaces show promise for smart home control
Participants found multimodal interaction engaging and intuitive
Technological limitations highlight areas for future research
Abstract
We report preliminary insights from an exploratory study on non-standard non-invasive interfaces for Smart Home Technologies (SHT). This study is part of a broader research project on effective Smart Home ecosystem Sagacity that will target older adults, impaired persons, and other groups disadvantaged in the main technology discourse. Therefore, this research is in line with a long-term research framework of the HASE research group (Human Aspects in Science and Engineering) by the Living Lab Kobo. In our study, based on the prototype of the comprehensive SHT management system Sagacity, we investigated the potential of bioelectric signals, in particular EMG and EOG as a complementary interface for SHT. Based on our previous participatory research and studies on multimodal interfaces, including VUI and BCI, we prepared an in-depth interactive hands-on experience workshops with direct…
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Taxonomy
TopicsInnovative Human-Technology Interaction · Context-Aware Activity Recognition Systems · Technology Use by Older Adults
