New Mexico Patent of the Month – October 2021
In general, an environmental fall risk assessment is a process of identifying problems and offering solutions to hazardous areas in the homes. This process may also include a demonstration of common activities in the home (eg, walking from the bedroom to the bathroom) to assess the person’s functional abilities. People experience two forms of risk factors. Personal risk factors include age, gender, and ability. Environmental risk factors refer to hazards found around the person’s environment from uneven surfaces to the presence or absence of hand rails. Electronic Caregiver, Inc. has developed a system to predict the environmental fall risk of a user.
Typically, to prevent falls, a person might use home-health care systems with emergency alerts and an initial fall hazard assessment by a professional. Some of these potential hazards are not predefined or pre-existing and can therefore not be included in the initial fall hazard assessment. Electronic Caregiver has integrated a standardization of health data into a Machine Learning (ML) program to create a more accurate hazard detection. The data that feeds into the ML program is gathered from camera footage of risk assessments. The camera observes the environmental map, identifies the map, searches for and identifies the risk factors in the environment. These risk factors feed into the ML program and the process repeats while the ML program learns how to identify and assess the risk factors.
This automation of the fall risk assessment can reduce the high cost of home-health-care-monitoring and decrease the number of hazards to prevent falls. As the ML program advances, the accuracy of the risk assessment improves, creating a more reliable system over time.
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