AI-enabled multimodal monitoring for enhanced safety and functional recovery in elderly and post-stroke care: A mixed-methods study.

ABSTRACT:

Objectives

To develop, feasibility test, and evaluate an AI-enabled multimodal monitoring system to integrate safety outcomes, functional recovery and quality of life in elderly and stroke survivors in multiple care settings.

Methods

This was a 24-month mixed-methods study across 12 sites spanned from private homes, assisted living facilities, rehabilitation centers, to acute care transitions. The study was a quasi-experimental design, with three groups: integrated monitoring (n = 112), basic monitoring (n = 89), and usual care control (n = 86). 313 respondents were purposively selected using stratified purposive sampling. The multi modal system combines wearable sensors, ambient environmental control sensors, computer vision algorithms and voice analysis by adaptive fusion

SUBMITTER: Xue W 

PROVIDER: S-EPMC12536216 | biostudies-literature | 2025 Jan-Dec

REPOSITORIES: biostudies-literature