Catalyst Awardee

Project Description

Human-machine interface for the assistance and care of elderly people with motor dependence: a transformative proposal based on computer vision and video analytics

Claudio Tapia Malebrán |Universidad de Chile; Gonzalo Rivera Lillo, PhD; Bárbara Torres Acin, EU.
Competition Sponsor: Chile Agencia Nacional de Investigacion y Desarrollo
Awardee Year: 2023

Human-Machine Interface for Assistance and Care of Elderly People with Motor Dependence: A Transformative Proposal Based on Computer Vision and Video Analytics
The initiative aims to design a human-machine interface (HMI) leveraging computer vision and video analytics to aid elderly with motor dependence. This interface will facilitate environment interaction through recognition of facial and body movements, enhancing user autonomy and mitigating dependence effects. The design process involves developing detection software, training algorithms on individualized gesture recognition, creating a real-time communication system, and conducting validation and usability evaluations in real settings.
A proof of concept will be trialed in health centers with selected participants. The system’s effectiveness will be assessed by its response accuracy in movement detection and device control, with end-user and healthcare worker feedback on its application in practical scenarios.
Anticipated outcomes include improved patient autonomy, reduced care dependencies, and minimized health risks, which may lead to decreased overall healthcare costs. Following validation, the next phases would focus on clinical trials, healthcare integration, electronic device manufacturer partnerships, cost-benefit analyses, and obtaining regulatory approval.
The proposal addresses an urgent need for innovative elderly care solutions, promising a significant shift in current care paradigms by integrating AI technology to support an aging population. With the elderly demographic expanding and heightened necessity for remote care due to the pandemic, this HMI system represents a critical advancement in healthcare technology.

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