Catalyst Awardee

Project Description

A multi-sensor wearable system with a personalized AI and multimodal biofeedback to improve balance of older adults at home

Alparslan Emrah Bayrak, PhD,and Antonia Zaferiou, PhD | Stevens Institute of Technology
Competition Sponsor: US National Academy of Medicine
Awardee Yer: 2021

Falls remain a leading cause of morbidity and decreased quality of life in our older adult community. About half of older adult falls occur in the home. In order to extend functional aging and healthy longevity, the multifaceted nature of fall risk requires holistic solutions that leverage emerging technology that can enter older adults’ homes. In our proposed research, we will leverage and develop technology that uniquely integrates wearables, personalized Artificial Intelligence (AI), and multimodal real-time biofeedback- including music-based biofeedback. We propose that, in order to provide older adults with the agency to understand and improve their balance day by day, we will need to deeply engage older adults in the design phases through a collaborative process. Within this user-centered design framework, we will innovate a multi-sensor wearable system to monitor older adults’ balance patterns and provide multimodal biofeedback that includes precise musical cues based on a personalized AI model running on a transparent user interface.

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