Zibrio Inc.

Massachusetts Institute of Technology

Harvard College

Katharine Forth

Erez Lieberman Aiden

Erez Lieberman

William H Paloski

Frez Lieberman Aiden

A person's fall risk may be determined based on machine learning algorithms. The fall risk information can be used to notify the person and/or a third party monitoring person (e.g. doctor, physical therapist, personal trainer, etc.) of the person's fall risk. This information may be used to monitor and track changes in fall risk that may be impacted by changes in health status, lifestyle behaviors or medical treatment. Furthermore, the fall risk classification may help individuals be more careful on the days they are more at risk for falling. The fall risk may be estimated using machine learning algorithms that process data from load sensors by computing basic and advanced punctuated equilibrium model (PEM) stability metrics.

Identifying fall risk using machine learning algorithms

A method for determining postural stability of a person can include acquiring a plurality of pressure data points over a period of time from at least one pressure sensor. The method can also include the step of identifying a postural state for each pressure data point to generate a plurality of postural states. The method can include the step of determining a postural state of the person at a point in time based on at least the plurality of postural states.

Determining postural stability

Growing community of inventors

Houston, TX, United States of America

Katharine Forth