Personalized multi-modal interfaces for cognitive aging: A narrative review of design and technological innovations

Abstract

This narrative review examines the design and execution of adaptive multi-modal interfaces aimed at improving autonomy and cognitive health in aging populations. This is a pressing necessity as the worldwide demographic of those aged 65 and older is anticipated to exceed 1.5 billion by 2050. By incorporating modalities like as speech, touch, gesture, and haptic feedback, these interfaces adaptively customize interactions to accommodate age-related sensory, motor, and cognitive impairments. This review integrates interdisciplinary literature from human-computer interaction, gerontology, and artificial intelligence, synthesizing evidence on cognitive and functional requirements, user-centred design principles, and enabling technologies such as wearable sensors and AI-driven predictive models. This demonstrates 95 % accuracy in predicting user preferences. It emphasizes that tailored interfaces enhance usability by 30 % for older adults and facilitate independent living, especially for individuals with mild cognitive impairment. This evaluation is presented due to the increasing demand for accessible technologies that address accessibility disparities and foster equitable cognitive engagement among various aging demographics. Additionally, this work also identifies research gaps, including the necessity for longitudinal studies and unbiased algorithms, thereby offering a thorough framework for advancements in adaptive systems. It underscores ethical considerations such as data privacy and cultural sensitivity to promote inclusive design.