Identifying fall risk using machine learning algorithms

A system for determining postural stability and fall risk of a person, comprising:

• at least one load detecting module configured to acquire a plurality of load data points;
• and
• a data analysis module configured to analyze the plurality of load data points received from the at least one load detecting module, wherein the data analysis module is configured to perform steps comprising:
• determining a plurality of posture states based, at least in part, on the plurality of load data points by applying a machine learning algorithm to the plurality of load data points;
• calculating one or more base punctuated equilibrium model (PEM) stability metrics based, at least in part, on the plurality of posture states, wherein the base punctuated equilibrium model (PEM) stability metrics comprise metrics corresponding to a presence of a plurality of postural states;
• calculating one or more advanced punctuated equilibrium model (PEM) stability metrics based, at least in part, on the plurality of posture states, wherein the advanced punctuated equilibrium model (PEM) stability metrics comprise metrics corresponding to a relationship between the plurality of postural states;
• and
• determining a balance score based, at least in part, on the one or more base punctuated equilibrium model (PEM) stability metrics and on the one or more advanced punctuated equilibrium model (PEM) stability metrics.