STTR Phase I: Gait Tracker Shoe for long term accurate measurement of walking and running

Period of Performance: 01/01/2015 - 12/31/2015


Phase 1 STTR

Recipient Firm

JKM Technologies LLC
525 Rookwood Place Array
Charlottesville, VA 22903
Firm POC, Principal Investigator

Research Institution

University of Virginia
351 McCormick Rd ECE Dept., Thornton Hall
Charlottesville, VA 22904
Institution POC


The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project centers around the ability to provide accurate gait data for every day real world activities. Certainly this could be something of a game changer in the field of locomotion rehabilitation where self-reporting of compliance is an issue. In the growing activity of running this can change the way runners (or even cross-country skiers or skaters with modified algorithms) train. With this capability runners would know the history of their gait through a training session or race. For an individual with a condition that needs long term monitoring this technology can provide for the first time, detailed data on how one locomotes in the real world. One can determine not only the number of steps one takes and how large each step was, but detailed information on what activities the user performed, such as walking up or down stairs; walking up or down slopes, walking versus running, etc. Finally, IMUs could be packaged in different devices that could be used to objectively measure rehabilitation activities other than walking. The proposed project uses advances in our ability to gather accurate information from Inertial Measurement Units (IMUS) and combines them with an innovative shoe design to allow economical measurement and reporting of out-of-lab locomotion for individuals. Using new mathematical algorithms the data from the IMU sensors can accurately determine gait, running or walking, parameters. They can also distinguish the type of locomotor activity a person is engaged in, such as walking up a hill vs running on a level surface. The analysis of this data over extended periods of time will be a practical application of the use of Big Data (large data sets where special analysis tools are needed). This work will allow low cost reporting in rehabilitation settings avoiding the issues of self-reporting and the high cost of supervised rehabilitation. This work will also develop apps for smartphones to allow real time feedback to individuals to ensure that they are following their prescribed rehabilitation. Advanced manufacturing with Bluetooth data transmission and induction charging will allow the IMUs to be placed inside the shoe sole protected from the elements.