University of California

Jonathan S Woodbridge

Majid Sarrafzadeh

William J Kaiser

Hyduke Noshadi

Mars Lan

Wenyao Xu

Shaun S Ahmadian

Hagop Hagopian

Navid Amini

A saliency function is computed to indicate the saliency of each of a plurality of data points in a dataset. For each local maximum in the saliency function, a segment of the dataset is inserted into an index.

Efficient searching of stationary datasets

A method for determining the motive instability of an individual using foot pressure, foot speed and foot direction data collected from sensors on shoes. The sensed data is used to determine the minimum number and the placement of pressure sensors in the shoe. The data from the sensors is processed to extract spatial and temporal parameters as desired. The data is grouped into segments based on a segmentation rule. The trend in each segment is determined. The variability of the trend in each segment is determined. The risk of fall is computed on the basis of the trend and variance. The computation is adjustable by emphasizing certain parameters in order to tailor the instability assessment to a specific individual.

Method of assessing human fall risk using mobile systems

Growing community of inventors

Los Angeles, CA, United States of America

Jonathan S Woodbridge