1. A method for assessing falls risk in one or more persons using a system comprising one or more inertial sensors and at least one processor, the method comprising: collecting reference data to generate a regression model using the at least one processor, and wherein the collecting of reference data comprises: measuring inertial sensor trial data using one or more inertial sensors on one or more persons during a walking trial; and measuring reference minimum ground clearance measurements associated with the one or more persons using an optical motion capture system having at least one camera during the walking trial; generating, by the at least one processor, the regression model using: (a) the measured inertial sensor trial data from one or more inertial sensors associated with one or more persons and (b) the measured reference minimum ground clearance measurements from the optical capture system associated with the one or more persons collected as the reference data during the walking trial, wherein the generated regression model represents minimum ground clearance parameters as a function of one or more parameters of the motion data from the one or more inertial sensors; after generating the regression model, measuring subsequent motion data using one or more inertial sensors on a first person while walking; calculating, by the at least one processor, a minimum ground clearance parameter of the first person using the generated regression model, wherein an input to the generated regression model comprises parameters selected from the measured subsequent motion data of the first person, and wherein the calculation is performed without use of data from the optical motion capture system; and generating, using the processor, a value indicative of a risk of fall for the first person based on the calculated minimum ground clearance parameter of the first person.